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The Harte Hanks Blog

Signals: Identify and Get to Know Your Customers Better

identify anonymous visitors with signals


A lot of our conversations lately have been focused on providing the right content to the right person at the right spot in the buyer’s journey—marketing in the moment. This is not a simple task, given the explosive growth of customer data we have at our fingertips, driven by the various touch points across digital, social, mobile and traditional channels.

One of the challenges to marketing in the moment is bringing this data together across online and offline channels and across devices to identify individuals and the context in which they’re interacting with us. In other words, we need to take all of this big data we have available to us and turn it into small data—specific information that helps us to be more responsive to each individual.

It sounds complicated (and there are complicated algorithms and model training involved), but the concept is actually quite simple.

The Evolution of Matching

We are essentially talking about the evolution of matching. Anyone that works with marketing data is very familiar with this process. We’ve been associating individuals to households and contacts to businesses for decades, fixing truncations and abbreviations, filling data gaps in the customer profile, etc. The difference now is that, thanks to our partnership with Opera Solutions, makers of Signal Hub, this matching can be done across online and offline interactions, all in one platform, in the time requirements the business demands. This broadens what we know about our customers, allows us to identify them more quickly and in new ways, and improves our confidence in the match.

Your goal is to make sure you understand who your customers are, where they are in their buyer’s journey, and what needs they have so you can talk to them relevantly. For example, if you provide a content marketing platform, and you see a prospect Googling about how to manage content development, hitting your website, interacting with your social platforms, reading a Forbes article on managing a content team, etc., you can identify this prospect in your CRM and add the data to the record. Or, if the person is not in your CRM, you can save the information for later to make the connection when you are able.

Now, you know who this web visitor is and have a more accurate picture of the context in which she is interacting with your company. It’s probabilistic—you won’t know the identity of this person with 100% certainty until she self-identifies in some way—but you can have enough confidence in the match to speak to her contextually.

In this case, the data may tell you this person matches to Jane Smith at Acme Company A in your CRM. Since she last interacted with your brand, she has moved on to Widget Company B and moved up in title, acquiring a small content team. You’ll probably want to provide her with some content geared toward helping her learn about best practices in managing a content team, how to improve efficiencies in her development processes, etc. She’s not ready for, say, pricing information or case studies geared more toward helping her to evaluate specific solutions. Without the probabilistic match between your anonymous web visitor and Jane in your CRM, you would have none of this information with which to provide relevant messaging. Or, with a slow turnaround time on the data matching, you could miss the opportunity to speak to Jane when she’s actively looking for information.

Respect the Data

You might be thrilled to match an anonymous prospect with an email address (and you should be), but don’t jump the gun and email this person too soon. An email address is a valuable piece of data that will help you to match further valuable data points to the record—use it to this end. Your smart data matching does not mean it is a good idea to actually email this prospect. Remember: the goal is to be able to interact with individuals in a more human, relevant way. Emailing a prospect when he has not explicitly given you his email address is equivalent to cold calling him (ugh!), and he likely won’t appreciate it.

The same goes for other pieces of information you have gleaned about your customer. A good way to turn him off is to appear to be stalking his web browsing behavior, for example, and sending him a bunch of articles relevant to that activity. Respect the data, and use it in a way that helps your customer to achieve what he’s looking to achieve without being intrusive.

But…Hold Your Horses

This all sounds great, and you may want to jump right in. But the reality of it is, a lot of marketing organizations are not ready to implement this technology and these processes. Why? They’re not collecting the right data in the first place. This is referred to as the “sparse data” problem. There is a lot of data out there coming from many sources that, when combined, can provide us with great insights—but we’re not collecting or combining it today. Many marketers collect the obvious data points—name, email, etc.—but not all the available data points that would be useful in achieving their goals, such as geo location, browser ID, device ID, etc.

Not surprisingly, this problem can be remedied by increasing your data collection according to your specific goals—but don’t underestimate this endeavor. It’s a complex process that requires clearly-defined metrics and a strategic plan. Prioritize your data strategy, starting first with data housed or produced from internal platforms and applications, before moving on to partner and third-party data.

Simple, right?

The whole idea of recognizing customers across devices and identifying “unknown” to “knowns” has been somewhat overcomplicated. It’s a natural struggle to understand everything that technology can do considering all the choices and what that means for marketing. At the end of the day, signals and the Signal Hub platform make it easier for us to understand more about customers, including who they are, which helps to interact with them more contextually, in the moment.

If you want to learn out more about our approach to bringing human interaction back to marketing, including building an effective data and martech ecosystem, check out the 5 Pillars of Best-in-Class Marketing.

Buyer Personas Are NOT Customer Segments: What You Need to Know

buyer personas are not just customer segmentations

Let’s pretend you’ve just moved homes. You probably expect to receive a few postcards from local retailers congratulating you on your new move and welcoming you to the neighborhood with a coupon for things like new dishes and towels. You’re a “new mover,” so that makes sense, right?

But what if you moved because a storm wiped out your home, or your family situation changed,  and now you’re downsizing to an apartment or temporary living? “Congratulations on your new home” doesn’t sound like the best message anymore, does it? Or what if you just got a big promotion at work and are moving to a significantly bigger home in a nicer neighborhood—do you want new towels, or would you be more interested in bigger ticket items like new furniture?

Your mindset, context and urgency for your path to purchase would be very different in these two examples. Furthermore, the items you might be interested in buying would be different, too.

This is an example of why traditional segmentations often get it wrong when trying to understand who a buyer is and how to engage with them in a relevant manner in the buyer’s journey.

Customer Segmentation vs. Buyer Personas

It is easy to confuse personas with the traditional segments we use to define groups of prospects and customers. They sound very similar. But customer experience practitioners need to clearly understand the differences between these powerful marketing tools and use them to their fullest advantage. These definitions should clarify the distinction between traditional segments and personas:

  • Customer segmentation is the practice of dividing a customer base into groups of individuals that are similar in specific ways relevant to marketing, such as age, gender, interests and spending habits. Customer segments help us at the campaign level and are used to select people to market to, or to define categories to put them in. A female buyer between the age of 30 and 40 who shops our category 6 times per year is an example of a customer segment.
  • A buyer persona is a semi-fictional representation of your ideal customer based on market research and real data about your existing customers. When creating your buyer persona(s), consider including customer demographics, behavior patterns, motivations, and goals. The more detailed you are, the better. Buyer personas take into account the situation and role of the buyer and the job they are trying to do in the buyer journey. For example, a recent mover to a smaller place due to change in familial situation, looking to buy the basic necessities quickly without spending too much, is an example of a buyer persona.

Related content: how we build useful personas

The easiest way to keep them straight is that segments typically rely on demographics and transactional data as the defining characteristics to define one group vs. another. Personas take into account the real-time, real-life situation of the buyer. What is the person trying to accomplish right now? And what is their emotional state as they go through the buying process? Think about it as marketing in the moment.

We had a group in here the other day claiming that the buyer persona at a big box home improvement chain is those who repaint their house every year. That’s not a buying persona; that’s a segmentation. ~Frank Grillo, CMO, Harte Hanks

Put the Person Back in Personas

We are living in the Attention Economy, or what Forrester calls, the Age of the Customer. Forrester explains that “Today’s customers reward or punish companies based on a single experience — a single moment in time.” Going back to our “new mover” example, a recent divorcee would probably be pretty alienated by your direct mail piece that welcomes him/her to the neighborhood with a coupon for a cheery set of dishes. The consumer may be so alienated that he/she never wants to buy from you again.

This means that every interaction your brand has with a customer must deliver some value to the customer based on their reality. You just can’t do that with demographics-based segments. You must go further to be able to speak to each customer in the moment in which they are situated.

As an article by Mark Evertz states, it’s time to “put the person back in personas.” When you walk into a store and begin to browse, it’s likely that a salesperson will ask you a version of “How may I help you?” to figure out your individual situation and needs. He would be able to find out if you are furnishing a new home. If you’re budget-constrained or looking for top-of-the-line items. If you’re happy or sad. If you have never shopped for a set of pots before in your life but need something basic now. If you’re pressed for time or leisurely browsing. All of these things make you the buyer you are and make up your persona—and there’s no way to know them ahead of time. You must figure them out in the moment.

The associate would not only hear your verbal response; he would also see you lean in or cross your arms or shake your head. He would be able to adjust the conversation and his recommendations to your cues.

These human responses—both explicit and implicit cues—have not disappeared now that we operate in a more digital environment. They are still there, but we need to find them and pay attention to them to behave in a more human, relevant way with each customer interaction. THIS is the key data, the small data, that we need to uncover to drive our personas.

Bring the Human Back to Marketing

An understanding of the customer’s situation (rather than just demographics), layered with his or her current spot in the buyer’s journey, allows us to create messaging and content that actually delivers value to customers in the exact moment that they need it. In other words, understanding customers in this way allows us to interact in a more human manner—exactly what our customers are asking for.

Stay tuned for my next post on HOW to get at this contextual information you need for effective buyer personas.

Learn more about our approach to bringing human interaction back to marketing and developing useful personas.

Do You Really Need that Survey? Better Ways to Improve CX

improve customer experience in financial services

In a recent interview with Quirk’s Media, Nancy Vogt, VP of Customer Experience with Zions Bank, discussed the implications of an important factor in market research: survey fatigue.

She explained, “In recent years, as we’ve become ever more cognizant of survey fatigue, we’ve had to think long and hard about our priorities when designing a survey, considering each question to decide whether it is just ‘nice to know’ or whether the response will be actionable.”

It is important to recognize that we do need actionable data to improve the customer experience, but survey fatigue is real and plagues our customers. It is therefore important to incorporate other less intrusive ways to collect data, optimize the customer experience and ensure customer satisfaction to maintain a customer-centric approach. Here are a few places to start.

Recognize the Data You Already Have

1. Interaction History

Personally, I greatly dislike talking on the phone, which should be obvious since I have only ever interacted with my bank digitally (I will do anything I can to avoid talking to a real person—any extent of Google searching, emailing, webchat, etc.). My parents, however, call their branch directly when they have concerns or questions. This type of interaction history should inform how our banks communicate with us.

For example, I really appreciate that my credit card company has analyzed my spending and communication habits and denies unusually large purchases—while immediately sending a notification text to confirm or deny the validity of such a purchase. I can easily respond via text without having to answer or make a phone call. My parents, however, should get a phone call to communicate with them in the channel of their preference and optimize their experience.

2. Social

Now more than ever, customers are interacting with banks digitally—via social, for example. Data from effective social support programs can be used to identify points of customer dissatisfaction, as well as trending support issues. Proactively mining this data can help banks to identify common problems and address rising concerns promptly, limiting negative impact and satisfying social customers.

@ChaseSupport does a great job at supporting customers on social. From difficulties with credit card applications to opinions about ATM locations, Chase customers are letting the bank know how they feel. And Chase responds! My colleague recently tweeted to @ChaseSupport about a problem with her mortgage held by Chase. @ChaseSupport looked up her account, reviewed the history and conversations with phone support, and added the social conversation to her customer profile. They weren’t immediately able to solve her problem, but they did assure her that it had been escalated appropriately.

By using social channels to engage with customers, banks are able to receive candid and real-time feedback—no survey necessary. They’re also able to improve the overall customer experience for those that prefer to interact on social media. Note: it is crucial that these interactions be associated with the individual’s customer profile to ensure a seamless experience across interaction channels (e.g. make sure the customer service agents answering the phones also have the social conversation handy for reference).

3. In-Branch Technology

Another option is to mine satisfaction data from non-intrusive technologies that also facilitate customer experience improvements. This article from The Financial Brand explains how credit unions have implemented technology like lobby trackers that allow them to track wait times, desired services, transaction times and more. This data provides insight into the customer experience and allows banks to optimize the experience they provide to their customers through efforts like increasing staffing during peak times. In addition, banks are deploying service kiosks that invite members to easily provide feedback by clicking a range of happy, neutral, or sad face icons, which members happily interact with (about 4,000 responses per month).

Take Meaningful Action on the Data You Collect

Your customers are trusting you with all of this data they’re giving to you. A good way to break that trust is by failing to use it effectively and continuing to bombard them with requests for feedback. For example, if a customer signs in with your lobby tracker upon each branch visit, yet consistently has to wait over 10 minutes for service, he’ll start to wonder why he has to bother with the lobby tracker—it’s not providing any improvement in his experience. When you approach this customer with a survey, he will probably ignore it, believing that it also will have no effect on his experience.

To avoid what can feel like a one-sided relationship, customers need to see value in providing data or participating in surveys when they are necessary. Recognize and make use of the data you are already getting from your customer interactions and customer journey, and these customers will be happier to respond to your occasional survey.

You may also want to check out: MetLife Marketing is Focused on Providing Value—You Should Be, Too

How to Use Buyer Personas to Improve B2B Customer Experience


align buyer personas to the buyer journey

Customer experience marketing is a proven antidote to the complex buyer journeys that characterize the B2B sector today. The goal is to serve highly relevant content to buyers in the right place at the right time, enhancing lead nurture and conversion to deliver better revenue growth.

Progressive firms are achieving this via intelligent one-to-one, in the moment marketing. Others are struggling to make the shift from product-centric to customer-centric approaches. How can they address this fundamental issue?

The good news is that persona research can provide many of the answers. I’m not talking about traditional personas rooted in demographic and firmographic data with an occasional sprinkling of psychographic insight. Persona research in the digital age needs to take account of buyers’ real-time situations, the specific tasks they need to fulfill and the challenges they encounter. This give a richer context to help shape the development and application of marketing messages and assets.

1. Understand the Buyer’s Situation

An understanding of the backstory and current problems or ‘jobs to be done’ should form the cornerstone of a buyer persona. There could be dozens of reasons why a buyer is in the market for a given product or service. Marketing activity achieves better resonance and engagement when it acknowledges and addresses these reasons.

For instance, the needs and challenges of a fast-growing start-up relocating to new premises could be entirely different to those of an established business that is opening a new office, and different again to a firm that is having to scale back its operations due to a difficult climate. Each of these scenarios could create a need for new technologies, furnishings or equipment, but there will be huge variations in buyers’ attitudes, emotions and priorities.

To obtain this level of buyer understanding, it can be helpful to talk informally with existing customers and establish the sequence of events that led them to require your services. Ask what actions they needed to complete during the buying process, and find out which caused the most aggravation.

These conversations can reveal valuable insights. They can form a strong foundation for persona-led marketing that cuts to the chase and addresses specific problems buyers are trying to solve, particularly those that are not met by competitors. Segmentation can also become more sophisticated, enabling marketing spend to focus on personas with a higher propensity to convert.

2. Gather Relevant Data

Once the various need-drivers for a product or service have been established, it’s possible to identify relevant ‘digital breadcrumbs’. These are key indicators of a buyer’s current situation and their stage in the buyer journey. Digital breadcrumbs can include Google search terms, social media comments or open source information related to pertinent issues.

The collection, organization and analysis of such data facilitates context-led persona development, unlocking the capability for one-to-one in the moment marketing. This enables marketing spend to be prioritized more intelligently, with activity aligned to the specific needs of individual buyer journeys.

For instance, at some point in the purchasing process, buyers look at the logistics of how and when a solution will be delivered. If persona research reveals that this is a bugbear for a target group, marketers can develop content that counters this, then deploy it strategically.

This approach can be augmented through analysis of data surrounding buyers’ digital and human exchanges with your brand. Interactions with your website and marketing automation platforms, sales conversation records and CRM tracking can all provide additional insight to enrich personas.

3. Align Buyer Personas with the Buyer’s Journey

Traditional personas – pen portraits rooted in demographic and firmographic data – played an important role in their day. However, in 2017 demographics and firmographics represent the finishing touches of a persona, not the core substance.

Today’s B2B buyer’s journeys involve multiple, convoluted steps, from ‘defining the specifics of a problem’ to ‘defining criteria to evaluate solutions’ and ‘determining where to acquire the solution.’ Each of these steps is associated with various needs and required outcomes. For marketers to navigate this environment and provide buyers with relevant assets that add value, persona research needs to give the full picture. That means understanding the buyer’s current situation, where they’re trying to get to, and the jobs they need to complete to get there.

It follows that B2B marketing strategies need to be rooted in fundamental contextual information about the buyer. Persona research must be strategically aligned with the buyer’s journey and leveraged intelligently via appropriate content and omnichannel tactics. While demographic and firmographic tailoring is important to achieve surface-level resonance, contextual insight enables buyers’ deeper needs to be addressed.

When marketers understand buyers’ situations and how they quantify success, strategies can be developed to help them complete tasks more quickly and easily. Intelligent persona research, effectively leveraged, can unlock whole new ways of working, enabling marketers to add tangible value to buyers in the moments that matter.

If Customer Experience Is the Battlefield, Mobile Is the Weapon of Choice

mobile customer experience

For most of us, our smartphone is practically an extension of our body. The vast majority of brands today, however, are struggling to orchestrate outstanding intuitive mobile customer experiences.

The smartphone is truly ingrained in our daily lives. As Google notes, 87% of us always have one by our side always, and 67% of us check it within 15 minutes of waking. Among other things, this means mobile technology is the primary channel in which we interact with brands, communicate with friends and family, read the news and restock our toothpaste (love you, Amazon app.).

In order to realize mobile’s vast potential, brands must create relevant, contextual customer experiences that simplify and enhance people’s lives. That’s where one-to-one, in-the-moment marketing comes in.

I’m not talking about mere personalization, which involves leveraging in-depth “descriptive” data about a customer (e.g. your name, favorite drink, buying frequency, or if you used a coupon) to deliver individualized messages and offers.

One-to-one, in-the-moment marketing goes a step further by also factoring in predictive data such as propensity to buy, time-sensitive variables (e.g. geo-positioning) and external variables (e.g. current weather and its impact on customer buying decisions). Or, as CMO Frank Grillo explains it, “The things that are driving me to buy and the way that I behave are very much impacted by who I am at that moment.”

Mobile is that connective element (or weapon) that enables marketers to deliver in-the-moment customer experiences tailored to “who you are at that moment.”

While 71% of marketers believe mobile is core to their business, many still struggle to bring it to life. So, what is the foundation upon which these one-to-one, in-the-moment experiences are built? Let’s take a look at the big three.

1. Connected, Accessible Data

Data is rarely the problem for brands. The challenge comes with connecting the data to extract intelligence and the accessibility of that data downstream at the point of customer interaction.

We’ve all researched a product on a retailer’s website and then walked into a store only to find it out of stock. Very frustrating.

Home Depot has tackled this challenge head on. Over the past eight years, they’ve built a foundation of data connectivity around inventory management and supply chain architecture to enable a single view of inventory. With over 2,000 stores and 35,000 SKUs per store, this is no small feat. And good for them, because a seamless customer experience both in-store and online, including universal visibility into inventory by store, is what customers expect today.

2. Insights and Intelligence

Okay, your data is connected and accessible. Now, what is your strategy to deliver intuitive, tailored customer experiences? This requires a combination of human and technology intelligence. Connected data fuels data scientists to build the right descriptive and predictive data cues to power the engagement models to drive business.

At the heart of these efforts is the explosive artificial intelligence (AI) market, which IDC projects will grow from $8 billion in 2016 to $47 billion by 2020. Furthermore, Forrester predicts enterprise investments in AI will increase 300% in 2017, compared to 2016. Brands must be able to connect their breadth of data and tie it to a single customer profile so they can then extract the insights and intelligence to transform the individual customer experience.

Need your coffee fix in the morning? Dunkin’ Donuts partnered with Waze to simplify this process. By elevating your coffee preference data tied to proximity to a Dunkin’ Donuts store, they can deliver in-app offers during that morning commute to help you scratch your caffeine itch. (Don’t worry; they only elevate offers when the Waze app identifies you have stopped.)

3. Ability to Deliver the Experience to the Customer

It all comes down to this: the last mile. Can you deliver an experience as unique as your customer in that moment?

This is the area where “mobile” takes on an ambiguous definition and gives marketers heartburn. Mobile can encompass mobile-optimized web, mobile-optimized email, SMS, beacon-driven notifications, mobile apps, mobile media and mobile-enabled commerce (including mobile payments). And with 80% of social media time occurring via mobile access, we might even consider social to be synonymous with mobile.

Very simply, I view your mobile strategy as your digital strategy: While it can include any of the above tactics, it is the culmination of connected data, in-the-moment consumer intelligence and the ability to deliver a tailored experience that makes customers say, “It’s like they know me!”

Let’s look at Starbucks — their commitment to their digital strategy, focus on innovation, ability to deliver and the resulting impact on their business. They understand the use of innovation to simplify and enhance the customer experience … and it’s paying off.

After launching mobile payments in 2011, Starbucks executed over 26 million transactions in the first year. And now, more than 21% of transactions at company-owned U.S. stores are executed via their mobile app.

Starbucks is now able to layer innovations such as voice-enabled ordering upon this foundational infrastructure to further simplify the customer-ordering process. Order simplification has been so successful that Starbucks last year reported challenges in physically processing preorders within their stores—a good problem to have.

Research has shown that simplified checkout, while convenient, can shrink transaction size by minimizing those spontaneous purchases. To combat this, Starbucks has committed to their AI/recommendation algorithms to elevate recommendations into the mobile app based on descriptive and predictive cues to deliver a true one-to-one, in-the-moment experience.

By continually gathering data on mobile interactions, you can refine customer profiles/preferences and in turn sharpen your understanding of their behavior and motivations. Data fuels relevancy, relevancy drives engagement, and engagement enriches data. This symbiotic relationship enhances our ability as marketers to better understand our customers in the moment and in turn orchestrate intuitive experiences.

Where Do We Go from Here?

Mobile is the key to creating one-to-one, in-the-moment customer experiences that are essential for success in today’s marketing environment. In future posts, I’ll examine what this means for:

  • In-app innovation
  • Mobile commerce
  • Mobile media

Please stay tuned!

The Magic Question: What’s as Important as Baseball?


First, a case study from Dr. Karl Hellman (Co-founder, Resultrek) and then an analysis by Frank Grillo (CMO, Harte Hanks).

Case study from Dr. Karl Hellman

In our 3-second attention span world, social media marketing often grabs attention with dramatic discounts: 30% off or more. But discounts erode profits and detract from brand equity: “Thirty percent off? What’s wrong with this product?”

A better way to grab attention is to borrow interest from a topic your target is already passionate about. When I need to find a way to grab attention fast, I ask myself, “What does the target customer care about as much as kids care about baseball?” Here is why.

P&G had a small regional soft drink called Sundrop which was facing a dire situation: No promotion funding in the face of low market share and intense direct competition (Mountain Dew) in a crowded category—think Coke and Pepsi. This lemon-lime flavored soda was sold only in the Southeast and had come to P&G in the 1980s as part of the acquisition of Orange Crush. As a regional product with no plans for rollout, Sundrop had a miniscule advertising budget. The brand manager’s challenge was to build share and volume for this tiny brand with no budget. She decided to focus on one geographic area where Sundrop had good distribution: rural North Carolina.

Sundrop’s major product characteristics were its sweet flavor and caffeine fortification. Early research showed that the product had particular appeal for 10 to 14 year old kids. With this in mind, the P&G team asked themselves what was really important in the lives of youths in these geographic areas? The answer they came up with was Little League baseball.

The core of the attention grabbing, promotional program the product management team developed was simple. Kids (and their parents) would collect Sundrop bottle caps and exchange them for Louisville Slugger baseball equipment – bats, mitts, gloves and balls. To stretch the Sundrop budget further, the brand manager persuaded Louisville Slugger to support a cross-tie promotion. The baseball company would donate the equipment, and in turn get invaluable (free to them) advertising and goodwill.

Next, the brand manager approached the local Little Leagues and convinced them to break their non-commercial tradition and endorse the cross-promotional program. The Little Leagues mailed letters to all their teams in the Sundrop territory describing the program and encouraging parents and kids to participate.

The program was successful beyond anyone’s wildest expectations. Whole communities participated in order to equip their local teams. As the success mounted, Louisville Slugger asked for financial assistance in fulfilling orders. Sundrop was delighted to respond; they had tripled their market share and sold thousands of gallons of soda as a result of the promotion. At that point, they could justify additional promotional expenses.

When you’re looking at a particularly difficult challenge of breaking through information clutter and overload, think about why those kids in little towns and farms all across North Carolina chose Sundrop over Mountain Dew, Coca-Cola or Pepsi. You can invoke this attention-grabbing rule: Build promotions that support values customers care about as strongly as kids care about baseball.

Analysis by Frank Grillo

The Sundrop case illustrates beautiful integration of multiple aspects of effective promotion. Each component is closely linked, like a Jenga tower where every block seems stuck to the others. It is hard to imagine this promotional home run without Louisville Slugger as the partner, support from the regional Little League organization, and so on.

The case highlights the value of testing: start small, try something new, and expand from there if successful. Tests can be very low cost, which makes them an ideal tool, especially when budgets are tight. They can help “money appear out of nowhere” because smart money tends to gravitate toward high-return marketing programs.

As is so often the case, market targeting and persona definition play a central role in the development of effective marketing programs. But the unique Sundrop situation forced the brand manager to apply them in innovative ways.

1. Market Targeting

Market targeting or segmentation is the process of dividing a market into smaller pieces. This helps marketers tailor their programs for greater impact. Today we like to talk about “markets of one” but this can offset program effectiveness.

Using a Strategic Game Board, we can imagine that Sundrop could justifiably anticipate a high ability to influence a small regional market. These markets are often ignored by the larger brands. Because of low market share, however, the best Sundrop could hope for was a moderate degree of success. When its market share tripled, everyone was surprised because this was a low probability outcome.

By accurately characterizing the chances of success as moderate, the brand manager could see a need to borrow equity from another brand. Shooting high, the brand manager went for Louisville Slugger. It made the bat swung by legends such as Babe Ruth, Ty Cobb and Lou Gehrig. Every Little Leaguer wanted to be a slugger, and some of this brand’s affinity would hopefully rub off on Sundrop.

2. Personas

The unique lesson about personas offered by the Sundrop case is its multi-dimensional application. Personas were nailed for kids, parents, local community groups and regional organizations. Each persona embraced little league baseball. Each resonated with Sundrop as an underdog brand as well as with Louisville Slugger as a champion’s brand. The task of collecting and submitting bottle caps was readily translated by all personas as “stretch but achievable.” Further:

  • Kids were willing to collect those bottle caps. They were motivated by the prospect of playing with new, “Slugger” equipment.
  • Parents were willing to buy Sundrop six-packs every week or so. In fact, it is easy to imagine a parent buying a six-pack of Sundrop and surreptitiously pouring it down the drain just so their kids could sleep at night but still have a good haul of bottle caps for the day.
  • Coaches were motivated to remind kids and parents about the promotion and the need for new equipment.
  • The co-sponsor was willing to donate free equipment because they saw the very real possibility of making life-long brand alliances.
  • Communities were willing to support the promotion, perhaps by making Sundrop available at social functions, or maybe even in school cafeterias. Perhaps they created collection centers to facilitate bottle cap counting and mailing.
  • The Little League organization was willing to make an exception and be more commercial for a higher good: support those oft-ignored rural communities and get them some badly needed new equipment.

The brand manager’s ability to find and focus on themes that were clearly important within her target market can’t be over-emphasized. It is nearly impossible to simultaneously characterize so many personas with such accuracy. But, it will never happen if you don’t try. That is the key lesson here: look for multiple personas throughout the distribution channel. Pinpoint the overlaps and tie-ins: these offer key opportunities for connections, synergy and market share growth.

Great Marketers Will Focus on Small Data for Success This Year

small data about your prospects paints a clearer picture

We’ve established that this is the year of the consumer. We’re living in The Age of ‘Me’, and that means that as marketers, we really need to understand who our customers and our prospects are—and we need to use that to speak to them contextually.

I started off my 2017 recommendations series by explaining that—rather than interacting contextually—marketing has been neglecting to seek out and react to our consumers’ cues as they provide them (like my experience with the online retailer and the shoes). The first step to remedying this is thinking beyond one-to-one marketing to one-to-one in the moment marketing. The next piece of the puzzle is looking at the small data for a better picture of your consumer, at a particular point in time.

It’s the Small Data that Matters; Stop Counting Everything

You don’t need to have a ton of information on me to understand what’s driving me. You need the right piece of information about me at a moment in time.

Robert McNamara was the Secretary of Defense during the Vietnam War. He espoused the notion that for any problem, you should define objectives, make a plan and measure your success. In order to determine whether or not we were successful in the war, he measured what he had available to him: bodies. He concluded that, because we were killing more people than we were losing, we must be winning. Clearly, that was not the case.

In marketing, our vision is often clouded by the same mistake: measuring what is easy or readily available to measure at the expense of what is useful to measure. We rely on clicks, store visits and other single data points that don’t really tell us what is happening in any given situation. And we collect a whole bunch of this information. Another CMO I know likes to say, “I’m looking for a needle in a haystack, and you people keep throwing hay on top of it.” We count everything we can count, but we are counting things that don’t matter—or we don’t understand the information we have.

Instead of looking at all of the data that’s readily available and possible to collect, we need to look at the real indications that we have a ready buyer. It’s our job to determine what an interested buyer looks like—and if there are some data points in that description that we can’t easily get to, it’s our job to figure out how to get them. This often means breaking down walls inside the organization to share information at a human level rather than at a channel or interaction level. It can also mean bringing in third party enhancing data that help you understand who the buyer is.

Once we know what this buyer looks like, we can build algorithms to help us identify more buyers and a content engine that allows us to match the exact right message to the right person in the right moment—or at least as close as we can get.

For more insight on small data, see Martin Lindstrom’s article on

The Next Step is Content: Small Messaging to Match Small Data

The importance of that message and the content it’s contained in is the third thing we must rethink as marketers this year. Check it out in my next post next week.

Customer Centricity Means Time and Money. Is it Worth It?

planning for customer centricity

Customer centricity, the customer journey and the customer experience are the big buzz in marketing. But customer centricity takes a lot of time and money. How can you be sure it’s paying off? You’re making changes, but are they the right changes? You have 1,000 priorities; what’s your best course of action RIGHT NOW?

You’re not alone in asking these questions.

I often see marketing executives that have good intentions around understanding and improving the customer experience. But in many cases, the financial business case isn’t formed enough or the success metrics aligned well enough to determine if the investments delivered an improved financial return for the company.

Senior marketing executives need a concrete, reliable method of getting from the idea of customer centricity to actually improving customer experience. And you’re playing against the clock. With limited budget and limited patience to wait for the ROI. Add to that, the need for new investments to be self-funding. No wonder it can be so difficult to get from the idea of customer-centricity to scalable business impact.

In my experience, there are four things you need to have in place to make sure your customer experience strategy and execution work can justify the investment and, at the end of the day, prove it worked:

  1. Data, insights and understandings that go way beyond NPS, clicks, calls and routine transactions.
  2. A more integrated plan and platform for technology and enablement tools to tie all the parts and pieces together.
  3. Skill and agility to create the content and assets required to fuel the myriad of conversations to be had with the customer and to make the experience contextually relevant and meaningful.
  4. Focus and diligence on things that significantly impact both the customer and the business in a positive, incremental and measurable manner.

Let’s take a closer look.

1. Data, Insights and Understanding

Marketers need to understand what the consumer is trying to accomplish at each twist and turn of the buyer journey and the customer lifecycle. What are they thinking? What are they doing? Why? What’s getting in their way? To customize your CX plan, you must use a whole assortment of data, insights and understanding that go way beyond the usual suspects like NPS, clicks, calls, etc. These metrics answer very specific questions about specific points in the customer experience but rarely tell the entire story about what the customer wants, needs, and why she feels and behaves in certain ways.

To better inform your decision making on what to invest in now, later or never, you should be relying on insights from your buyer journey diagnostic, voice of the customer research, data audits, and a variety of other inputs including your NPS and CSAT data. By combining these various data sources and types, you can begin to create a more complete picture of the customer. 1 + 1 can equal 3.

2. Integrated Plan for Technology and Enablement Tools

There are legacy systems in place across every business. Some are old and antiquated, some are new and shiny. Regardless, there’s typically a need to bring together data and technology in a different way to capture the right customer information—to ultimately make informed choices and to be able to execute on your CX ideas. For example, if you want to use info about a customer’s website activity to arm your customer service representative on an inbound call, you need technology integration that connects the website and the inbound call center and also surfaces the data to the rep in a meaningful way.

With thousands of technology options and tools, what are the right ones for your brand and your customer experience? You need the right combination of tools in place to capture and action data from or about the customer. The technology needs to enable a seamless and satisfying experience for the customer in way that creates economic value for your business.

3. Skill and Agility to Create Content

To really embrace and deliver on a relevant customer experience requires an abundance of content to be actioned in real time to deliver a relevant interaction and to keep the conversation going. Most organizations have a lot of latent content that’s created for different functions across enterprise, but rarely is it organized and catalogued in a way to fuel relevant CX. Frequently, I find that all of this content is more heavily situated in upper funnel awareness instead of deep funnel or nurturing content that helps in other stages of buyer journey.

It’s important to assess all of your current content, identify gaps and opportunities to improve it or more effectively use existing content, catalog it, and be committed to continuous process of content creation. You’ll need to be able to bring together many different bits and pieces in real-time or in batch around the customer and what they’re trying to do in each moment of the journey.

4. Focus on Things that Impact the Business

There’s lots of ways to go about delighting the customer. But just because you can do it, doesn’t make it the right thing to do. You need to evaluate each potential CX improvement in terms of its impact to the customer, as well as its direct or indirect impact to the company’s bottom line. You have to look at what’s good for the customer and brand simultaneously. If you solve too heavily for one or the other, it’s going to be a mismatch. If you solve for customer without worrying enough about business impact, you’ll find yourself at some point unprofitable. If you lean too heavily on what’s right for the business, the customer leaves you. You have to have the right balance.

This is difficult because customer experience is the accumulation of interactions that occurs over time. You have to take a longer and wider view of CX to truly evaluate how all of the actions you could do over time affect the experience over time—and to what extent the improvement in experience relates to an improvement in business results over time.

With so many options available, it may be difficult to decide which investments will provide the best bang for the buck. It is critical to evaluate and prioritize your options based on what delivers the best value for the customer at the proper level of resource and investment for your company.

Delivering Business Impact

If you have all four of these points nailed, you’ll have a more effective customer experience strategy and a much higher likelihood of being able to demonstrate and deliver business impact.

IoT and Micro-Moments: Optimizing Big and Small Data to drive Omnichannel Marketing

HarteHanks_MarektingTechnology_ROIIn our last article we discussed how the advent of IoT is bringing marketers an overwhelming amount of data, behemoth data, that can be synthesized into usable knowledge that can drive more effective customer journeys. With companies having access to all of this data, we’d like to talk more about how this data can be optimized and utilized to have the largest impact on your organization.

Beware the overzealous that want to board the big data train too quickly, although they have the very best of intentions. The same “bad data in – bad data out” (incorrect insights or conclusions) rule holds just as true, if not more so, in the world of big data analytics compared to traditional statistical analytics. Big data is compiled from an ever growing number of sources, much of which is unstructured. And simple rules of probability apply here – the larger the pool of data, the higher the likelihood that analysts will miss “dirty” data that can ultimately lead to identifying false positives or false negatives.

Unlike traditional first party data that historically has lived in relational databases, big data often consists of a tremendous amount of unstructured data. Correctly integrating and/or blending this data with more structured first party data is critical so as not to lead to analytic outcomes that are way off in left field. This problem is only exacerbated by the velocity at which data is created, which can largely be attributed to the growing mobile trends discussed earlier where data is transmitted on almost a continuous bases. Also, keep on the lookout for the increasing trend of automobiles being online, yet another massive pool of data generating “devices”. To help ensure that the “signal” can be correctly extracted from the “noise”, it is critical that the appropriate amount of rigor is put behind understanding the quality of the data source, how that data is collected, and how it is integrated and blended with other sources of data.

Despite the value of big data synthesized to be used effectively, there is also extreme value in small data – data that’s about people and emotion (in addition to small datasets gathered from a singular historical event). Small data can be ingested into big data sets, merged with behavioral or trending information derived from machine learning algorithms, and provide clearer insights than we’ve ever had before.

Here’s an example of both: The use of smart labels on medicine bottles is small data which can be used to determine where the medicine is located, its remaining shelf life, if the seal of the bottle has been broken, and the current temperature conditions in an effort to prevent spoilage. Big data can be used to look at this information over time to examine root cause analysis of why drugs are expiring or spoiling. Is it due to a certain shipping company or a certain retailer? Are there reoccurring patterns that can point to problems in the supply chain that can help determine how to minimize these events? 1

The issue here is that we cannot become so obsessed with Big Data we forget about creativity. You have to remember that Big Data is all about analyzing the past, but it has nothing to do with the future. Small Data, can also be defined as seemingly insignificant observations you identify in consumers’ homes. Things like how you place your shoes to how you hang your paintings. These small data observations are likened to emotional DNA that we leave behind. Big Data is about finding correlations, but Small Data is about finding the causation, the reason why. 2

Optimizing Big and Small data into business processes can not only save companies millions of dollars, but creates a buyer and customer journey that are seamless, continuous and maintains context regardless of the touchpoint. This omnichannel marketing approach should be the ultimate goal of marketers – creating a conversation with their buyers and customers based on trust and value exchange – which leads to strong relationships in an increasingly connected on- and off-line world.

Laura Watson is Strategy Director at Harte Hanks, and Korey Thurber is Chief Analytics & Insights Officer at Harte Hanks. Harte Hanks can help your brand create an omnichannel marketing strategy, contact us for a free assessment.


1 Forbes Tech
2 Small Data: The Tiny Clues That Uncover Huge Trends

IoT and Micro-Moments Marketing: Leveraging Big Data to Improve the Customer Journey

4-biggest-challenges_illustrations_2-1_v02-01Being connected via wearables without your mobile device is already a reality with untethered Tech, like Android Wear and the Samsung Gear S2, which both support e-SIMs tapping into your pre-existing cell network at no extra cost. It’s a good bet that every smartwatch brand will have an LTE version by the end of 2016, which means that while there’s a vast number of facts and untold nuggets of information that could surprise even big data’s most ardent followers. Big Data is about to become behemoth data.

Every day, we create 2.5 quintillion bytes of data (that’s 2.5 followed by a staggering 18 zeros!)1 – so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: sensors used to gather climate information, posts to social media sites, the Curiosity Rover on Mars, your Facebook video from your latest vacation, purchase transaction records, and cell phone GPS signals to name a few. Google alone processes 3.5 billion requests per day and stores 10 exabytes of data (10 billion gigabytes!)2

Whether it’s tracking driving habits for the purpose of offering insurance discounts, using biometric data to confirm an ATM user’s identity, or using sensors to detect that it’s time for garbage pick-up, the era of the iOT in which “smart” things can seamlessly collect, share and analyze real-time data, is here.

Imagine a world where your watch recognizes that you withdraw cash every Saturday so that you’re ready for the neighborhood lemonade stand and your evening outing, and you haven’t made your usual transaction yet. A helpful alert pops up on your device, and another reminder displays when you’re within a ½ mile of your Bank ATM where a retina scan allows you to withdraw funds. Your Smart Refrigerator identifies that you’re running low on eggs and yogurt, while your wearable identifies an open parking space within 50-feet of your favorite Saturday farm market stop, but cautions you that there’s a marathon starting in 2 hours so you better get a move on. A “ping” in your email indicates that the killer little black dress you’ve wanted just became affordable with a special discount coupon you received as you drive past the store. While you’re away, the sun comes out, so your Smart Home lowers the window shades, turns the A/C up a few degrees and suggests adding popsicles to the grocery list. Like any fabulous assistant, technology not only aids you, but anticipates your needs and helps you make smarter, faster decisions based on “advice” you can trust. This is the best way to use Big Data.

Having the ability to be smarter, faster and always connected without having to carry around a device (or anything at all)…great.

Using Big Data to synthesize all of the fragmented individual data points into an orchestrated, holistic, powerfully intelligent view of the customer to help them during these everyday micro-marketing moments…priceless.

Big Data allows brands to go beyond customer motivation and engagement in driving value exchange to allowing them to foster their brand affinity and cultivate their customer’s evangelism in real-time, responding to their customer’s behaviors even as their activities and likes shift.

Although simple in concept, many brands are struggling to get it right (or get started at all). Leading brands have already gained a powerful competitive advantage by adopting consumer management technology that allows them to understand and engage based on individual consumer preferences and observation of behaviors and buying signals in their Buyer and Customer journey – thus taking a big step toward making Big Data a strategic reality.

Is Big Data, or really behemoth data, really the answer all by itself? There is lot of insight to be garnered from that data, but the key is being able to quickly sift through it all, tuning out the noise to focus on the key patterns and meaningful relationships in that data.

Traditional statistical analytics techniques which focus on finding relationships between variables to predict an outcome simply won’t do when the goal is to optimize decisions using massive pools of data that are growing and evolving on a near-continuous basis. This is where machine learning comes into play and brings the needed “giddy-up” to the analytic component. Machine learning evolved from the study of pattern recognition within the field of artificial intelligence. The easy way to think about it is, it provides computers the ability to learn and improve without a specific program being written to tell the computer to “learn and improve”. Machine learning software identifies patterns in the data in order to group similar data together and to make predictions. Whenever new data is introduced, the software “learns” and creates a better understanding of the optimal decision. Think of it as the automation of the predictive analytic process.

There is certainly a lot of overlap between statistical analytics and machine learning but there is one key difference. The former requires that someone formulate a hypothesis and structure a test to evaluate whether that that hypothesis is true or not. For example, a hypotheses that states a particular marketing lever (i.e. a certain offer or message) will generate or “cause” additional account openings or sales. Machine learning does not worry about hypothesis testing and simply starts with the outcome that you are trying to optimize – sales for example – and uncovers the factors that are the drivers. As more data is introduced, the algorithm learns and improves its predictions in almost real time.
Interestingly, machine learning has been around for decades. But now, due to the massive explosion in data, cheaper cloud based data stores, and huge increases in computing horsepower, the interest in machine learning is really starting to hit its stride.

Laura Watson is Strategy Director at Harte Hanks, and Korey Thurber is Chief Analytics & Insights Officer at Harte Hanks. Harte Hanks can help your brand leverage big data, contact us for a free assessment.
Forbes Tech

IoT and Micro-Moments Marketing: Opportunities and Pitfalls

With the advent of smart technology, we are getting ever closer to the Orsen Wells imagined world of Big Brother oversight in everyday interactions…and many of us are starting to like it because it makes our decision-making easier, our lives more efficient and allows us to do more of the “fun stuff” we’d all rather be doing.

Marketers used to think about the “top of the funnel” with sales and marketing engagement strategies, but most consumers these days are starting their buyer’s journey quietly online through research using video, ratings and reviews and more interactive decision-making short-cuts. And they’re mostly doing it via their mobile devices. Tomorrow is fast-approaching though, as smartwatches mature and the need for “tethering” to a smartphone goes away, devices supporting e-SIMs that are able to tap into your cell network at no extra cost will magnify the Internet of Things (IoT) explosion of use and related data.

The popularity of wearables, especially fitness-related devices, has sky-rocketed over the last couple of years, with 39.5MM US adults using wearables in 2015, including smartwatches and fitness trackers. There’s an expectation that the number will double to 81.7MM users by 2018, or 32% of US adults.1

Wearable devices go way beyond the smartwatch and fitness tracker, with things like FitBark, activity monitoring for Fido, to Athena, a personal security wearable that may help save lives. Verily has a glucose-detecting contact lens and Google is set to use tech to target cardiovascular disease, cancer and mental health problems too. More devices are moving from the nice-to-have category to an integral-to-our-lives status.

With all of this cool, new tech, it’s the nature of marketers to want to use it to sell stuff.

And that’s where we, as marketers, want to caution our compatriots to take the highest marketing road. You can’t get any more personal than something you wear on your body, even sleep with. With great personal engagement comes great responsibility to ensure the consumer experience with your Brand is a beneficial – even trusted – relationship. In digital terms, a break-up takes only seconds. Marketing messages that are annoying in other channels have the potential to take on a new and amplified level of aggravation in personal, wearable devices…running the risk of customers divorcing themselves from your Brand forever.

Yes, new tech means new, small-data points resulting in a big (very big) data explosion measured on the zettabyte scale. (A zettabyte is a 1 followed by 21 zeros.)Finding ways to use that data in a meaningful, mutually beneficial way in micro-moments marketing will ultimately best serve both Brands and their customers.

Laura Watson is Strategy Director at Harte Hanks, and Korey Thurber is Chief Analytics & Insights Officer at Harte Hanks. Harte Hanks can help your brand utilize micro-moments marketing, contact us for a free assessment.


1 eMarketer
2 and the International Data Corporation

B2B vs B2C marketing analytics – the same, but different?

analytics illustrationI’ve spent much of my career working in data-driven marketing roles and delivering insights for B2C brands, but over the last decade the balance has shifted and I now work almost exclusively with B2B businesses. While some of the differences between the two worlds are to be expected, such as the availability of different data types and the more complex buying cycle in B2B, in fact there are a great deal of similarities in the techniques and types of analysis that can be carried out for B2C and B2B. So why aren’t B2B brands making as much use of analytics as their B2C counterparts?

At first I wondered if this was just my isolated view of the world, but a recent study* by B2B Marketing in association with Circleresearch seems to support this. It reveals that 73% of B2B marketers don’t feel their companies make the most of data, with the weakest skills being in the area of Predictive Analytics.

Not a day goes by where we don’t carry out one or more of the following analyses for the B2C brands we work with:

  • Upsell propensity modelling
  • Path to high value analysis
  • Segmentation
  • Share of wallet analysis
  • Cross-sell propensity modelling
  • Churn prediction

And yet, I still don’t see widespread adoption within B2B organisations. Of course there are exceptions, and some readers will be able to recount many examples of insight-driven B2B sales and marketing activities they’ve been part of. But it’s not commonplace.

In simple terms, the marketing objectives facing B2B and B2C businesses are the same. The difference however, is that B2B businesses tend to focus their efforts on acquisition activity, with much less attention given to “in-life” marketing. B2B buyer journeys are much more complex, lead times are longer, and involve multiple decision makers and influencers (Prospect Modelling and Lead Scoring are great examples of analytics used here, particularly with the tools that have been developed in the last 10 years).

While it used to be true that the low volume and variety of data was a limiting factor in B2B, this is no longer true. Data collected through inbound marketing activity and social channels is a rich and current asset, and the tools and platforms available now mean we can quickly convert this into insight.

Here are just a few ways that analyses most often used for B2C can inform marketing programs for B2B organizations:

  • Churn Prediction: Develop a model that predicts which customers are more likely to churn at the end of their contract. For B2B knowing who to contact, and with what message, has historically been tricky. However, analysis of previous contact behaviour and campaign interactions can help optimise future activity and identify the key decision makers.
  • Share of Wallet: Share of Wallet analytics is an area that has great potential in B2B. Most B2B organisations have an account management structure to maintain the relationship with their customers, and this typically means that high value accounts get 1:1 attention while low value accounts just become one of many for a beleaguered account manager. A Share of Wallet analysis can identify those accounts that still have room for growth, and will typically unearth some sleeping giants!
  • Path to High Value: We use this a lot with our B2C clients! Look at today’s ‘best’ customers and identify what was the sequence of events that got them there. Is their first purchase significant, or is it the acquisition channel, or just their firmographics? By recognising tomorrow’s best customers at an early stage, you can implement the right programs that will help nurture that growth

To put all of this into perspective, research by eConsultancy in association with Adobe** shows that only 26% of responding (B2C and B2B) organisations have a solid data-driven marketing strategy in place, so perhaps it’s no surprise that analytics isn’t as widespread in B2B as I’d hope to see. There’s definitely still room for improvement on both sides, so maybe the similarities are greater than I thought!

Harte Hanks has a team of Analysts, Data Scientists and Strategists to help you integrate analytics into your B2B sales and marketing plans. Is your company fully utilizing Analytic driven insights to better inform acquisition, growth and retention activities? Tweet us at @HarteHanks and share your experience.

* “Data Skills Benchmarking Report 2016-17”, April 2016
** “Quarterly Digital Intelligence Briefing: The Pursuit of Data-Driven Maturity”, April 2016

The Machines of SXSW Future

sxsw-600x379We’ve been urged (well, that’s maybe overstating a little) to follow up on the pre-SXSW evaluations post. In it, Alan opined that the three “tracks” most likely to get most industry attention were Wearables, IoT and VR/AR.

We’d say he pretty much nailed it. Well, except that (in our view at least) Wearables was usurped by discussions on AI and Machine Learning.

Not to say there wasn’t excitement about some of the world’s best start-up wearable companies demonstrating their products––particularly cool Korean firms like skin care and health device WAY and posture-adjusting wristband ZIKTO––but we were not as blown away as we’d hoped. Anyway, back to self-learning machines …

Artificial Intelligence
With the Google DeepMind AlphaGo triumphs against Lee Sedol fresh in our minds, we heard from the brightest and best in AI such as Siri co-founder Adam Cheyer and Allen Institute’s Oren Etzioni in a panel called “Can AI Systems Really Think?” We also saw Professor Pedro Domingos talk about “The Secrets of Machine Learning Revealed” which outlined the five tribes of AI scientists and their schools of thought.

Many others, including Dag Kittlaus (Cheyer’s co-founder in new firm VIV) and Pinterest’s Head of Commerce Michael Yamartino, discussed all the forms and factors in AI’s implementation in the current and future worlds of medicine, education, environment and, of course, marketing.

They all took it upon themselves to reassure us that the singularity is (most likely) still hundreds of years away. But if you simplify it down (and we had to so it all made sense) what they were describing was tremendously exciting. And this area of thinking is a very rich and fertile space for data-driven marketers.

You’ve probably seen IBM’s new branded point of view advertising featuring Watson. And you also probably know marketers are using Watson to (among other things) build predictive models for buyer trends and to build optimal customer journeys. A sandbox for the industry’s best analytic and strategy minds to test hypotheses and determine the most efficient sequence of touch points to create optimal returns––Watson consumes limitless amounts of unstructured data as it goes about its work.

And yet its still “just” a tool … a very, very artificially clever tool, but nonetheless completely controlled by us.

In the world of shopper experience, AI is helping to predict customer preference before they can even recognize their desire to purchase. Ecommerce sites like and parent company Amazon have created an art out of the science of personalized recommendations. AI can create the same level of customer service as a local storeowner who’s had the same customer for years … all in the blink of a cursor.

So learning machines are definitely going to feature in future SXSW Festivals.
But what about other machines and devices connected to each other, and us, via the Internet? We are referring of course to the IoT track…

The Internet of Things
Well, we heard many hours worth of discussion about connected cars, cities, homes and more. From demonstrations on the trade show floor to panels around Downtown venues, it was hard to avoid someone talking about the Internet of Things. We were keen to learn about people’s opinions on an ethical code for makers and coders building these connected experiences (from AppDynamic’s Prathap Dendi) and how connected devices should respect our privacy (panel including Intel and Microsoft representatives).

And we had many divergent conversations about IoT … a sure sign it’s already an embedded and popular topic. “Cognition Clash in the Internet of Things”; “Internet of Banking Things”; “IoT: A Thousand Touchpoints of Marketing?”; and more.

So. the Internet of Things will continue to spread into more niche conversations over the next few years which leaves us with our final forecast––VR/AR ubiquity.

Virtual Reality
And so it came to pass … VR was EVERYWHERE! The trade show stands were full of Gear VR and Google Cardboard devices encouraging everyone and anyone to be impressed … Sennheiser demonstrated Ambeo VR headphones that let wearers experience sound in 3D. SAP promoted their Digital Boardroom, allowing users to enter a shared space and review documents using VR devices. And of course many panels and sessions took the trend to heart as they vied for attendee attention.

With more mainstream devices making it possible for more and more people to access VR content, the question for marketers becomes: What stories make the most sense?

The VR filmmakers at the panel discussion “New Advertising Models for Virtual Reality” sought to answer just that. All agreed that no marketer wants their advertising associated with a VR injury––so creating TVC style spots to be consumed instantly is unlikely to become standard practice.

Rather, the best brand-in-VR experiences are when audiences are transported to an experience that fits your brand values. Perhaps even your product, it it’s relevant in the case of the film. If all else fails, brands that sponsor a VR film can grab some of the attention—even if they’re not the stars of the show. But curating and presenting content associated with your brand personality is at least one way of capitalising.

Across the various VR sessions, many agreed the New York Times had scored the biggest hit so far with its Google Cardboard collaboration, “The Displaced”—and according to the Times’ SXSW session, they’re planning to ramp up VR editorial features to around twice monthly.

The Times’ VR story played out so well because they solved two key problems: 1) They literally put Google Cardboard kits in the hands of their readers by delivering sets with the Sunday paper; and 2) with “The Displaced,” they told a story that resonates with their brand’s core value of providing exceptional journalism to its readers. By adding a VR component to this particular story, they transported readers into the lives of three refugee children displaced by war and persecution. An essential story brought to life in a format that delivers more than important information: It creates empathy.

The best VR, everyone agreed, isn’t what you see, but how it makes you feel. And, as the technology becomes more and more commonplace, the machines of the future that let you feel a connection on a more visceral level, will win the day.


Alan Kittle is Global Executive Creative Director at Harte Hanks, and Andrew Womack is Group Creative Director at Harte Hanks.

Pre-SXSW: Three Trends and Tracks That May Impact Your Marketing Plans in 2016

As I prepare for my second pilgrimage to Austin, to immerse myself in all that is emerging and mind-blowing in our industry, I thought I’d curate some of the information the organizers are now sending to registered attendees. There are three very important customer engagement trends, or “tracks” as SXSW calls them, that every marketer will want to evaluate.

The evolution of wearable technologies
An emerging trend last year will become even bigger this year, as more products enter the market. In 2015, Samsung and others showcased smart watches, VR headsets, fitness trackers, sensor clothing and so on. The Apple Watch launched post-event (their rumored SXSW pop up shop never did appear) and many, many other companies released products in a move towards a future where “quantifiable self” becomes a “thing”.

This year the big evolution seems to be a convergence between fashion, technology, art and other cultural influences. Within the SXStyle Convergence Track sessions and events, I’m hoping thought leaders answer a pertinent question for marketers everywhere, “What branded experiences are possible with emerging wearable technologies and what useful data can I collect to enhance my relationships with customers who have them?” Creatively, considering these devices as inputs and outputs for campaigns ushers in a brave new world.

And if you consider, as you should, that wearable technologies form part of the connected devices ecosystem that is the Internet of Things, then you’re already prepared for the next trend …

The potential of the Internet of Things
Ever-higher speed connections are creating opportunities for devices to converse with each other through the Internet. IoT means smart cities; connected cars; sensor and wearable technologies; connected homes and appliances; and so much more; speak to each other and can make decisions on our behalf. The on-going conversations about Artificial Intelligence, even in something as user-friendly as Google Now, also fuels conversation on IoT.

“The Internet of Things is nothing short of the Fourth Industrial Revolution.” – Jamshed Dubash, “Marketing and The Internet of Things: Are you Ready?”

The big data created can, theoretically, be used to create enriched experiences between brands and customers. Figuring out how to wield the data to do this, though, is very difficult … honestly, marketers seem to have given up trying to get their heads around “big data” as a topic and have moved on to IoT––hoping this will help make the real world applications of information more obvious and easier to get their heads around.

Brands taking advantage of third, fourth and fifth screens in fridges, cars and watches … building in unrivaled relevance and usefulness, will win the engagement game in the near future. I hope the sessions focussing on IoT help us all get our heads in the game. Speaking of games …

The explosion of VR and AR
360 content is everywhere, already. You can see it in your social feeds; on YouTube channels; through cardboard viewfinders and soon on gaming consoles. Global brands like Samsung are building technologies like the Gear VR headset and Gear 360 camera; Microsoft is waiting for the right time to launch their Augmented Reality headset, the Hololens; Facebook-owned Oculus Rift made VR accessible to everyone and days ago (at Samsung’s Unpacked event in Barcelona) Mark Zuckerberg proclaimed the growth in popularity will be exponential … his presence reinforced original statements made when they spent $2 billion when buying Oculus.

“This is really a new communication platform … We believe this kind of immersive reality will become a part of daily life for billions of people.”

So if you’re a brand built around an experience not easily replicated on a website, or in a showroom or through a telephone agent, VR content can create immersive experiences that genuinely offer a window into a world that your customers could live in. Harte Hanks’ David Chandler offers insight into how brands can harness VR effectively in this blog post.

Of course this doesn’t even consider the notion that the pure entertainment value of great advertising could be enriched with VR. Will someone be brave enough to create a VR Super Bowl LI commercial next year? I hope so.

So. There you have it. Just three trend tracks I’ll be engaging with in Texas. There’ll be more to follow from me, post-event. And a whole lot to keep your eye on over the next few years!

Are you planning on attending SXSW this year? Tweet us at @HarteHanks and let us know which tracks you think will draw the biggest crowds this year.

The Critical Role of Analytics Driven Insight in the Financial Services Sector

There is a critical need for Analytics Driven Insight in the Financial Services (FiServ) sector. The customer journey is no longer solely about the in-branch experience or siloed traditional marketing deployed by marketers. Today, a FiServ institution can influence the customer experience across a multitude of interaction points.

Examining specific sectors within Financial Services, there is a tremendous amount of disruption at the various interaction points across the customer journey:

Retail Banking: The branch network is still highly relevant today but expect routine transactions to continue to migrate from “brick-and-mortar” outlets at the rate of 4% – 5% annually. Financial Services institutions are continuing to turn their attention to the digitization of transactions as well as the digitization of the in-branch experience by integrating digital tools for the branch staff to use to improve service.

Consumer Lending/Credit: Financial Technology – also known “FinTech” companies – are the big drivers of disruption in consumer finance. Companies like borro and LendingClub to name a couple have stormed in and grabbed market share from traditional banks. These same traditional banks are now scrambling to make up lost ground by partnering with or acquiring FinTech firms to create more impactful and relevant interaction points for their customers. In addition, companies like PayPal and bitpay have and will continue to change the way people pay for goods and services, which in turn will continue to influence how we use the old-school “plastic” in our wallets.

Wealth Management: Traditional Wealth Management entities are starting to augment their core, face-to-face wealth management advisor capabilities with online capabilities. Millennials are arguably the most critical segment in the marketplace and as they build wealth, Wealth Management organizations need to be ready to interact and engage with them using the appropriate channels, technology, etc.

State of Analytics Driven Insight in Financial Services
So how do Financial Services institutions best inform marketing and business strategies across the sectors mentioned previously? Analytics driven insight is the key! Marketing analytics have been a mainstream, high-value add in the Financial Services industry for quite some time. In fact, many would agree that marketing analytics essentially “grew-up” in the FiServ sector, driven in large part by the vast amount and quality of data stored by financial service institutions. The FiServ sector is a veritable playground for traditional marketing analysts and statisticians to hone their data mining and insights generating craft.

But the world has changed…..and here is what is behind it:

Exponential Data Growth: More data has been created in the past two years than in the entire history of the human race. By 2020, 1.7 megabytes of new information will be collected every second for each individual on the planet (Forbes). And it’s not only the volume of data….it’s the speed at which it is growing and the variety of sources. Financial Services consumers are generating new data by visiting provider’s websites, transacting online and interacting with various forms of online media. This new pool of data combined with more traditional direct mail, email, telemarketing and first party customer data, is a powerful enabler to better inform spend across a multitude of channel/media choices.

It’s “BIG Insight” that matters: More data is just that….”more data” unless the FiServ entity can wrangle, manipulate and mine that data for better targeting and insight. Financial services organizations have to more closely align themselves around customer’s needs as opposed to traditional product or business lines. Data analytics is driving this trend to enable FiServ institutions to become more customer oriented – not only to know who they are, but where they are (online or branch), and what types of deposit, lending, and wealth management products and services they are interested in.

Increased use of Marketing and Data Management Platforms (DMPs): What used to be available to only the largest financial service institutions is now becoming much more prevalent in mid-tier institutions, enabling them to coordinate and optimize customer interaction points across online and offline channels. By utilizing a DMP the Analysts can more clearly understand WHAT action is being taken and in what channel, WHEN it is being taken, and WHO is taking it. By also incorporating first-party data and having the appropriate tags placed on each page of the digital journey, financial services analysts will have a plethora of data to influence and optimize experiences across the entire customer journey.

Customer-Centric Analytics…NOT Digital Analytics: It wasn’t that long ago that digital marketing was primarily about broad reaching ad buys based less on robust targeting and more on what “felt like the best thing to do”. The “old school” individual/household level data that Financial Services Analysts cut their teeth on has now become a reality in the digital space! Digital marketing is very simply becoming more addressable and more targeted, with a greater portion of ad spend happening at a very targeted individual level. All the analytic disciplines (campaign test design, campaign analytics, predictive models, segmentation, frequency and cadence of touch, etc.) that grew-up in the FiServ sector using individual and household level data, is now being used heavily across addressable digital media – as well as in conjunction with traditional offline data. Everything that was “old” has become “new” again. Please also see my related and recent blog post on fractional attribution.

Harte Hanks has a team of Analysts, Data Scientists and Strategists to help you navigate the new landscape. Is your company fully utilizing Analytics Driven Insights to better inform business and marketing strategy? Tweet us at @HarteHanks and share your experience with us.

How to Individualise Your Marketing: Smarter Demand Generation and the Rise of Micro-targeting


“The importance of customer experience is on the rise; marketing is on the hook”. So said Gartner for Marketing Leaders in a 2014 research report. It predicted that customer experience, not product differentiation, would be the new battlefield for organisations wanting to achieve standout. And it said marketing would be expected to ‘create exceptional branded moments at every customer touchpoint’.

Two years on, the B2B sector is in the thick of this new reality. Linear buyer journeys have been replaced by a more episodic, multi-interaction buyer ecosystem. Every customer interaction is crucial and must be carefully planned, crafted and delivered. Traditional personalised marketing is no longer enough. We have entered the age of individualised marketing.

What is individualised marketing?
Micro-targeting is gaining increasing attention in the B2B sector. Drawing on data and analytics to better understand target audiences or personas, it enables real-time delivery of content tailored to buyers’ specific needs at the exact time of need. This is individualised marketing. It enhances the buyer experience via targeted and relevant one-to-one interactions.

Naturally, individualised marketing involves a highly customised approach to content creation and relationship building. Smarter demand generation is a critical enabler here. It goes beyond traditional demand generation to ensure all audience interactions are based on insight, tailored to the individual and deliver an impact. Achieving this requires sophisticated deployment and integration of data, tactics, people and technology.

Discover, Create, Act
So what steps can B2B marketers take to individualise their marketing through smarter demand generation? Grouping activities into three distinct but interconnected areas can provide a springboard for success.

Discover – The first step is to understand your current situation. That might involve defining your audience, developing more comprehensive personas, augmenting data and establishing the most effective approach to meet your goals. It can be beneficial to conduct a high level demand marketing audit which culminates in:
• a summary of the existing situation
• a gap analysis against best practice demand generation
• top line recommendations for change
• a roadmap of prioritised and sequenced activities and investments to make the recommended changes.

Create – Once the foundations are in place, marketing campaigns, assets and models can be developed as the basis for delivering individualised marketing.

Integration is an overused term, and often focuses on connecting systems or tactics. But it can be much more than that. It is about how the four dimensions – data, tactics, people, technology – are plugged together to create meaningful interactions. A truly integrative approach leverages insight to improve targeting, messaging and creative. It ensures multiple resources across marketing, sales, agencies, service providers and customer service work cohesively and responsively, drawing on a unified view of data, interactions and systems.

Act – Micro-targeting involves the optimisation of marketing technology to facilitate one-to-one conversations across an integrated set of channels and touchpoints. It’s important to ensure digital and human interactions don’t operate in isolation. Digital is the platform from which to plan, create and deliver many interactions with human input built in. Think of live chat, responsive one-to-one emails or social conversations: digital interactions delivered by humans. A central feature of smarter demand generation is the convergence of people and technology.

In today’s complex buyer ecosystem, individualised marketing can deliver significant, measurable pipeline impact. Alex Gill and Alana Griffiths from Harte Hanks explore this theme in detail at B2B Marketing’s InTech breakout session: Making Demand Generation Smarter.

How to Optimize Spend with Fractional Attribution



When traditional “database marketing” first took off in the early 1990’s, marketing performance measurement and attribution was quite simple. We generated sales and direct mail campaign performance reports using a handful of dimensions. Attribution was easily derived through business reply cards (attached to direct mail pieces), phone numbers or tracking codes. We also used indirect attribution rules by making control group comparisons. We were fairly accurate and the process was easy to execute.

The Current State of Attribution

We all know that the marketing landscape has changed … and it continues to evolve with massive channel proliferation. With so much data and so many options regarding how to best apply a limited marketing budget, how can a CMO receive richer insight to influence tactical decisions that will improve media/channel performance?

Let’s first examine the various states of attribution from the viewpoint of the modern day marketer:

  • Direct Attribution: Still used widely today and still relevant. A specific customer behavior (e.g. a purchase) can be “directly” attributed to a given marketing stimuli via a unique code, landing page/URL, response device, etc. However, other marketing stimuli may have created momentum and been a significant contributor to the consumer’s ultimate decision to purchase.
  • Last Touch Attribution: Attributing the desired customer behavior to the last “known” marketing touch. Similar to “Direct” Attribution, but not always the same, here the marketer attributes the desired customer behavior to the last known touch. This method is very common when there are no specific tracking codes/tags that tie a desired customer behavior directly to a specific marketing stimuli.
  • Multi-Full Attribution: Channel proliferation has led to individual channel/media silos, each with their own unique attribution rules. The separation of traditional offline data and online data is very common. For example, direct mail data is stored in a traditional customer database, email data is stored with the email service provider, and online data is stored by various DMPs, by vendors/partners that are contracted to capture it, each often with their own siloed attribution logic taking FULL credit for the same desired behaviors.
  • Rules Based Attribution: Building on the “Multi-Full Attribution” described above, here marketers use what is often called a “common sense approach” to proportionally assign attribution to very siloed marketing stimuli. For example, a business had recently identified the large overlap between their direct mail and digital channels. For the overlapping purchases identified in both groups, 100% of a given purchase was attributed to direct mail, while simultaneously 100% was also attributed to a combination of digital channels. A rule was then quickly implemented to assign 20% of the attribution to the direct mail channel and proportionally reduce the attribution by 20% across the various forms of digital media. So, it is “fractional” by the simplest definition, but no real math or analytics was being used to assign the “fraction” to each media/channel.

Each of these options contains significant attribution bias towards channels/forms of media, that when taken for face value will result is less than optimal decision-making.


What’s Next and What is Fractional Attribution?

Marketers must now leverage math, science and statistics to analyze and derive insight from large pools of data, much of which can now be integrated across channels to inform decisions across touch points during the customer journey. Fractional Attribution is a necessary tool for understanding campaign performance across a multitude of touch points.

Through advanced (and proven) analytic techniques, a weighting calculation is developed and applied to the various marketing touches during the customer’s buying journey. In short, you are attributing a portion of that customer’s purchase to each of the marketing touches that impacted the customer’s decision to buy.

Harte Hanks has a team of analysts that work with marketing organizations to create a fractional attribution model through a collaborative development process:

  1. Define the overall objectives and identify the behavior metrics you want to positively impact (e.g. response, sales, conversion, product registration, etc.).
  2. Define and implement the roadmap including identification of key performance indicators (KPIs) and setting the overall attribution approach. Companies have used both “quick start” fractional attribution solutions and more robust solutions that require dedicated data stores and data integration tools.
  3. Collect and compile the data.
  4. Execute the fractional attribution solution and create the scenario planning tool.

The “scenario planning tool” is what enables the user to optimize media/channel performance. Using the tool, the analyst or marketer can quickly run “what-if” analyses to estimate the impact of reallocating marketing spend across channel/media or removing a channel/media from the mix altogether. The end result is a much more informed decision that can result in significantly higher returns from your marketing budget. Performance data and insights from the optimization exercise are then used to calibrate and refine the attribution engine going forward.

Fractional Attribution rooted in proven math and statistical techniques is a critical tool to accurately improve and optimize the performance of an incredibly fragmented and complex system of channels and media, both online and offline.


It’s not perfect – no marketing science or advanced marketing analytic solution is. But a robust modeled attribution solution is proven marketing science, and those that leverage it appropriately will generate higher return from their marketing spend and outperform their competitors.

Has your company used fractional attribution to better analyze your marketing spend? Tweet us at @HarteHanks and share your experience with us.

How Pharmaceutical CRMs Can Lead to Healthier Relationships

Boosting physician and patient engagement

pharma CRM postCustomer Relationship Management (CRM) software offers a great deal of potential for the pharmaceutical industry. However, this is a complex sector, riddled with regulations surrounding sensitive data. It is not easy to find a solution that fits business needs while complying with relevant laws. This is especially true at an international level when different rules need to be observed for different countries.

Purchasing a standard CRM solution and trying to adapt it to various business and regulatory requirements is time consuming and difficult. Inevitably it involves compromise and hidden expense.

Instead, many pharmaceutical companies could benefit from international CRM programs that are purpose-built from the ground up by a marketing services provider.

Bespoke CRM for pharmaceuticals

A truly customized approach uses business goals as a starting point and builds a CRM framework around them. This ensures variations across different countries can be accounted for and embraced at an early stage, rather than being bolted on later. The result is a highly specified solution intrinsically optimized to meet business needs. It can have built-in scalability and the flexibility to handle international differences in data laws or standard practice, such as call centre versus nurse-led activity.

Ultimately, custom-built CRM offers better value and efficiency. Adapting existing systems is expensive, license fees can be high and product release cycles can delay the implementation of certain functionalities.

Using an MSP to build, manage and implement the solution brings multiple advantages. Since all aspects – from database management to phone calls, emails and SMS to direct mail – are handled by one organization, the program is more cohesive and affordable. What’s more, sensitive data is all held securely in one place.

Physician and patient communications

The best pharmaceutical CRM programs empower physicians and patients to make better, more informed choices – whether they’re prescribing treatment or following it.

Meeting physicians in person is becoming increasingly difficult for pharmaceutical companies. Physicians are often under pressure to see a certain number of patients per day, leaving limited time for meeting with third parties. Some countries also have complex regulations surrounding personal interaction between pharmaceutical companies and medical professionals. In many cases, direct marketing can play an effective role alongside or in place of face-to-face meetings. It enables physicians to keep abreast of the latest developments in treatments and processes such as pharmaceutical-led patient support.

Patient-focused activity varies depending on the nature of the patient’s condition, where they are in the treatment cycle, the level of data available and nuances of their country of residence. Naturally, when more is known about a patient, activity can be better tailored to their current needs and communications become more meaningful.

A central aim of pharmaceutical CRM should be fostering good relationships between patients and physicians. This means acknowledging the authority of the physician in prescribing drugs, while enabling patients to get more out of their appointments and the overall treatment. Ideally communications should operate progressively, supporting patients as they move from the initial awareness that they may have a certain condition, to actively acknowledging it, then learning to live with it. The latter stage is vital to boost adherence to treatment regimen and enhance overall patient outcomes.

Overcoming challenges

There are many challenges facing the marketing of pharmaceuticals today. However, deeper engagement rooted in custom-built CRM can help navigate many of them.

Direct alignment of patient and physician communications is complex from a data perspective, but with care and attention it can usually be achieved. Bespoke CRM programs can incorporate specific opt-in language to overcome many of the barriers surrounding sensitive data. This ensures that patients who are happy to share their data can access the wider support that is on offer should they need it.

Achieving buy-in from physicians and patients is not easy – nor should it be. Pharmaceutical organizations need to earn trust and loyalty over time. Striving for better, deeper engagement is a critical factor. An effective way to realize this in the short- to medium-term is through the empowerment of patients and physicians, arming them with knowledge and information so they can make informed choices. In the longer term, improved patient outcomes will speak for themselves.


Harte Hanks handles CRM programs for leading global pharmaceutical companies. Patient data is handled sensitively and an integrated approach ensures improved patient support and outcomes. Natalia Gallur has more than ten years’ experience in the sector.


Smarter Demand Gen Awakens

Convergence of Tech and People Will Amplify Demand Generation in 2016

UnknownThe B2B demand-marketing ecosystem continues to evolve at a rapid pace. It’s driven by emerging technologies, tactics and buyer behaviors, alongside other well-established factors that continue to shape the discipline.

Industry influencers and analysts such as SiriusDecisions and Forrester identified a raft of demand generation trends and requirements in 2015. These range from better use of analytics as a foundation for demand planning to buyer journey alignment and operationalizing personas.

The notion of operationalizing personas involves integrating persona intelligence into demand generation efforts. At a fundamental level, it involves dynamic delivery of persona-based content, messaging and offers across email, landing pages and websites. It was first mooted by SiriusDecisions in 2014, but began to take hold last year. During 2016 it will occupy a more central role as we enter the next stage of the journey: smarter demand generation.

Why do we need Smarter Demand Generation?

Many B2B organizations find their demand generation efforts are characterized by small pipelines, missed targets and failure to respond to the needs of today’s buyers. It’s not surprising when you consider the seismic shift in buyer behavior over the past few years.

B2B sales and marketing is becoming increasingly complex and far less linear in its nature. There are multiple influencers, decision makers and stakeholders. There are multiple online and offline marketing channels. And there are multiple interactions and conversations taking place.

In this fractured, multifaceted landscape we need to find a path to more effective, joined-up demand generation. We need an approach that embraces the complex realities of the B2B sector today and handles them with ease. Smarter demand generation is the answer.

What does it mean?

A central feature of smarter demand generation is the convergence of people and technology. This is true throughout the process. Human insight and expertise facilitates the creation and operationalization of personas. It also shapes the development and substance of programs that are augmented and delivered via sophisticated technologies. Finally, individuals at the receiving end of smarter demand generation are served with optimized, highly personalized communications. Content is relevant to their current and future professional needs and it is delivered at an opportune time via the most appropriate platform. The upshot is finely tuned buyer engagement and a more robust pipeline.

This might sound a world away from traditional demand generation. And it’s true that it requires a deeply analytical and intelligent approach expertly integrated with technical capabilities. But every journey begins with a single step. Marketers who set their sights on smarter demand generation can quickly realize benefits at a micro level that can later be replicated at a larger scale.

Exploring smarter demand generation with one segment of your target audience can be a good place to start. Integrating data, technology, people and tactics for the first time isn’t easy – but it is more manageable and achievable at a smaller scale. Ring-fence a project that leverages insight to improve targeting, messaging and optimization. Then closely monitor the results to track the impact on the sales pipeline. Spotlighting the effectiveness of smarter demand generation in this way, and sharing it at a Board level, can create an appetite for more. It might help secure investment in the technologies and skills required for a wider rollout.

The B2B sector has strived for precision marketing for decades. With the awakening of smarter demand generation, it is finally within reach.


Alex Gill explores this theme in a B2B Marketing webinar on 27 January: How to align your marketing for smarter demand generation and stronger ROI. Book your seat here.

The Campaign is Dead, Long Live the Campaign


The evolution of the customer journey from vendor-led to the modern, customer-empowered experience has all but killed the idea of a “campaign.” Marketing to today’s consumer is not a short-term affair – it requires a sustained effort that provides the consumer with relevant and useful information at the right time and place. This “long” approach has seemingly ended the usefulness of the traditional campaign, with the thought being that the modern consumer is acutely aware of when they are being marketed to and are turned off by campaigns. While this is partially true – consumers are more aware – the rumors of the campaign’s death are unsubstantiated.

Traditional Campaigns

When we think of the word “campaign” in the traditional sense, we think of short-term, targeted efforts and messaging designed to spur action, like voting for a political candidate or driving consumers to a holiday sale event. In the past, these campaigns were singular efforts, and while not completely disconnected from the brand, existed largely outside of the overall brand message. In essence, the customer journey was brief. Those customers targeted by the campaign were targeted specifically for the campaign, but not necessarily for an ongoing relationship.

It’s All About Semantics

The massive customer journey sea change in the digital age has painted the campaign in a negative light. But the rumors of the campaign’s demise are greatly exaggerated. The campaign is alive and well – if viewed as a tactic rather than a strategy. After all, “campaign” is just a word. Campaigns – no matter what you call them – do have a place in the modern customer journey. But they must be seamlessly integrated into a larger, more macro approach to customer engagement.

The Tactical Approach

To successfully promote your brand and its products or services, simply marketing to consumers is not enough. You must build relationships and build trust. Today’s consumer knows a pitch when they see it and tends to be turned off when approached with a purely sales-driven message, especially as an initial communication. Consumers are, however, receptive to individual campaigns within the larger context of an existing relationship with your brand. Those consumers who already have a level of engagement with your brand – particularly those who have shown increased interest by opting in to your communications – are likely to embrace a campaign for your product or service, or at the very least consider the message.

Consumer engagement communications should never be stagnant – simply promoting the same thing in perpetuity will eventually lead to message fatigue and a loss of interest in your brand. Injecting timely, targeted campaigns into your customer communications can breathe life into your customer engagement and drive revenue for your brand.

Marketing Technology: Where’s My ROI?


The modern customer journey is consumer driven and often fractured. Unlike the linear, vendor-led customer journeys of the past, the buyer is now in full control. With endless options – and a bevvy of information about each product or service readily available for consumers – marketers must devise new ways to attract customers and secure brand awareness and loyalty. A slew of new marketing technology, including CRM, marketing automation and inbound marketing platforms, have risen up to solve the new customer journey riddle. But despite the effectiveness of these platforms, too many B2B companies are reporting negative ROI for marketing technology investments. There are a number of reasons why.

Failure to Launch

The B2B sales cycle is a complex process. Unlike B2C products, there is no such thing as an “impulse purchase.” Buyers typically spend weeks, months and sometimes even years researching and deliberating before deciding on a purchase – particularly where big-ticket items are concerned. Marketing technology can help significantly simplify this process, but it isn’t a magic bullet. Marketing platforms aren’t plug and play; they are a set of interconnected tools for marketers to utilize as part of an overall strategy. Too often, B2B companies purchase marketing technology, but fail to allocate the resources necessary to realize their benefits. Marketing systems are a great delivery system, but engaging and strategic content that guides prospects along the customer journey must be created first. You can buy a car, but if you don’t fill it with gas and get behind the wheel, it isn’t going to move.

Scratching the Surface

Most of the marketing technology platforms available today come equipped with an array of features that justify their cost – intelligent analytics, A/B testing, easy integration, etc. Companies who fail to realize ROI on these products are often utilizing only a fraction of the features available to them. These features can significantly enhance the power of the platform and should be utilized whenever possible.

Stove Piping

With so many different types of technology available, B2B companies often have more than one system for sales and marketing. Failure to integrate these systems – particularly marketing automation platforms and CRM software – creates a confusing environment where systems are not communicating with each other and often duplicating efforts. In order to get the most out of marketing software and a favorable ROI, marketing platforms and CRM software should always be integrated.

Putting the Cart Before the Horse

Too many B2B companies dive head first into marketing technology – purchasing platforms without a full understanding of the system or a plan to implement it. B2B marketers often find themselves tasked with becoming technology experts trying to implement and integrate systems they know little, if anything, about. Additionally, systems are often purchased before a strategy has been developed to utilize them.

Boost Your ROI

To fully realize the benefits of marketing technology platforms, B2B marketers must view these platforms as an important tool, but as only part of the process. Creative campaigns, strategic plans and actual customer conversations are all an integral part of the modern customer journey as well. Before purchasing a new marketing technology platform, B2B companies should perform due diligence on the products they wish to purchase and have a plan in place on how they will be utilized.

And if you need help boosting the ROI of your marketing investment, Harte Hanks has extensive experience integrating marketing technology with marketing strategy. We’re here to help!

Back to the Future: Predictive Analytics


What if you knew what your customers wanted, when they wanted it? With predictive marketing analytics, gazing into the future is entirely possible. While predictive analytics is not a new concept – marketers have often tried to use past performance to predict future behavior – the dawn of the information age has amplified its effectiveness and usability. Predictive analytics allow marketers to focus efforts and maximize their budgets by identifying targets who are ready to buy and by eliminating those who aren’t.

Big Data

 To accurately predict consumer behavior, you need more than focus groups and surveys. The era of Big Data has armed marketers with a deluge of information on consumers – including engagement with marketing automation platforms and “intent” data from across the web. The technology to crunch this data and make sense of it is rapidly evolving, providing marketers with a roadmap to reach the right audience at the right time.

Data in Action

The Big Data era has produced an incredible amount of information about habits, desires and tendencies of consumers. Marketers who follow these digital footprints can optimize their marketing efforts to target individual audience segments and personalize messages to speak directly to potential customers. Predictive analytics can help create incredibly specific buyer personas – marketers no longer need to rely on broad demographic data and guestimates of what a particular buyer prefers. Enhanced buyer personas lay the groundwork for highly personalized messaging for nurture campaigns, which multiple studies show leads to significant increases in conversion and revenue. Predictive analytics also provide the benefit of targeted spending. Knowing what audiences to target and which platforms to target them through significantly increases the impact of marketing budgets.

B2B Adoption

B2B marketers have lagged behind their B2C counterparts in the adoption of marketing technology ­­– predictive analytics included. And while it’s true that personalized data from individual consumers offer a more clear view into purchasing habits and tendencies, plenty of data exists for B2B customers that can be utilized to implement more intelligent marketing tactics. Purchase history, for instance, is a great predictor of current and future behavior. If a customer has recently purchased a software system that won’t need an upgrade for three years, targeting that customer with marketing messages is not only inefficient, but could negatively affect that customers’ perception of your brand. Existing software licenses, log-in frequency, help desk calls and firmographics can also help B2B companies predict the need and desire for their products. Normally this kind of data will predict the type of customers that buy your products. Add social data sources to the mix, and you can predict customers that are ready to buy.


Depending on the level of sophistication and budget resources, B2B marketers can deploy analyst-led solutions or automated “black box” solutions to perform predictive analytics. For larger, more comprehensive data operations, an analyst-led approach is preferred. Computers are wonderful, but a human touch – specifically when there are oddities in the data – can more accurately utilize the information output to design programs and messaging that take into account both the customer and the nuances of the company. However, there are various automated solutions that are more than sufficient for less sophisticated marketing automation programs. Both approaches have their own merit, but one thing is clear: predictive analytics allow businesses to focus on what’s important and discard what’s not, leading to amplified revenue growth – and happy customers.


The 4 Biggest Challenges Facing B2B Tech Marketers Today (Part 4)

Unifying Communication Strategies Across Channels Throughout the Customer Journey


Over the past few weeks, we’ve been exploring the four biggest marketing challenges faced by B2B tech companies.

Whether you’ve been following along or just tuning in now, you can find the first three installments about utilizing all available tools and technologies, leveraging high-quality, real-time data and generating ROI with less budget and fewer resources on our blog.

For the fourth and final challenge, I will discuss the best strategies to unify communications across channels in order to drive the customer journey.

CHALLENGE #4: How do I unify communication strategies across channels to drive customers through the buyer journey?

Your brand is a powerful thing. Not only does it represent the essence and promise of your company, it also embodies the expectations and opinions of your customer as they move through their buying journey. Each touch point with your brand is a chance to enhance – or diminish – a customer’s perception.

That means that each piece of advertising, each call to your contact center and each visit to your landing page should work in tandem to convey a consistent message that represents your brand. Just one negative interaction can damage your customer’s perception. And it’s much more difficult to reverse a negative perception than it is to proactively ensure positive customer interactions from the start of a campaign.

So how can we ensure a single view of customer across their entire journey, with consistent brand touch points and a clear, unified message? Read on:

  1. Start with a clear definition of your brand. First and foremost, you need to clearly define what your brand represents. Your brand platform needs to be articulated and shared with everyone in the company, particularly the external-facing representatives. A marketing program is the creative output built on top of the brand, designed to build awareness and the desire to purchase.
  2. Decide what you are trying to achieve with your marketing efforts. What is your vision of success? What are you trying to do and why are you trying to do it? At this stage, it’s helpful to look at what Harte Hanks Creative Director Alan Kittle calls The Beautiful Intersection. Draw two intersecting circles. In one, write out what you or your client wants to say. In the other, detail what your audience wants to hear. The intersection of this Venn Diagram is your sweet spot – the message that will tell your story while resonating with your audience.
  3. Identify the necessary building blocks and work streams. After you define your end goal and key objective, work backwards to figure out what will get your there. Start with a solid strategist or planner. This individual or team should gather and interpret all available data, and determine how that insight into the customer will enable a connection with the brand. Data intelligence should help form creative briefs and build a campaign message that is highly measurable.
  4. Cut through with a single unifying thought. In a complex, multi-channel, multi-territory campaign, it is essential to have one unifying idea that all marketing efforts tie back to. In fact, the more complex the marketing campaign – the more channels, audiences, periods of time – the simpler the message should be. By looking at the whole picture, you can determine how all the pieces fit together throughout the journey: how an audience reacts to an email, then a phone call a few weeks later and a piece of advertising leading them to a customer landing page a few days after that.
  5. Create an ecosystem of collaboration and information sharing. It is essential that all agencies plug into the brand and work together in a creative, synergistic manner to tell the same story. Branding agencies need to work in tandem with creative teams – the strongest teams collaborate to make a greater sum of their parts.

By following these steps for a new marketing idea, or to increase the effectiveness of an in-progress marketing program, it is possible to unify communications across channels and create that single, unifying thought that weaves through the entire customer journey. Data helps inform and define this thought and to create a cycle of excellence: use data to create something with the best chance of success, then look at what to improve and start the process again.

Staying in Touch With the Zeitgeist


Last week I had lunch with an incredible group of people: an Academy Award-nominated director, a 21-year-old nuclear physicist, and a New York Times columnist. Just another day in the glamorous life of a digital agency executive, right?

Not exactly.

The lunch was just a small part of the amazing parallel universe Google creates once a year called Zeitgeist, which Google describes as “a series of intimate gatherings of top global thinkers and leaders.” And a few lucky agency wonks, apparently!

On one level, Zeitgeist is Google’s version of the TED conference. The topics are eclectic, inspirational, and thought-provoking. This year’s speakers included an astronaut (from space, no less), Kanye West, a North Korean defector, a golf pro, two Nobel Prize winners, a civil rights lawyer, and so on. And, I assume like TED, the hallway discussions were equally if not more interesting than the amazing speeches. I personally chatted with two billionaires, a few Google executives, forward-thinking CEOs, and some great non-profit leaders.

So why does Google put on this lavish event? I’m sure there are many reasons. First, because they can. Google is doing pretty well as a company, so funding a modern-day Bloomsbury Group once a year isn’t going to put much of a dent in their numbers. More importantly, however, I think it reflects the intellectual curiosity of Google’s founders and executives. Remember, this is a company that could have sat back and counted their cash from AdWords but instead has set out to revolutionize everything from cars to diabetes.

And there’s a lesson here for the SEM community. Life is pretty comfortable for the average SEM pro these days. High-paying jobs are easy to come by. (Don’t like your current gig? Don’t worry, someone will no doubt offer you a 30% raise to come across the street to their company.) And whilst SEM continues to change, the industry won’t be going away anytime soon. So if you want to, you can put your head down and do SEM really well and have a great life (for the foreseeable future, at any rate).

Alternatively, you can take the Google path and decide not to rest on your laurels. You can learn Facebook advertising, attribution, mobile acquisition, and audience segmentation. You can experiment with Beacons and Bitcoin. Heck, you can even try to understand branding and out-of-home advertising (call me if you figure this out, because I certainly haven’t).

As an added benefit, expanding your expertise is a good way to maintain that comfy lifestyle you worked so hard to achieve. Some day – maybe even sooner than we think – SEM will decline and possibly disappear entirely. Learning new skills will enable you to effortlessly leave SEM in the dust and move into the next age of digital marketing. Intellectual curiosity aside, there’s strong business strategy behind Google’s forays into video, mobile, shopping, delivery, healthcare, Internet, transportation, and so on: self-preservation.

The tough part about keeping up with the Zeitgeist is that it is fickle and changes quickly and often unpredictably. Whether you’re a multi-billion dollar Internet giant or a really sharp SEM pro, staying on top of the vanguard of online marketing (and really, of the world in general) does more than keep your mind fresh; it is also just a smart business decision.

Now if you’ll excuse me, I believe a Google drone just dropped off my groceries on my doorstep!

Global Patient Support Needs to ‘Think Local’

PharmaPatient support programs play a vital role in facilitating better disease management and treatment optimization. Traditionally pharmaceutical companies launched such initiatives on a local level. However, from a regional perspective, this sometimes resulted in patchy and fragmented support. Today, many pharmaceutical companies are driving centralized programs that benefit from a more sophisticated and strategic approach.

This approach brings many advantages around compliance, visibility of success and cost-effectiveness of implementation and maintenance. Yet centralized programs can be inherently complex and unwieldy. This is compounded by the fact that they often need to be coordinated at a global or area level to maximize infrastructure and management efficiencies.

Walking the line between global/regional efficiency and local effectiveness is no mean feat. Patient support is not a ‘one size fits all’ discipline; activity needs to be expertly tailored and carefully orchestrated.

At Harte Hanks, we believe five critical factors underpin patient support that is successful both at a global and a local level.

  1. Gather and leverage local knowledge

Understanding the nuances and intricacies of healthcare provision in different regions is essential. Ideally, you should have people on the ground who have in-depth knowledge of their local system and keep a finger on the pulse of any changes or developments.

Typical patient paths can vary significantly between countries for the same disease. Take the patient touchpoints and interactions for the U.S. healthcare system versus the UK’s NHS or Spain’s Seguridad Social. Prescription behaviours, drug dispensing and the length of time between specialist visits can be entirely different. There can even be differences in the role of healthcare practitioners during treatment, in terms of nurse interaction levels, nurse-led advice, pharmacist involvement and primary or speciality care.

  1. Create space for consultation and collaboration

Regional offices need to have clear channels of communication with the head office, and regular opportunities to report back on the local healthcare environment. They need to know that their observations are taken into account and actively used to shape the delivery of patient support in their territory.

At a strategic level, this collaborative approach enables program goals and objectives to be adapted to the realities of each country and healthcare system. It also needs to work at a tactical level, with regional teams of medical and regulatory professionals reviewing and approving materials before they are issued to healthcare professionals and patients.

Pharmaceutical companies often lack the time and resources required to give adequate attention to each country of a global patient support program. This is especially true when implementation needs to happen in parallel with a product launch or other internal deadlines. Working with a trusted third party can be a mutually beneficial solution for individual countries and the global program as whole. They can offer expert guidance as well as coordinate materials distribution and facilitate knowledge sharing.

  1. Ensure processes and training are water-tight

It’s vital that staff delivering the program, especially those with direct patient contact, understand indicators of pharmacovigilance events. Processes need to be in place to ensure that any spontaneous or solicited reports of adverse effects are handled appropriately and escalated in the right timeframes.

A centralized model can ensure that training compliance efforts are optimized and that all pharmacovigilance processes are managed in a cohesive way. A balance needs to be struck to ensure that training and reporting procedures meet certain standards, while respecting any elements or formats that vary between countries.

  1. Coordinated multi-channel communications

Using a CRM suite to facilitate patient and healthcare provider communications boosts efficiency and enables better control of patient support programs. For example, Harte Hanks can act as a multichannel one-stop-shop which is managed centrally but enables local offices to customize activity, such as:

  • Secure data management and hosting, in-line with local privacy rules
  • SMS, email and direct mail assets (drawing on print-on-demand and personalization capabilities)
  • Creation, development and hosting of personalized online portals for patients and healthcare providers, with self-tracking tools to support all digital communications
  • Advanced reporting and analytics to measure success and monitor progress

CRM and digital services should be flexible enough to accommodate multilingual communications and adaptations for the individual needs of each country. For instance, a global program will encounter various regulatory frameworks and the requirements of medical, legal and regulatory teams differ between countries.

  1. Continual improvement philosophy

If program goals and objectives are tailored to local regions, it follows that KPIs need to be tailored too. For measurement to be meaningful, successes or failures need to be considered in context. And they need to feed into the development of ongoing goals and objectives geared towards a cycle of continual improvement. To facilitate effective management at a macro level, it’s important to ensure global real-time visibility across the entire programme, from high-level KPIs to more detailed local perspectives.

The cornerstone of any successful patient support program is recognition that patients are people. They have their own lives, families, work and hobbies, as well as living with a disease or illness. They deserve to be listened to and helped to live their life to the fullest.

Treating patients as people within a program that operates on a global scale is complicated., but with an intelligent, carefully coordinated approach that draws on local knowledge, it is possible to achieve this. Communicating with patients at the right time with the right message via the most appropriate channel is half of the story. Ensuring information and interventions are precisely tailored to their real needs completes the circle, both supporting the treatment and enhancing the overall patient experience.

Harte Hanks handles patient support programmes for leading global pharmaceutical companies. Patient data is handled sensitively and an integrated approach ensures improved patient support and outcomes. Natalia Gallur has more than ten years’ experience in the sector. To learn more about the services we offer, take a look at our case studies.

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