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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.

Three Marketing Automation Myths That Need to Die

Marketing_AutomationAutomation is a fairly young, up-and-coming concept in the marketing industry, so it is understandable that there would be misconceptions in the beginning about what it is and what it does. As we start 2016 and “marketing automation” becomes less of a buzzword and more of a mainstream strategy, Harte Hanks wants to set the record straight on the facts about marketing automation. Here are three myths that we want to clear up:

1. Marketing Automation is for Scheduling Email Batch-and-Blasts

This is by far the most common myth, and misuse, of marketing automation. Email is just ONE tactic within automation. Most enterprise marketing automation technology platforms can incorporate landing pages, social media, personalized emails, gated content, videos, pay-per-click ads, and third party apps into your campaigns.

“59 percent of companies do not fully use the technology they have available.”Ascend2 “Marketing Technology Strategy” (August 2015)

The beauty of a marketing automation platform is its ability to respond differently depending on the contact. It can be integrated with your CRM and allow you to personalize all emails and touchpoints in a campaign based on this data. For example, a highly personalized email can be sent to a contact who has visited a certain page of your website, while simultaneously a more generic discovery email can be sent to another contact who you know little about or who has never visited your website.

Marketing automation is also much more “aware” than traditional email marketing. Automation tools are sophisticated enough to not only tell whether a customer clicked on a link in your email, but also which product-specific pages they visited after they clicked, whether they filled out a contact form, and even gather geographical and language information from them based on their IP address. Marketing automation tools can then take that user’s activity data and segment him or her into another flow of automated touchpoints (including additional emails, retargeting ads, high value content, etc.) that are specific to their interests.

2. Marketing Automation Means ‘Set It and Forget It’

While it’s true that marketing automation is great for scheduling emails and other campaign activities in advance, simply “setting and forgetting” is a sure-fire way to make sure your investment goes down the drain.

Many marketing automation tools offer robust functionality out of the box, but most are also cloud-based platforms that have new features added on a regular basis. Keeping a pulse on these updates, and participating in product improvement discussions, is important in making the most of your automation software. In fact, Eloqua will be rolling out a new UX experience this spring.

Another reason you should never “set it and forget it” is that with a healthy marketing automation program, your contact database will be continuously growing. Your customer insight will evolve as the system collects more data from your customers and their activities. And as you learn new things about your customers and their preferences, you can use that information to create more meaningful content in your campaigns.

3. Marketing Automation Stops After the Lead Converts to a Customer

Using marketing automation only for lead generation underestimates the power of the tool. As marketers, we know that the best lead source is always your previous customer. Repeat business and customer referrals will always give you the best ROI for your marketing budget. So why not make the most of that source?

“53 percent of marketers say continued communication and nurturing of their existing customers results in moderate to significant revenue impact.” (DemandMetric, Customer Marketing: Improving Customer Satisfaction & Revenue Impact, October 2014)

Luckily, marketing automation is not only a powerful lead generation tool, but it also gives you a platform to keep the conversation going with your new customer(s). When you properly sync your CRM to your automation tool, you can harness the power of segmenting by moving converted customers away from prospects into their own nurturing campaigns. These customer-specific nurturing campaigns open a two-way communication channel allowing your customer to become more engaged with your brand and to fully utilize your product or service.

For example, a customer-specific nurturing campaign can share content on best practices using your product (or service) via weekly newsletters, retargeted ads, and videos. Likewise, you can use those touchpoints to upsell products or services that complement what they’ve already bought. Automated campaigns can also be used to promote customer-only events via email invitations and trigger follow up phone calls from telemarketing or sales representatives.

You will never see the value in your marketing automation strategy if you don’t have a clear understanding of what it can accomplish. Marketing automation is more than the latest corporate buzzword. It’s a powerful marketing strategy and tool that allows companies to nurture prospects with highly personalized, useful content. It helps convert prospects into customers, and customers into brand ambassadors.

Harte Hanks is a full-service marketing agency that can support all aspects of your marketing automation program with minimal ramp up and faster go to market. Contact us for a free audit of your marketing automation programs at 1-844-233-9281.

How to Optimize Spend with Fractional Attribution

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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.

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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.

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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.

 

The Hottest Three Letter Acronym for 2016: D-M-P

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Marketers are overwhelmed with tools and channels, and most of these – OMG! – have a three-letter acronym (TLA) that we use to theoretically make it easier for us to discuss them (and of course, to make us feel like we are in the know!). DSP, SEM, PMD, PLA, SEO, FPD, LOL, CRM, FAN, GDN . . . the list goes on and on. BTW, “LOL” on the previous list refers to “laugh out loud,” ICYM!

IMO, the hot TLA for 2016 will be DMP – data management platform. FYI, a DMP is a data warehouse that “can be used to house and manage any form of information, but for marketers, they’re most often used to manage cookie IDs and to generate audience segments, which are subsequently used to target specific users with online ads.”

For example, let’s say that you have a CRM full of FPD (first-party data) about your customers. You can upload this data to a DMP, enhance the data with third-party behavioral targeting, and then generate audience profiles that you can use to create more targeted and effective ads across your social, search, and display channels. Compared to your competitors without a DMP, your marketing campaigns should resonate better with consumers. Information asymmetry leads to better ROI, so marketers who don’t have a DMP have more to fear than just the FOMO – they may actually be at a significant disadvantage.

All of this assumes, of course, that marketers who invest in a DMP will install it correctly and use it correctly. As anyone who has seen an amazing pitch of marketing technology knows, the product never seems to work quite as well as it does in the canned demo! Setting up a DMP properly is fraught with potential pitfalls, from not properly importing data to incorrect data interpretation. So simply having a DMP is not enough – having the right pilots of data collection and analysis is vital. Given that this is a corporate blog, now would be a good time for me to promote Harte Hanks’ DMP/service solution, which we call Total Customer Discovery.

The future of marketing is always murky, so the centrality of the DMP is still TBD. That said, theoretically DMPs make a lot of sense, and it seems likely that it will be an important component of all online marketing strategies going forward. TTYL!

Harte Hanks Announces Data Refinery to Harness Customer Data and Drive Marketing Results

Data Refinery ProcessMarketers are increasingly looking for innovative ways to get to know their customers better, and to get the most out of the campaigns they create every day. The best way to learn more about your customers is by leveraging data. This isn’t as simple as it sounds. With a plethora of channels at your customers’ disposal, both online and offline, and the growing number of devices that people use, it is difficult to harness all of that data – especially when you’re mining it from multiple sources. Utilizing big data also requires the complexities of hiring a staff to manage data, ensuring best-in-class quality and governance procedures and working with constrained budgets across siloed departments. This is no easy feat.

How do we overcome these challenges together? The answer lies in gathering and storing the most current data on your customers through a data refinery. Data refinery is a scalable platform that allows for on-demand access to compiled customer views that can be accessed by all departments within your organization. The compiled views should be nimble, customizable and rich with proprietary and third-party data sources so they effectively serve the ever-changing marketing demands placed on the various teams that need access, and as a result, empower marketers to know more and communicate better to their customers.

So how does it work?
At the heart of a good data refinery platform is the aggregation of large amounts of various data types from multiple sources and channels, both traditional and digital. A data refinery platform starts with an ideal customer profile that defines data attributes needed to deliver results. This ideal customer profile serves as your “map,” guiding data profiling and sourcing to bring together and enhance owned data with third-party data. The data refinery then cleanses, validates and standardizes the customer profile for output to any downstream marketing or sales application.

Today we are excited to announce that Harte Hanks is launching its very own Data RefinerySM solution. With our solution, access to pre-vetted data sources by vertical and marketing objective are utilized – think of this as an app store for data – reducing the time to value. Selecting data based on reliability and performance metrics optimizes data usage and spending, ensuring campaigns don’t become stagnant. To learn more about Harte Hanks’ Data Refinery click here.

A brand’s success will continue to be dependent on technology, innovation and the ability to connect with the customer in a highly relevant way. A data refinery platform is needed to bring data together and make it foundational to all your marketing and sales efforts.

Next week we’ll review what data sources are available and how best to manage them using the latest open source technologies. In the meantime, start thinking about what you could do if all your data could be harnessed, treated as a single source of the truth and accessed by anyone on demand. The possibilities are almost endless, aren’t they?

Delivering data from all different sources and augmenting it to form purpose-built customer profiles allow you to understand your customers. This insight is powerful and allows you to acquire new customers, reduce churn within your existing customer base, increase repeat purchases and increase customer satisfaction.

A Data Refinery Platform Helps You:

  1. Better understand existing customer base
  2. Create models and segmentation to find better prospects at scale
  3. Understand existing customer behavior, avoid attrition and encourage growth

Back to the Future: Predictive Analytics

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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.

Implementation

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 2)

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A couple of weeks ago, I kicked off a blog series about the four biggest challenges faced by B2B tech companies. If you missed the first installment about creating an ecosystem that makes use of all available tools and technologies, you can read about it here.

Today’s challenge is around generating high-quality, real-time data and using it to drive sales and ROI.

CHALLENGE #2: How do I make my data high-quality, real-time and usable to drive sales?

Marketers today are inundated with data. Just when you’ve successfully integrated Instagram into your marketing activities, a new channel is added to the mix, be it a new social network, a mobile app or even virtual reality and interactive holograms. With the army of channels comes a network of devices. From our fitness trackers to our appliances to our cars, almost everything is getting connected to the Internet. With this propagation of channels and devices, we have more data, more sources and more insights than ever before. The challenge now is figuring out whether that data is quality and usable.

How to solve it

At Harte Hanks, we are all about the data. Data analysis and analytics is in our DNA, and we’ve spent the better part of the last decade figuring out how to make data work for us. Here’s what we’ve learned about increasing data quality to effectively run your business:

Obtain Quality Data (Data Remediation)

The first step to driving sales through data insights is to make sure you have quality data. My colleague Seth Romanow recently outlined his proprietary 4-Box model for determining whether data will meet marketing, analytics or campaign requirements. In a nutshell, as a marketer, you must:

Match data requirements with your ideal customer profile and marketing objectives, ensuring that data is “fit for purpose.”

Perform a data audit that implements the 4-Box methodology to segment your data based on completeness against your previously defined ideal profile and engagement.

Identify the gaps and develop a remediation plan that defines clear paths to cleaning, updating, appending and enriching your data.

Execute the remediation by fixing data sources and process issues and incorporating new digital and social data sources to add depth to the record and increase the ability to segment and target more effectively.

Use Quality Data to Drive Sales (Predictive Analytics): Once you have quality data at your disposal, things start to get really interesting. Predictive analytics is a great way to drive bottom line results as it can reduce the need for expensive third-party data or telemarketing support, particularly for acquisition programs.

What It Is – Predictive analytics helps identify when prospects are ready for an up-sell or a cross-sell, but that’s only half of the story. They also enable marketers to focus their efforts and budgets on prospects with a high response rate, and they can tell companies the prospects with which they should not waste their time. For example, targeting an individual who just invested in a product that met their needs and won’t need an upgrade for three years is not a worthy recipient of marketing dollars – not only could it waste time and budget, it could also harm brand equity.

How To Do It – There are a couple of different ways to implement predictive analytics: through an analyst or through a black-box solution. If you suspect your data has oddities or you need precise, robust outcomes, the analyst-led, human approach is best. If budget is a consideration and you are looking for a quick, scalable and repeatable solution, black-box algorithms may be the way to go. With either option, predictive analysts pinpoint firms that have exhibited a desired behavior, extrapolate the common factors about those businesses, and then analyze the behavior and features of the business to help identify others with a similar profile to be prioritized for marketing activity.

With data remediation and predictive analytics, marketers can improve their data quality and use it to more effectively drive targeted sales. So, what’s coming up next? The final two pain points delve deeper into ROI and delivering consistent communications throughout the customer journey.

  • How do I maximize ROI with fewer resources and less investment?
  • How do I unify communication strategies across channels to drive customers through the buyer journey?

 

Taking Your Customers from Anonymous to Known: Introducing Total Customer Discovery

A Deeper Dive into the Solution

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Today, we are excited to announce our newest solution to enable smarter customer interactions: Total Customer Discovery. You can learn more about the details through our press release, video and digital guide. In this blog post, I’m going to break down some of the technology components that went into creating it.

In a nutshell, Total Customer Discovery provides a holistic, 360-degree profile of customers, merging data from online and offline channels and across devices. This single customer view encompasses data across demographics (contact data, social profiles); psychographics (interests), historical (purchase and promotion history) and influencing power (networks, connections). With this richer customer view, marketers can deliver enhanced and personalized customer experiences, leading to increased acquisition, retention and, ultimately, ROI.

So without further ado, here are the different components of the Total Customer Discovery Solution and what they help address:

Solution Component: Cross Screen Identification

With cross-screen identification, each customer has a persistent, unique ID that carries with them, helping marketers track associated devices with that customer even when customers delete their browsing history (and their cookies). With Total Customer Discovery, we can identify and track customers across various devices (mobile phones, tablets, computers, laptops and so on), learning their behaviors, adding to their customer profiles and offering a seamless brand experiences across touch points that takes into consideration their past purchase history and preferences.

Solution Component: Cross Journey Mapping

To solve the problem of internal silos and overwhelming amounts of data, the cross journey mapping function captures customer’s digital behavior and stores meaningful attributes, such as click, searches, interests, preference, etc. to produce richer, more multi-dimensional customer profiles. These attributes can then be linked with other data sources within an organization such as a Customer Relationship Management (CRM) database. Total Customer Discovery identifies customer interactions across multiple devices and channels, so that we can track a customer throughout their entire journey, from smartphone, to tablet, to computer, to in-store.

Solution Component: Data Onboarding

A single view of customers provides a comprehensive view of the purchase journey. Integrating both online and offline data helps round out the single view of customer for a comprehensive picture of customer behavior for better retargeting and personalization. With data onboarding, online and offline data are merged and customer files are created using email or physical address lists that are matched with a database of advertiser tracking parameters. Particularly for brick-and-mortar stores, integrating online and offline data sources is crucial for delivering relevant content across channels based on the customer identification, from digital interactions on their smartphone to offline purchases at a retail store.

Solution Component: Social Linkage

Personalized, relevant content is the key to driving ROI in today’s world of real-time “micro-moments.” With social linkage, customers’ social interactions and behaviors are tracked across sites to enable deeper customer segmentation. Social linkage takes data from over 150 social sites, including Facebook, LinkedIn, Pinterest, Twitter and Google+, and gives marketers insightful social profile data to inform their social investment decisions and make their digital marketing efforts more effective.

We’d love to tell you more about how Total Customer Discovery takes customers from anonymous to known. For more information, you can visit hartehanks.com/TCD or email TCD@hartehanks.com.

5 Ways to Improve Your Contact Center Through Digital Marketing

Use Your Contact Us Page and Digital Marketing to Improve Customer Satisfaction

five ways

We live in an age where the customer – not the company – dictates your brand. In the old days, you could put out a massive advertising campaign with the moniker “Fly the Friendly Skies” and convince consumers that your airline was the nicest around. Today, an angry customer can create a video called “United breaks guitars,” and millions of consumers will share it in second.

Every interaction with a customer is an opportunity to create a brand advocate or a raving-mad critic. Many companies don’t realize that there are relatively painless ways to use digital marketing to increase the chances that you wow every customer who interacts with you. Here are five ways digital marketing can help:

  1. Help people find your contact info online via search engine optimization. Some companies purposely hide their contact us info deep into their website, in the hopes that customers will end up getting their questions answered without talking to an actual human. While this saves money in the short term by reducing the size of your contact center, the long-term negative hit to your reputation when customers complain to their friends and through social media will cost you dearly. Using search engine optimization (SEO), you can edit your website content and code to increase the visibility of your Contact Us page, making it easier for clients to get their questions answered promptly.
  2. Retarget visitors with a customer satisfaction survey. Retargeting is a form of advertising that serves banner ads to customers who have visited a particular page or completed a particular set of actions on your Web site. While most people use retargeting to convert a customer from a browser to purchaser, contact centers can use this technique to increase their customer satisfaction (CSAT) survey results. Simply retarget everyone who visited the Contact Us page of your website with a banner ad inviting them to give you feedback about their experience with your contact center, and your company overall.
  3. Use analytics to reverse-engineer why customers contact you. When a customer visits your site, your online analytics tool (usually either Google Analytics or Omniture) follows their every move. Which pages did they visit? In what order? How long did they stay on a page? How frequently do they visit the site? All of this information can be mined to figure out how your customer ended up at your Contact Us page. Did the customer look at your “Frequently Asked Questions” (FAQ) page and not find what they wanted? Use this information combined with your call log to create additional FAQs to resolve future customers’ needs. Do numerous customers go to the same product page right before calling customer support? Check the URL of that page; perhaps it is broken.
  4. Test different landing pages to optimize business objectives. The way you design your Contact Us page will influence the way customers interact with it. For example, a page with a giant toll-free number in the middle of it – and not much else – will inevitably lead to lots of calls to your contact center, but a page with links to your FAQs, a live chat option, and a less prominent phone number will increase site interaction at the expense of your contact center. The right balance of contact center versus web-based customer support will vary for every company. The good news is that there are plenty of tools available to help you test different Contact Us page experiences to figure out what look and feel drives the best business success for your business. Tools like Optimizely and Unbounce as well as “landing page optimization” (LPO) experts can help you set up the right tests.
  5. Encourage mobile app installs for customer loyalty. Many companies use their mobile apps to drive sales to their business and also respond to customer questions and concerns. When a customer visits your Contact Us page, why not encourage them to download your app with a prominent link? This is even more relevant if the customer is visiting your mobile website.

Digital marketing is usually known as a way to efficiently drive new customer acquisition and increase existing customer purchases. Using it to enhance your customer satisfaction is just one more great reason to invest in digital marketing.

Who Wants to Waste Time or Money on Data? Not me.

In my last post, I discussed how building an ideal customer profile is the first step to successful inference marketing—using data from a variety of sources to learn about the customer without requiring him or her to fill out a form. In this post, I’ll go into a little more depth about why you should take the time to build an ideal customer profile and how to get it done.

Why Build an Ideal Customer Profile

By ideal customer profile, I’m not referring to creating a picture of your best customer. I’m talking about determining what customer data points are most important to collect in order to achieve your marketing and business goals. Instead of trying to perfectly complete every contact or account record, data should be fit for its intended purpose, such as more effectively segmenting your email lists or better customizing web, email or other content.  . Deciding up front what specific information you need about your customers and prospects allows you to prioritize your data acquisition activities, only buying or remediating the data that you really need. You should strive for a balance between what’s needed to improve marketing and sales effectiveness and the costs of acquiring, using, and maintaining additional data sources.

Who wants to waste time or money on data? Not me (and probably not you). Take the time to build an ideal profile so you don’t. 

How to Build an Ideal Customer Profile

Overall, it’s pretty simple:

  1. Audit what you have. Come up with an inventory of the different data points you currently collect for each profile.
  2. Determine if are there other data points that would allow you to create better segmentations for marketing and sales.
  3. Adjust for a region, country or segment. It’s no secret that data availability, depth and quality vary by geography. Additionally, data for larger companies is generally more complete and up-to-date than data for small and medium businesses.  Please be mindful of data usage regulations.
  4. Add the data points from steps one and two together to complete your ideal customer profile.

A common set of desirable data includes (but remember to keep in mind your specific objectives):Ideal Profile Visualization

  • Core Contact and Account Attributes: standardcontact profile (name, email, address, title, company) and account firmographics (company revenue, industry, location, number of employees) plus relevant account level transactional data
  • Extended Attributes: supplemental orderived data, such as installed base, wallet size, role, cross-channel shopping, white space, propensity or other modeled scores
  • Social Attributes: includes data on sentiment, interest and intent derived from social interactions or social networks; can be at the contact or account level
  • Behavioral Attributes: engagement activities that may include sites visited, content consumed, campaign response, events attended, etc. Much of this data will come from your own web analytics and response tracking tools, but there are external providers as well.

Sources for web and social data are becoming more available and easier to access, allowing you to build out your profiles. Well known providers of digital and social data include LeadspaceDataSiftWorkDigital, FullContact, Profound Networks, and Gnip. You can also obtain information on content consumption through companies such as Madison Logic. The company tracks and reports content use across a network of over 450 B2B publications. This type of information can be helpful at the account level and, on a permissioned basis, contact level to understand what topic or solution areas your prospects find interesting.

Need Some Proof?

One of our clients recently used this approach as part of a data remediation program. The result? They achieved an ROI of well over 500 times their investment in data. While results can vary, I am confident that this strategy works to deliver a better marketing ROI.

What Next?

Now that you have a template for your ideal customer profile, you need to collect the data to complete it. For suggestions on tactics for updating, appending and enriching your records, check out this white paper.

Solving the mystery: How does your clean data get so dirty?

By: Traci Varnum

Data Quality Stats on Bad DataBy now, you are probably aware that a lack of accurate, clean data can be a huge problem for us marketers. According to an infographic from Trillium Software, 50% of all companies overestimate the quality of their data. Even more troubling, 50% of companies have absolutely no plan for managing their data problem.

So where the heck does all this bad data come from?

A recent article from Direct Marketing News explains that “dirty data” can rear its ugly head in a number of different ways.  Some common examples include:

  • Consumers failing to update their information
  • Brands failing to update their database as prospect/consumer information changes
  • A lack of communication/sharing between internal departments regarding the data necessary to create consistent or complete profiles
  • Third parties providing data without first performing a proper quality check

Given that the average person will change both jobs and living situations approximately 11 times over the course of their life, clean data can get dirty FAST.

With the large amount of data coming from new, quickly evolving sources like mobile and social media, it is now more important than ever to keep on top of your data. While social networks can provide a plethora of valuable data points, this social information can quickly become outdated. For instance, every single time a user creates a new social profile or updates an existing one, this personal information is stored in a secure database, offering up new information to marketers.

Fortunately, despite all of these extra records to worry about, there are ways to keep your database sparkly clean. Okay, maybe there will be just a tiny bit of dust or an occasional smudge–there’s no such thing as a perfect database. But with the right approach, you can substantially improve your data, and as a result, your overall bottom line.

To learn how small data enhancements can lead to big ROI, download our latest white paper: “Good Data: A Marketer’s Best Weapon.”

7 Reasons to Care About Clean Data

By: Sigrid Seymour

Using clean dataIs your data “clean”? Or does it contain inaccuracies, gaps, duplicate records or old information? Does clean data even matter?

You bet.

From overall corporate strategy to marketing efforts to performance measurement, clean data positions you to make the best possible decisions for all aspects of your business.

Here are seven reasons I have encountered over the past two decades as to why you should be concerned about improving the health of your customer data.

Improve your ability to perform advanced analytics.

A clean customer database that provides a complete view of all your customers’ engagements and transactions paves the way for optimized advanced analytics.  Whether you want to define personas, understand lifetime value, design upsell and cross-sell strategies, or develop sophisticated models, having clean and consolidated data will enable better analytics, improve the performance of your marketing campaigns and maximize your marketing investment.

Produce more effective direct marketing through better customer experience.

Accurate customer data, such as contact information and response data, allows you to better segment your customers based on their individual buying preferences and behaviors, leading to improved campaign targeting and personalized, relevant marketing content and offers—which all lead to a better customer experience and improved marketing results.

Set the stage for integration of online and social data.

A clear, detailed picture of your customer can make a world of difference when it comes to your marketing success. To develop this comprehensive view of your customer, you need to integrate traditional data with data from online sources. This process begins with a customer’s name, postal address or other offline data point and then appends new digital data about the customer, such as a Facebook or Twitter identity or online purchasing behavior. This online data enrichment is more likely to be successful when you begin with clean, accurate offline data. The result is a rich portrait of your customer that empowers high-performance targeting, messaging and experience strategies.

Improve efficiency and save money.

If you’re working with “dirty” data, you’re sending mail to inaccurate addresses, emailing obsolete email addresses and calling disconnected or wrong numbers. Clean data eliminate these wasteful efforts and make sure that your marketing communications actually get delivered, in a timely fashion, saving you valuable marketing dollars.

Properly inform strategic decisions.

“The impact of higher-quality data is most immediately evident in the quality and speed of business decisions. Organizations reporting data accuracy of over 90% were able to put reliable information in the hands of their executives fast enough to meet demand 80% of the time. Companies with lower than 70% data accuracy only succeeded at meeting this demand window half of the time.”

~Aberdeen Group

You need an accurate attribution of customers to stores, branches or regions in order to make solid strategic decisions for your business, such as those surrounding store level merchandizing, real estate assessment or regional segmentation. For example, fully understanding who your customers are and their saturation level at a location or within a geography will help you to decide which product categories to stock, which services best resonate in a particular state, or how seasonal factors will impact your business.

Allow you to accurately measure performance.

Most companies find that transactions alone cannot describe the true health of the business—you must also consider key performance indicators like customer growth, migration and attrition. These KPIs will be more accurate and more useful when based on complete, up-to-date data without duplicate records.

Mitigate risk and deliver on commitment to shareholders.

When there is a data breach, recall or other critical information to relay, clean data help you to mitigate risk by quickly communicating with your customers through accurate contact information.

So, now that we know why clean data is so important, the next step is to learn about cleaning up your dirty data. Look out for our next post on data enrichment FAQs. 

10 Tips to Avoid Costly B2B Data Purchase Mistakes

Analyzing B2B DataPurchasing B2B data isn’t rocket science. There are common areas that can be learned quickly, and vendors can help with less common queries. However, once you expand your requirements beyond your country, you might be surprised at how complex buying can become. These 10 commonly overlooked areas require careful consideration, or your data purchase decisions could cause the failure of an otherwise fantastic campaign.

1)      Turnaround times vary, greatly!

In Western markets, 24 – 48 hours turnaround time for counts is the norm.  Other markets respond slower. Far Eastern vendors, for example, can take 5-10 days to return a count. Work this into your timelines. 

2)      Adhere to local data legislation.

Be careful to adhere to local law and best practice, and ensure your data suppliers follow regulations too.  In Germany, double opt-in rules mean there is no such thing as a cold email. Conversely, the UK operates opt-out for B2B, so you can have a broader reach with email campaigns.  This is not just important from a data perspective – there is no point creating a fantastic campaign if it cannot be deployed.

3)      No database is perfect.

Some databases are fresher than others, but none are 100% accurate.  Business data decays rapidly (Watch this video to see how rapidly!), so you need to know local benchmarks and the vendors’ guarantees. That way you can expect certain inaccuracies, order over-supply when necessary and identify if the quality of the data you purchased is genuinely unsatisfactory.

4)      Language.

Can non-English data be handled accordingly?  Can your systems cope with special characters found within many European languages such as German or Spanish?  What about double byte characters from Russia and the Far East?

5)      Variation of variables – do they meet your needs?

Not all vendors collect, manage and store data consistently. Variables like employee size and turnover can be banded or actual, and the latter could be local currency or US Dollars.  Check how vendors report these variables early in the planning process.

6)      NACE vs. SIC vs. NAICS – ensure consistency of selection.  

There are different ways an organization’s industry can be categorized. In Europe, a NACE code is used whereas in the USA, US SIC codes or NAICS is used.  While there are similarities between all systems, there are also subtle differences. Aim for consistent use of industry codes, especially when using multiple vendors.

7)      Put data volumes into context. 

If you listen to vendors’ claims, then every database is the biggest and best on the market. But don’t worry, a bit of common sense will ensure you obtain genuine datasets. If the vendor claims they have 40m businesses in the USA, then it’s probably not true. Why? Research shows there are only 20m businesses, so the 40m figure is more likely to be contact volume, not sites.

8)      Lack of data quality standards.  

In the UK, we have an established association, The DMA, who produce guidelines and member Codes of Practice on acceptable data quality benchmarks. However, in some developed markets – including North America – there are no comparable benchmarks and vendors set their own standards. Don’t make any assumptions; ask suppliers what their guarantees are and why. Ask probing questions about their data collection methods and quality processes.

9)      Know the cost and usage terms.

How do you want to be billed, €, £ or $? If it’s different to the vendor currency, ensure you work in the correct exchange rates and include caveats allowing for fluctuations. How do you access the data? Annual subscription licences vs. per record purchase? Must data be downloaded from a portal or can it be transferred by SFTP?

10)   Data formats vary.

With 180 + countries globally and many of them having individual address standards, there are different ways to represent an address.  Communicate to the vendor exactly what you need for the campaign. Taking international phone numbers as an example, should country code be a separate field? Does the number need leading zeroes?

Buying data can be complex, particularly for international campaigns in markets where you are unfamiliar. The 10 areas above are the tip of the iceberg. Don’t hesitate to contact us if you have any questions about the above, or need guidance on how to apply these tips to your marketing programs.

Go Where No Marketer Has Gone Before with CRM

By Niranjan Oak, Senior Consultant II, Nuedesic

Remember the classic Star Trek TV series? Captain Kirk’s mission was to explore new worlds and civilizations by going into deep space where no one had gone before. Imagine if Starship Enterprise and Captain Kirk were in the business of marketing. What would their “mission statement” look like? Maybe something like: “Growth: The final frontier! These are the voyages of today’s marketers. The five year mission to explore new markets, to seek out new customers, and to boldly go where no marketer has gone before.”

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Source: Trillium Software

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