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Broken Data Smart Data Collective
Broken Data Smart Data Collective
Broken Data Smart Data Collective
Broken Data Smart Data Collective
Broken Data Smart Data Collective
Broken Data Smart Data Collective
Broken Data Smart Data Collective
Broken Data Smart Data Collective
Broken Data Smart Data Collective
Broken Data Smart Data Collective
Broken Data Smart Data Collective
Broken Data Smart Data Collective
Broken Data Smart Data Collective
Broken Data Smart Data Collective
Broken Data Smart Data Collective
Broken Data Smart Data Collective
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Broken Data Smart Data Collective

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EBook On Dealing With Big Data with Esteban Kolsky, Brent Leary, Tyson Hartman and myself

EBook On Dealing With Big Data with Esteban Kolsky, Brent Leary, Tyson Hartman and myself

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  • 1. The Broken Data Promise:How CRM Failed, and Why Businesses Need It More Than EverBrought to you bySponsored by © 2011, Social Media Today, LLC
  • 2. FOREWORD 1 2 3 4 CONCLUSIONSThe Broken Data Promise:How CRM Failed, and Why Businesses Need It More Than Ever3 Foreword4 Customer 360° Esteban Kolsky6 What Customers Want Brent Leary9 The Rise of Analytical CRM Mark Tamis12 Big Data, Big Problems Tyson Hartman14 Conclusions15 Author Bios16 About Us
  • 3. FOREWORD 1 2 3 4 CONCLUSIONSForewordDuring the 1990s and early 2000s, the so-called golden years We will take a two-pronged approach. First, we’ll exploreof CRM deployment, CRM vendors made a promise to their what is necessary to achieve a holistic view of our customers,clients: If organizations bought and implemented complete what data must be collected, and how that data can beCRM suites; they’d be rewarded with 360º portraits of their used. We’ll also examine the benefits of this approach, andcustomers. These portraits would be generated by the large look at case studies to better understand why organizationsquantity of transactional and operational data that CRM must meet the data challenge.solutions produce. Vendors claimed that by gathering alldata about all interactions between the organization and its In the second part, we’ll explain how to monitor and storecustomers, companies could then leverage analytical tools the data needed to create useful customer profiles, andwithin the suite to build deep, meaningful relationships leverage those profiles in different functions. Finally, we’llwith customers. present a case study of one organization that successfully used a CRM system to profile its customers.This became the 360º view of the customer promise. It wasnever kept. It’s not because we didn’t try. We kept detailedrecords of all interactions, all transactions, everything thecustomer did and said. We gathered more information oncustomers during the last 10 years than we had since theinvention of data collection.Despite all this data, we still can’t begin to understand whatour customers truly want or need. Worse, we can’t use thedata we collect to improve our customer relationships—oneof the core goals behind the CRM data promise.How is that possible? How could we fail so completely inthe single most important promise made by the most criticalpiece of front office software to be released in our lifetimes?This eBook will explore the answer to those questions. 334
  • 4. FOREWORD 1 2 3 4 CONCLUSIONS1 Customer 360° Esteban Kolsky It may seem obvious, but still needs to be said: This is accurate predictions about behavior within our segments. all about data. If you want to create a complete profile Nevertheless, all this operational and transactional data is of any customer segment, you need to collect, store and still being stored today, and is still being used as a partial analyze lots of data. The data we need falls into four predictor of future behavior. main categories: Attitudinal – This is the missing behavioral link. Demographic – this is what we traditionally think of when Organizations tend to collect and store behavioral data we talk about customer data. The core data points are name, from their perspective: What is the customer doing and address, and phone number, but we also retain gender, age when? But these questions don’t capture the reasons group, education status, income, race, and similar data why customers do what they do, because organizations that will help us classify customers in different segments. don’t see the world from the customer’s perspective. One such group might be males aged 18 to 24 years living The point of gathering attitudinal data is to close this in New York state. Initially we believed that members of gap by asking customers why they would buy a product. these segments would all behave in the same way, but we What circumstances determine the attitude that drives found that isn’t always the case. Nevertheless, gathering the behavior? We collect this type of data via surveys basic demographic data still helps us identify customers for and other feedback events, which normally include different purposes. satisfaction questions. Behavioral – The promise of CRM systems was that if Sentimental – Sentimental data refers to the emotions and we retained and analyzed sufficient transactional and feelings that a customer has towards the organization, its operational data about customers, we could determine products, and the relationship as a whole. It has traditionally how they behaved and make predictions about their future been materialized in metrics like satisfaction, loyalty and behavior. If certain males aged 18 to 24 living in New York advocacy. Sentimental data can only be captured by direct state perform a specific action at a specific time, we can feedback, and can never be inferred from other metrics. infer that the rest of the group will behave in a similar way. This was one of the biggest pitfalls of the original CRM Thus, when a 19-year-old male New Yorker interacts with promise: The original systems tried to guess sentiment by us, we can offer him a particular product with a certain analyzing behaviors, yielding poor or erroneous data. degree of confidence. Later, of course, we discovered that Continued on next page we were missing other core data points needed to make 344
  • 5. FOREWORD 1 2 3 4 CONCLUSIONSCustomer 360° (cont’d)In short, a complete customer portrait would tell theorganization who the customers are (demographics), whatthey do (behavioral), what they want (attitudinal), andwhy they want it (sentimental). Such profiles allow anorganization to tailor solutions, products, services, andinteractions to what its customers are looking for. 354
  • 6. FOREWORD 1 2 3 4 CONCLUSIONS2 What Customers Want Brent Leary About a decade ago, Mel Gibson starred as marketing their concerns, likes and dislikes freely via social channels. executive Nick Marshall in a movie called What Women Want. We can pick up extremely useful insights by knowing where Nick thinks he can use his charm, powers of persuasion, and to listen, what to listen to (and for), and, maybe most especially his perception of feminine desires in order to important, how to listen. land a major sportswear retailer as a client for his firm. But he never tries to understand what’s important to women The tools for listening and engaging are already plentiful, until he gets passed over for a major promotion. and will become easier and easier to use as time goes by. But we still need a strategy for collecting and analyzing Shocked, Nick immerses himself in trying to get inside what we hear, so that we can translate it into solutions the minds of his customers—not because he really cares that solve the challenges our customers and prospects face. what women want, but to prove that he shouldn’t have While listening to our customers and analyzing what they been ignored. say, we are also creating meaningful interactions with them that lead ultimately to stronger relationships. After adjusting to his new powers, Nick starts exploiting what he hears for personal gain. He eventually realizes The more active our customers are on Facebook, Twitter that misusing his new power is an overall negative, and other social networks, the more data they create. so he starts listening in order to really understand women, This presents an opportunity to better understand and and not just to validate his preconceived notions. Having engage our customers. It also challenges us to integrate changed his own thought processes, he finally learns how this information with transaction data, activity data and to care about women’s needs and concerns, which helps other information that adds up to a layered customer him connect with the audience that he originally took portrait. While the challenges are not trivial, the payoff for granted. can be substantial. While this is only a movie—and I sincerely hope there will Lisa Larson, director of customer care at online pharmacy never come a time where people can hear what’s going Drugstore.com, recently shared her experiences integrating on in my head—we can learn valuable lessons from Nick’s social channels in customer service. Here’s what Lisa had transformation. First, it’s more important than ever to to say about the importance of listening to and analyzing understand what our customers are thinking. Fortunately the social footprints that customers leave. we don’t need Nick’s extrasensory ability. Customers share Continued on next page 364
  • 7. FOREWORD 1 2 3 4 CONCLUSIONSWhat Customers Want (cont’d) People who aren’t looking at this are missing a key part of These are the kind of results that might make it easier their business. You learn the most from just listening to to understand the benefits of leveraging social tools to your customers. Years ago, you would have paid amazing listen, analyze, and engage with customers. But don’t amounts of money to get this kind of information. Now forget Nick—you need to be genuinely interested in it’s free and right there for all of us, we just have to go understanding your customers, and not just interested in listen and find it. It’s amazing, the difference. These what they can do for you. are really honest conversations that you can listen to and learn from, and possibly join in. You have to decide what the best opportunity is for your company. You are missing out if you are not involved. Besides, it’s fun!In addition to being fun, social media interaction can helpyour top and bottom lines. For example, interacting withcustomers via Twitter and other chat technologies yieldedthe following results for Drugstore.com:• The overall phone time that Drugstore.com devoted to customer interaction decreased by 15 percent. E-mail volume shrank by 30 percent. Meanwhile shopping-cart sizes in sales facilitated by chat are now 10 percent to 20 percent larger compared to sales without chat.• Chat sessions deliver a conversion rate of approximately 25 percent; the site’s overall conversion rate is just 6.4 percent• Third-quarter 2010 sales grew 17 percent, compared to 2 percent growth in e-commerce overall• Customer satisfaction scores reached 77 on ForeSee Results’s list of the top 15 online retailers 374
  • 8. FOREWORD 1 2 3 4 CONCLUSIONSCOMMENT BY ESTEBAN KOLSKYBrent makes a couple of very interesting points that are 20 and 100 times larger than structured data volumes.worth exploring in more detail. First, he talks about the need Unstructured data complements structured data; it doesn’tto listen. Customers give organizations lots of information, replace it. So organizations must match their new data tobut it typically doesn’t take the form of perfectly structured existing data about customers and their experiences, anddata. This was the error in the previous methods that tried integrate all the data sources to obtain more comprehensiveto generate 360º customer profiles: We relied on structured views of their customers.data provided by transactions and interactions. We assumedthat customers who behaved in a certain way once would do The problem is that these gigantic data volumes arethe same thing again in a similar situation. cumbersome to manage. Organizations have limited capacity and will to parse data and create actionable insights fromThe problem is that we never bothered to ask why our them. This was the problem that created the second evolutioncustomers behaved in particular ways or what their needs of CRM software: analytical CRM.were. We simply assumed that their actions told us everythingwe needed to know. This was our great error. We can onlycorrect that error by collecting unstructured data, analyzingthem, and creating actionable insights from them.Listening is the first step. Organizations have always knownhow to create surveys (some good, some awful, most in-between), distribute them, and collect the data that theyproduce. With the advent of social networks and socialchannels, we finally found the source for the unstructureddata that would complete the thoughts started by traditionalstructured feedback events such as surveys and focus groups.For better or worse, both methods generate lots of data.Today, unstructured data volumes collected from customerinteractions and transactions are estimated to be between 384
  • 9. FOREWORD 1 2 3 4 CONCLUSIONS3 The Rise of Analytical CRM Mark Tamis Never before in history have we been able to gather Although these tools have their merits, they don’t trace and store so much data about customers. We start with connections between the various data points that we have contact information, purchases, support interactions, leads about a given customer. Nor do they help us decide how and opportunities. The social web allows us to capture we should respond to that customer, or even whether we data about site navigation and the like. And now we’re should respond at all. adding even more data points: Facebook Likes, Twitter microblogging, and online customer communities. To state the obvious, business decisions should be guided by customer data and analysis. Although the sheer volume So how do we turn vast data volumes into actionable of social data is daunting and the tools far from perfect, insights that are relevant both to our organizations and we should try to use these data to enhance what we’re to the customers we are trying to serve? There’s still a already doing with transactional data. Each customer’s disconnect between data captured by CRM systems and cross-channel activity will need to be captured and blended behavioral data that we capture through social media into customer “snapshots,” building on the historical and channels as well as traditional channels such as email, transactional content of the CRM system. surveys and interaction with customer service reps. Step one is finding identifiers that link customers to their The data sets captured in the different channels are hardly identities on the Social Web. Ideally this would happen ever correlated effectively with data from other sources. We through an opt-in procedure, for example when the seem satisfied to track Facebook fans and Twitter followers customer visits your community support forum and fills out without following through to see whether all these fans her profile, sends in her warranty card or signs up for her and followers were already customers or if they actually loyalty card. bought from us after stating their interest. Nor do we try to capture how fans and followers influence others in their The next step is to mine and analyze relevant interactions social networks and how this influence affects our brand that we can match with a persona. Micro-segmentation can images and sales. give us insight into the experiences that our customers expect and suggest appropriate responses. New analytic tools such as Radian6, Attensity and Lithium try to organize unstructured data by using clever filtering This matching can be based on personality analytics, to automatically or manually create CRM system entries. sentiment evolution, social and interest graph Continued on next page 394
  • 10. FOREWORD 1 2 3 4 CONCLUSIONSThe Rise of Analytical CRM (cont’d)segmentation, product portfolio, issue anticipation, and soon. The analysis should help us make business decisionsregarding the desirability of the customer.Social data also create opportunities for predictive analysis,due to our real-time access to the customer’s voice. As theysay, the best customer service is no service!You also need to consider where your data are stored.Increasingly this is done via data centers managed bythird-party infrastructure providers, otherwise known as“the cloud.” Contrary to popular belief, the real promiseof cloud computing is not the ability to outsource yourIT management or access applications and data fromanywhere. Rather, it’s the ability to quickly connect yourdatasets to those of your partners, suppliers, and channels,and mine the collective data for customer insights that youwould miss if you were only looking at your own data.The Social Web has given us many new ways to fine-tune customer information. Going forward, the mainchallenge will be linking customer identities acrossdifferent interaction channels and blending structured andunstructured data into clean datasets that we can mine foractionable insights. 34 10
  • 11. FOREWORD 1 2 3 4 CONCLUSIONSCOMMENT BY ESTEBAN KOLSKYMark’s vision underscores the fact that we gather social 5. Iterate. Analytics is not an end game. New technologiesand other data about our customers in order to generate and tools allow organizations to take on new challengesactionable insights. This should be the goal of any company and gain a better understanding of what they are after.that analyzes the data they collect from their customers Make iteration a core part of your strategy.and their operations. It’s the main reason to invest infeedback and data management initiatives. But today, most Unfortunately, these steps don’t guarantee success. Toolorganizations that deploy data analytics seem to believe interfaces may be getting simpler, but pretty screens alsothat actionable insights arise from some magic strike, lucky hide the true complexity of analytics. Talented analysts areguess, or black box method. still the most critical component in analytics—and they are very hard to come by. If you want to succeed at theThe five keys to effective data analysis are: game of analytics, either hire the expertise you need or train committed individuals to extract vital insights from the sea1. Always know what you are seeking. Diving into a of data in which all businesses swim. Big Data set “just to see what’s there” will only yield frustration.2. Understand what you have. To achieve useful results, it is critical that you understand what the data are, what they say, how they flow through the systems, how they are used by the organization, and how they relate to other data points.3. Correlate to KPI. Data insights must be correlated with your organization’s key performance indicators. Analytics must articulate with past performance issues and future needs.4. Define Actions. You can’t have actionable insights without actions. You must know what should happen when data processing yields a value that falls above or below expectations. 34 11
  • 12. FOREWORD 1 2 3 4 CONCLUSIONS4 Big Data, Big Problems Tyson Hartman In the global marketplace, businesses and employees are puts even more pressure on executives to consume even creating and consuming more information than ever before. more information. Which begs a question: Are executives Gartner predicts that enterprise data in all forms will grow addicted to data? The following data points would suggest by 650 percent over the next five years, while IDC claims that the answer is yes. that global data volumes double every 18 months. • 70 percent of business leaders report that their current According to “The Business Impact of Big Data,” a new IT infrastructure allows employees to get the data they global survey of C-level executives and IT decision makers need at the speed they need it. commissioned by Avanade, this data deluge is creating very • 61 percent of executives still want faster access. real challenges for business leaders. • One in three say they need even more sources of data in order to perform their job better. Big Data – Hype or Reality? Across industries, regions and companies, executives report For many, this data addiction is driven by the inability to that the exponential growth in data is degrading their ability find the information they need. In fact, a recent survey to access critical information. According to the report, 56 found that during the recent recession, more than one- percent of business and IT executives feel overwhelmed by quarter of executives lost business because they couldn’t the amount of data their company manages. Many report access the right information. This dearth of accurate that important decisions are often delayed because they information pushes executives to continuously search for have too much information. better information, creating an addictive behavior pattern. Despite these challenges, executives see some value in the So what kind of information are executives most concerned data deluge. For instance, 61 percent believe that the flood about? According to the survey, their top priority is the of data entering the enterprise fundamentally changes the ability to keep up with customer-service expectations. way their business operates. And when it comes to perceptions of the most data categories, customer information leads the pack. This focus Data Addiction on customers is driving technology investments in CRM Although the onslaught of data can make it more difficult systems—67 percent of executives have already invested for executives to make decisions, they are still asking for in CRM or are seriously considering doing so over the next more data, and they want it even faster. This desperation 12 months. for the right information to make business decisions Continued on next page 34 12
  • 13. FOREWORD 1 2 3 4 CONCLUSIONSBig Data, Big Problems (cont’d)Executives are recognizing the opportunity to leveragetheir customer data in order to create new revenue streamsand generate new business. Alarmingly, however, fewerthan half of all managers view the available sources ofdata as strategic differentiators for their organizations.They struggle to understand how Big Data can drive realbusiness value.Big Data, Big ValueSo how do we get from where we are today to where wewant to be? First, companies must develop a “data culture”in which executives, employees, and strategic partners areactive participants in managing a meaningful data lifecycle.Companies need to start educating their employees on howto best participate in this process.This is not just a technology challenge. It’s also a peopleand process problem. It takes a culture shift among thepeople who are interacting with the data—whether theyare producing or consuming—to be more accountable fordata management.Tomorrow’s successful organizations will be equipped toharness new sources of information and take responsibilityfor accurate data creation and maintenance. This willenable businesses to turn data into usable information firstand then ultimately into true business insights. 34 13
  • 14. FOREWORD 1 2 3 4 CONCLUSIONS Conclusions“It is imperative that companies So what have we learned? Not only did we lack the necessary The original CRM vision failed due to the lack of sufficient develop a ‘data culture’ in data to understand our customers holistically, we also lacked data and processing ability for the data that existed. We are which executives, employees, the operational capacity to manage and learn from the Big solving those issues today, but CRM is still not an automaticand strategic partners are active Data sets that we created. How should organizations deal solution. participants in managing with Big Data? There’s a vast literature of attempts to answer a meaningful data lifecycle” this question, but the following three steps are crucial. Three core areas need to be explored in more detail: – Tyson Hartman 1. Recognize. You must recognize that your current systems, Listening. Listen to the customer’s needs and desires through analytic engines, databases, and potentially your architecture direct, structured feedback and interactions. This is the first are not prepared to handle the deluge of Big Data. Trying to step towards discovery of the necessary data. accommodate an aging and inappropriate infrastructure is a recipe for failure. Big Data. Unstructured datasets are 20 to 100 times larger in volume than structured datasets. The new social datasets 2. Plan. To accommodate slow growth as opposed to a must be understood and then articulated with existing data landslide of data clobbering your systems, figure out what to create blended datasets that can provide the insights we data will be coming from what channels and create a plan need. to accommodate the various data streams. Once you have the first data stream under control, focus on the second Analytics and Actionable Insights. Analytics are not, as and third, and so on. Plan for a gradual assimilation of the we used to believe, about understanding the relationship magnitude of data you will receive. between data and data elements. We need to build an analytical model that produces actionable insight into what 3. Learn By Doing. You are now dealing with a lot of issues our customers need and desire. that your organization did not have to deal with before. Is it better to store all data and eventually get around Organizations that embark on this journey will be trailblazers, to analyzing it? Or would we be better off simply doing building a repertoire of best practices and lessons learned real-time analytics and storing the results? How much more than relying on others. Some will reap the reward of accuracy is required, and how can we achieve it? You can’t nearly perfect knowledge about their customers. answer these questions until you’ve been confronted with them. Resolve to learn as you go and constantly improve Will your company be one of them? your implementation. 34 14
  • 15. FOREWORD 1 2 3 4 CONCLUSIONSAuthor BiosEsteban Kolsky is the principal and founder of ThinkJar,an advisory and research think tank focused oncustomer strategies.Brent Leary is co-founder and partner at CRM EssentialsLLC, a CRM consulting/advisory firm focused on small andmid-size enterprises.Mark Tamis is a noted blogger on social CRM withconsiderable experience in enterprise software.Tyson Hartman holds the title of Avanade Fellowat Avanade, a Seattle-based technology solutions provider.In this role, Hartman works with the senior technologyteam to define the vision and road map of Avanade’ssolution development practices. 34 15
  • 16. FOREWORD 1 2 3 4 CONCLUSIONSAbout UsSmartData Collective, an online community moderatedby Social Media Today, provides enterprise leaders accessto the latest trends in Business Intelligence and DataManagement. Our innovative model serves as a platformfor recognized, global experts to share their insightsthrough peer contributions, custom content publishing andalignment with industry leaders. SmartData Collective is akey resource for executives who need to make informeddata management decisions.About Our SponsorTeradata is the world’s largest company solely focusedon creating enterprise agility through database software,enterprise data warehousing, data warehouse appliances,and analytics. They deliver award-winning, integrated,purpose-built platforms based on the most powerful,scalable, and reliable technology platform in the industry,with assets including:• Approximately 7,400 associates in more than 42 countries• Strong diversified client base of over 900 customers worldwide and companies of all sizes• 2,000+ implementations worldwide 316

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