IBM SoftwareDigital Media

Technical White Paper

Big data and analytics for a holistic customer journey

Contents

1 Foreword

2 Overcoming big data challenges for insight and opportunity

3 How to acquire, grow and retain customers

5 IBM big data platform and IBM PureData System for Analytics

7 Engaging clients through value and insight

10 Roadmap to holistic customer engagement through big-data analytics

11 Conclusion

Foreword What your customers primarily concern themselves with, and rightfully so, is their own never-ending journey through life. All they really want is to bring more satisfaction, fulfillment, and fun into their own existence.

In the modern business world, customer experience is everything. Digital marketing focuses on ensuring a seamless, holistic, multichannel experience to all customers all the time. This is the pivotal concept of a “holistic customer journey.” Big data and agile analytics are key tools to help your company personalize and target the delivery of superior experiences to all customers.

The business stakes could not be higher. In an experience-driven economy, your customers will quickly leave you if you don’t offer an experience that’s tailored to their ever-changing life circumstances. To re-align your customer-engagement initiatives around this new reality, you will need a clear roadmap for where to start and how to proceed.

This strategic whitepaper provides that roadmap. It offers an in-depth discussion on how you can use big data analytics to enhance experience while boosting the bottom line. It includes informative case studies on

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how other companies have used big data analytics to delight their customers. And it helps you understand which IBM big-data solutions might support your own company’s initiatives in digital marketing, multichannel engagement, and customer experience optimization.

It’s a highly readable compendium with solid advice. It’s well worth your time.

James Kobielus IBM Big Data Evangelist

Overcoming big data challenges for insight and opportunityConsumer attention is shifting from traditional channels such as TV, radio and print media to digital media channels and devices. A study by Forrester Research found 50 percent of US consumers’ time was spent online, with thousands of new digital devices competing for consumer attention. Marketers have to maneuver their way through transactions and click-streams; call-center interactions, e-mail and retail store visits; product and service feedback and social media channels.

The potential to leverage big data is unlimited. Each industry has its own unique challenges that can benefit from using big data for new insights and improved decision-making. The fol-lowing five cross-industry use cases provide excellent starting points for anyone looking to begin their big data journey:

According to an Aberdeen Group paper, “Big Data for Marketing: Targeting Success,” the number of firms planning to increase their use of data analytics for marketing is 98 percent.

Security/intelligence extension

Enhanced 360º view of the customer

Operations analysis

Big data exploration

Data warehouse augmentation

Process and analyze new types (social media, emails, mobile,3rd party) and sources of under-leveraged data to significantlyimprove intelligence, security and privacy.

Extend existing customer views by incorporating additionalinternal and external information sources.

Analyze a variety of machine and operational data for improvedbusiness results and gain visibility into operations, customerexperience, transactions and behavior.

Find, visualize and understand volumes of information toimprove decision making.

Integrate big data and data warehouse capabilities to increaseoperational efficiency and optimize your data warehouse toenable new types of analysis.

Figure 1. Big data use cases

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This “big data”—the enormous volume, variety and velocity of data being produced—holds tremendous potential for marketing professionals to gain unprecedented insights about consumers. Insights derived from big data analytics will drive future decisions in accurately delivering the right message to the right person at the right time at the right price for maximized customer value.

The wealth of big data can be used to create win-win scenarios in which insights are turned into relevance as customers prog-ress through the purchase funnel. Yet the volume, velocity and variety of big data also comes with numerous challenges defined by questions about how best to access, analyze, optimize and apply insights to innovate customer lifecycles and create differentiated experiences:

●● Are we acquiring, aggregating, and analyzing the right data sources?

●● Does fine-grained customer segmentation and inf luence assessment truly help us to target our campaigns for maximum lift?

●● Do proactive big-data-powered target marketing and engagement efforts expose us to charges that we’re invading privacy and stalking the customer?

●● Are we going too far or not far enough to bring social, mobile, and other digital channels into the core of our customer engagement strategies?

●● Should we be incorporating real-time click-stream analytics and other behavioral data sources into efforts to tune the customer experience across multiple channels?

●● Are we truly differentiating with all of these digital engage-ment efforts, or simply keeping up with the competition?

This paper will discuss how marketers and advertisers can manage the constant f low of big data and gain the necessary insight to rethink their data environments for new value—using analytics and social and mobile technologies. Discover how the IBM big data platform and IBM® PureData™ System for Analytics, powered by Netezza® technology, can help marketers better acquire, grow and retain customers, target high-value customers, determine the best channels for reaching those customers, tailor the messaging and ultimately deliver better results.

How to acquire, grow and retain customersDo your competitors have more insight about your customers than you do? Are you effectively converting your audience insights into added value for your consumers? The following four objectives can help you can acquire, grow, and retain cus-tomers by improving customer interaction, building long term relationships and realizing value from customer sentiment.

1. Personalization—Ensure each customer interaction is unique and tailored to buying journey by predicting best communi-cation method, channel, message, and time of delivery.

2. Profitability—Enhance a customer’s lifetime value through advanced association methods that deliver targeted up/cross-sell offers in real-time and optimize use of marketing resources.

3. Retention—Increase retention and customer satisfaction by detecting anomalies in desired behavior through sentiment analysis and scoring to proactively make tailored offers.

4. Acquisition—Improve accuracy and response to marketing campaigns, reduce acquisition costs and predict lifetime value using granular micro segments based on profitable customers.

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Delivering a superior customer experiencePredictive analytics captures unstructured and structured data, uncovers hidden patterns and associations within that data to determine future outcomes, and acts upon the insights gained through optimized, real-time decision making.

The following three objectives of customer analytics can help your organization gain deep understanding into customer atti-tudes and preferences to predict future behavior and deliver a 360-degree view of the customer throughout their lifecycle:

Obtaining the right data on your customer. This includes data on customer sentiment, customer experiences and feelingsas well as inclinations and predispositions. The best place to find such information is through social media. The challenge for marketers is how to harvest that intelligence and bring it into a big data platform and correlate it with all the historical data on customer buying patterns etc. There are many addi-tional, typically siloed, sources of data, such as mobile and geospatial, to combine with customer records to monitor behavior and drive rich intelligence into predictive models.

Process, store and manage data. Unstructured sources of datare rich and intelligent. Marketers need to process, store them and manage these types of challenging data sources in a coher-ent way. Scalability and processing power is key as you bring in more sources of structured and unstructured customer data. You want the ability to enhance that historical and real time record of your customer as your ability to appropriately apply that data grows to add value along the purchase funnel.

Build predictive models. Data scientists who are essentially statistical and predictive modellers can help with complex tasks including customer marketing and churn analysis. These experts can help build and tune these models from all of this data. Therefore, you need to train and cross-train existing data

modellers in new approaches that are fundamental to marketing campaign analysis, such as MapReduce and R, text analytics and more to visualize patterns and acquire, grow and retain customers through personalization, profitability, retention and acquisition.

Past, present and future time horizons

a

The following deep past, present and future core components are important when it comes to a big data infrastructure and obtaining a 360-degree view of the customer:

Deep past: How deeply can you look into the customer’s history when identifying how best to serve them? You need the full historical customer record, including all purchases, transactions, and interactions. Missing information about the customer during an interaction results in inappropriate or incomplete offers and communication, inconsistent service delivery, and weak customer relationships.

Deep present: How deeply can you drill into the moment that the customer is currently experiencing, such as clicking on products on your website, in your store, or speaking with a call center representative? You need to correlate the full historical customer record with real-time feeds of customer click-streams, interactions, geospatial coordinates, social posts, and other behavioral data that changes moment to moment.

Deep future: Do you have predictive capabilities when it comes to your customer’s future, and how confident are you that you can nudge that future in a positive direction with actions you take right now? You need to continuously generate next best actions by aggregating past and present data; mining it for patterns relevant to customer propensities; and using it trigger embedded predictive models that can drive loyalty, upsell and experience.

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Driving customer interactionsBy asking how, why, who and what, questions requiring multi-ple systems, a fusion is achieved that enables deeper insights:

1. What products can I up-sell this customer?2. What impact will inventory have on this customer?3. What marketing materials or “next-best-offer” should I send?4. What should I know before contacting for renewal?5. What’s going on with this customer today?6. How can we increase engagement?7. How can we get more customers like this person?

By bringing disparate data sources together to create a single view of each customer, companies start to see increased customer satisfaction and decreased customer churn. When enterprise data is brought together with unstructured data for real-time predictive and social analytics, there are benefits along the content delivery value chain. This includes a deep understanding of audience sentiment, as well as the ability to anticipate customer behavior and offer real time incentives to accelerate offer acceptance and overall conversions.

IBM big data platform and PureData System for AnalyticsAccording to Aberdeen Group’s “Big Data for Marketing” survey, best-in-class companies’ data analytics for marketing is focused on improving the targeting of offers, delivering the right message to the right person through the right channel at the right time. Best-in-class firms are combining campaign management and insight with customer analytics for invaluable customer sentiment.

IBM big data platformTo achieve best-in-class requires transformation to data-driven marketing. Such initiatives require agility, yet major change is often constrained by IT system lifecycle costs and complexity. IBM is unique in having developed an enterprise class big data platform that enables marketers and advertisers to address the full spectrum of big data business challenges. The big data platform can help process and manage historical data at rest, real-time data in motion as well as execute the predictive models to help keep your customer relationships growing.

Figure 2. IBM big data platform

CONSULTING AND IMPLEMENTATION SERVICES

SOLUTIONS

ANALYTICS

BIG DATA PLATFORM

SECURITY, SYSTEMS, STORAGE AND CLOUD

sales, marketing, finance, operations, IT, RBI, HR, industry

performance management, risk analytics,decision management, content analysis

business intelligence and predictive analysis

content management, Hadoop System,stream computing, data warehouse

information integration and governance

Figure 3. Driving customer interactions with next best action solution

360 Degree Customer View

How? Why?

What?Who?

Interaction data

Descriptive data Behavioral data

Attitudinal dataEmail or chat transcriptsCall center notesWeb click streamsIn-person dialogues

OpinionsPreferencesNeeds and desires

AttributesCharacteristicsRelationshipsSelf-declared informationGeographic ordemographic data

OrdersTransactionsPayment historyUsage history

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Marketing organizations need to combine the past, present and future analysis of customer data using a holistic big data platform. IBM provides a consolidated and integrated approach to big data and analytics:

●● Assemble and combine a relevant mix of information●● Discover and explore with smart visualizations●● Analyze, predict and automate for more accurate answers●● Take action and automate processes ●● Optimize analytical performance and IT costs ●● Reduce infrastructure complexity and cost ●● Manage, govern and secure information

PureData System for AnalyticsIBM PureData System for Analytics, powered by Netezza tech-nology, powers predictive analytics and statistical modeling to meet the needs of your customers, improve response rates on marketing campaigns, and improve click-through rates on various solicitations and product offers.

According to the IBV executive report, “Analytics: The real-world use of big data, How innovative enterprises extract value from uncertain data,” many organizations are basing their business cases on the following types of big data decisions:

• Smarter decisions—Leverage new sources of data to improve the quality of decision making.

• Faster decisions—Enable more real-time data capture and analysis to support decision making at the “point of impact,” such as when a customer is navigating your website or on the telephone with a customer service representative.

• Decisions that make a difference—Focus big data efforts toward areas that provide true differentiation.

To accomplish these data driven marketing efforts, IBM PureData System for Analytics delivers the proven performance, scalability, intelligence, and simplicity that organizations need to delve deep into their data:

Fast. Due to massively parallel processing architecture, IBM Pure Data System for Analytics can perform data queries 10 - 100 times faster than traditional custom systems. This will help marketers and advertisers go “from weeks to hours” turnaround time to slice and dice more complex sets of audience, advertiser, and 3rd party data to meet the reporting demands of audience research, advertising and marketing teams.

Scalable. IBM Pure Data System for Analytics System provides up to peta-scale data capacity starting with 96 terabytes on a half-rack system. This enables IT departments the certainty to grow with the data volumes from their business teams as they need to analyze new and more sources of digital media and marketing data.

Simple and completely integrated. Deliver high performance automatically, with no indexing or tuning required. The inte-gration of hardware, software and storage is already done leading to very short deployment cycles to get the analytics up and running quickly. A portal helps to monitor and manage all aspects of administration for a single, easy-to-use access point.

Marketing objectives achieved with PureData System for AnalyticsAs marketers and advertisers increase their demands to quickly ingest, analyze, develop insights, deliver relevance and drive new business processes from a wide variety of existing data

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types and sources and from new data being generated throughout a system of engagement, IBM PureData System for Analytics can help them achieve the following objectives:

1. Audience optimization: Enable higher precision identifica-tion, analysis, measurement, and targeting of existing and new audiences for content/programming, brands, or campaigns.

2. Advertising optimization: Maximize advertising revenue through better mapping, measurement, analysis, and reporting of all available inventories within and across all available media platforms.

3. Marketing optimization: Achieve higher precision audience targeting, optimized media planning, and campaign level analysis/reporting for marketing teams, MSPs and other media buying entities.

4. Digital commerce optimization: Improve the precision, relevance, and discovery of digital content offering to its audience members to drive greater engagement and direct revenue.

5. Business operations optimization: Improve forecasting, management and optimization of operational resources and assets.

Engaging clients through value and insight2degrees MobileAs a mobile communications provider, 2degrees is revolutioniz-ing mobile communications with the country’s first pay-as- you-go service. Its approach has been embraced by more than a million consumers seeking greater f lexibility and lower costs. However, with no long term contracts, 2degrees must closely monitor the customer experience as consumers can easily switch to another provide if they’re not satisfied. Using a high-performance big data analytics platform from IBM, the

client is gaining new insight into its network and business operations that helps it prevent churn and negotiate more profitable agreements with retailers.

Benefits:●● Helped staff uncover the cause of a customer service problem

affecting more than 60,000 subscribers●● Expected to help staff pinpoint the optimal location for new

cell tower sites●● Improved contract negotiations, enabling staff to negotiate

more profitable contracts with retailers●● Accelerated query performance by 10 - 100 times●● Improved data load times

According to McCallum, the simplified experience and built-in expertise of the PureData System for Analytics helped the team rapidly deploy its new platform. “The process went incredibly smoothly,” says McCallum. “About two days after the PureData System went into the data center, we were ready to go. We worked with Lexel [an IBM Business Partner] to migrate the data from the Oracle platform to the IBM platform in March and April and switched over in May. Lexel provided a lot of added value about how to get the most out of our new system.”

“We negotiated better contract terms with the retailer for a more positive financial outcome.”

—Peter McCallum, Information Solution Manager, 2degrees Mobile

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Trident MarketingTrident Marketing is a direct response marketing and sales firm for leading brands such as DirectTV, ADT and Travel Resorts of America, handling more than four million calls per year for its clients.

For Trident Marketing, success is based on its ability to acquire the largest number of paying consumers for its custom-ers while minimizing the cost of sales. That means running highly targeted and efficient demand-generation campaigns. But the company lacked key insights into the performance and efficiency of its campaigns across channels, from the call center to the web. It could not measure basic close rates, or determine why some sales pitches worked while others failed. The company needed better visibility across channels as well as the ability to analyze and optimize performance.

Trident Marketing uses PureData System for Analytics to capture massive amounts of data from the call center, order systems, CRM application, credit bureaus and search engines to predict how customers respond to campaigns across channels. The company can quickly determine when to call a consumer, which product to pitch and which salesperson is best suited to close the sale. Plus, sophisticated analytic models can also predict which consumers are likely to cancel services within 12 months. In addition, analysis of click-stream data from search engines helps the company optimize its pay-per-click bids.

Benefits:●● Increased revenue by 1,000 percent in four years by making

sales and marketing campaigns more targeted and effective.●● Achieved a 10 percent increase in sales in 60 days by choos-

ing high-yield PPC keywords.

●● Improved pay-per-click (PPC) bids, calculating click-through rates, the number of calls generated by each keyword, the cost per call and close rates, along with a record of products sold. With this information, Trident Marketing can see clearly which keywords generate the highest yield for its customers and determine what bid levels are justifiable for each keyword.

●● Gained the ability process more than a million keywords, with a large number of permutations, quickly enough to support its fast-turn promotional campaigns.

●● Supports complex analytical models on hundreds of thou-sands of consumers, creating significant value for Trident Marketing and its customers by accelerating analysis.

“We anticipate taking predictive analytics beyond the marketing process, all the way through sales and into our ongoing communication with customers. We see bringing this into the sales area as the best way to monetize it.”

—Brandon Brown, marketing CIO, Trident Marketing

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DatalogixFounded in 2002, Datalogix has built a successful business helping companies drive better performance with their direct mail campaigns. Datalogix developed an online capability with a vision to leverage the power of off line data, targeting and accountability, and bring it to the digital world.

Datalogix had already proven that it could deliver a high return on investment with off line data, and it felt that the same target-ing precision could be delivered online. Their infrastructure could not support the growing online data volumes and analysis required. The IBM PureData System for Analytics, powered by Netezza technology, was implemented, providing speed, scalability and modeling capabilities.

Benefits:●● Drastically improved query turnaround time from 24 hours

to 15 minutes.●● Scaled to support 50 percent data volume growth per year.●● Increased campaign performance by 50 percent.●● Improved ROI.●● Gained the ability for analytic people to run their own

queries; can join a 400 million row table to a 600 million row table in minutes.

●● Gained the ability to track multi-channel performance.●● Helps the client optimize its bidding on the display ad-

exchanges, which is a complex task. The company has to incorporate frequency capping and price volume curves into its bid optimization algorithms.

An eyewear retailer in the United States anticipates improving marketing effective-ness by 10 percent, developing more person-alized campaigns, and conducting faster and richer customer segmentations based on customer attributes.

North American retailerSweeping change was required for a large North America retailer. To acquire new customers and increase market share, marketers wanted the ability to “meet” customers during the shopping process. To retain existing customers and expand cross-selling opportunities, campaigns had to be more relevant and personalized, instead of being just about brand. And to manage and measure campaign effectiveness, the company needed advanced analytic capabilities. As such, the retailer sought to bring much of its valuable data back in-house and limit its outsourcing to campaign execution.

The retail giant implemented the Aginity Customer Intelligence Appliance (CIA), an integrated set of smart and adaptable software, hardware and embedded analytics built on the IBM PureData System for Analytics platform; a high- performance, scalable, massively parallel system that is powered by IBM Netezza technology and combines a database with server and storage technology in a single solution.

The solution helps transform marketing efforts with a sophisti-cated solution powered by advanced behavioral analysis tools. It also captures and consolidates customer, sales and product data from dozens of internal and external applications, resulting in an unprecedented 360-degree omni-channel customer view that helps the company identify and segment its most profitable customers and sales channels. By segmenting, tracking and scoring customers based on thousands of behavioral attributes, such as shopping frequency, spend, historical purchases, sea-sonal buying habits and countless other factors, marketers can refine, target and customize marketing campaigns down to the individual level while simultaneously boosting customer loyalty, retention and revenue.

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Benefits●● Anticipates improving marketing effectiveness by 10 percent. ●● Gains ability to develop more personalized campaigns that

demonstrate intimate knowledge of each customer’s buying preferences.

●● Enables marketers to conduct faster and richer customer segmentations based on customer attributes.

●● Gains the ability to acquire new customers by targeting non-digital channel shoppers to purchase items through the company’s commerce site.

●● Enables data feed from online channels and the ability to capture data from numerous customer interaction devices, such as smartphones, tablets, PDAs and laptops.

●● Enables capture and ingest of customer behavioral data from online sales channels, in-store POS systems, and internal and external customer databases, and feed it to the analytics engine.

●● Provides a 360-degree, highly detailed view of customer trends, preferences and patterns across all sales channels, helping the company create highly targeted, relevant campaigns and track, score and segment nearly 100 million customers.

Roadmap to holistic customer engagement through big-data analytics

From improving customer insight to waging loyalty campaigns and implementing retention strategies, businesses are presented with a range of challenges—and a wealth of tools—from which to choose. Today’s big data requires sophisticated analytics that use iterative analysis and pattern recognition, not to mention the ability to handle the sheer size of data workloads with which businesses must now contend.

Migrating from traditional marketing approaches to data-driven techniques is a significant process that takes time. The follow-ing five steps can help digital media organizations achieve acquire, grow and retain customers:

1. Recognize the vast new amounts of consumer data as the emerging core asset in your digital marketing future. Until you take this step you will be standing still as competi-tors with greater foresight surge ahead. Determine if your organization requires deep dives on what people are saying on social media. It may be that your target market are those individuals who don’t use social media heavily or aren’t inf luenced by social challenges.

2. Gain access to your own big data. Even very basic analysis of the data you own but haven’t yet studied can yield meaningful insights about customer loyalty, churn, simple likes and dislikes surrounding specific products and brands etc. It can begin an interest for accessing deeper customer insights and without such insights critical goals such as greater personalization in consumer messaging cannot be achieved.

3. Commence simple, data-driven campaigns to apply reliable measurement dimensions to justify moving ahead to more advanced data-based digital marketing. This step is all about deliberate customer engagement based upon elementary analysis and the insights gleaned. Digital market-ing lends itself to more solid ROI measurement than any of the devolving traditional approaches. Your migration into big data digital marketing is heavily dependent on demonstrating ROI.

Figure 4. Big data preparation by media and entertainment clients

Have notbegun big data

activities

Planning big data activities Pilot andimplementation ofbig data activities

24% 47% 28%

1 243

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4. Add platform services and talent to expedite the develop-ment of an expanding big data-focused culture in your marketing organization. Once you have proven that small campaigns rooted in basic data analysis can be clearly correlated to improved ROI, you will be in a position to take advantage of tools like data management platforms (DMPs) and demand side platforms (DSPs). These relatively inexpen-sive platforms dramatically increase your access to data across multiple channels and provide more personalized and predictive customer insights around which to build more targeted campaigns.

5. Seek out and invest in your own big data platform. This is the natural result of rigorously adhering to ROI measure-ment, the addition of data-science talent that understands marketing principles and the positioning of big data analytics as the new core for digital marketing—a multi-year process. A critical factor, no matter where you are starting from, is to build f lexibility into your strategy so you can add new sources into your big data platform as well as new types of analytics as your needs evolve.

ConclusionCustomers won’t wait for you to upload the nightly batch of fresh intelligence for new offers. Your business needs a real-time, 360-degree view of the world through the customer’s eyes that is updated moment-to-moment. Throughout the world, marketing and digital media organizations face a growing variety of analytics tools while also facing a critical shortage of analytical skills. Big data effectiveness hinges on addressing this significant gap. The optimal market and customer strategy can help an organization turn customers into advocates, infuse customer interactions across each channel with positive impres-sions of the brand, and help engender a feeling of loyalty across the customer base that drives campaign performance and positive business results.

Marketers need to be as agile as possible in this fast paced and changing connected consumer era. This requires an uncompli-cated, easy-to-maintain system that runs lightning fast and analyzes growing digital media-based data volumes. IBM Pure Data System for Analytics offers one of the fastest time-to-value for important business intelligence and analytics initiatives.

About IBM PureData System for AnalyticsThe IBM PureData System for Analytics, powered by Netezza technology, integrates database, server and storage into a single, easy-to-manage appliance that requires minimal setup and ongoing administration while producing faster and more consistent analytic performance. The IBM PureData System for Analytics simplifies business analytics dramatically by con-solidating all analytic activity in the appliance, right where the data resides, for industry-leading performance. Visit: ibm.com/PureSystems to see how our family of expert integrated systems eliminates complexity at every step and helps you drive true business value for your organization.

About IBM Data Warehousing and Analytics solutionsIBM provides the broadest and most comprehensive portfolio of data warehousing, information management and business analytic software, hardware and solutions to help customers maximize the value of their information assets and discover new insights to make better and faster decisions and optimize their business outcomes.

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For more informationHelp IT make the shift to the strategic center of your business, and leverage proven expertise to take the lead. To learn more about the PureSystems™ family and the PureData System for Analytics, contact your IBM representa-tive or IBM Business Partner, or visit the following websites: ibm.com/PureSystems/PureData/ or http://www-01.ibm.com/software/data/puredata/analytics/

To learn more about the IBM big data platform, visit: ibm.com/bigdata

Additionally, IBM Global Financing can help you acquire the software capabilities that your business needs in the most cost-effective and strategic way possible. We’ll partner with credit-qualified clients to customize a financing solution to suit your business and development goals, enable effective cash management, and improve your total cost of ownership. Fund your critical IT investment and propel your business forward with IBM Global Financing. For more information, visit: ibm.com/financing

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