TCS - Retail Journal

ForumTCS - Retail Journal

Experience certainty.

Feb 14 | Issue 3


Foreword

Pratik Pal President & Global Head,Retail, CPG, Travel, Transportation & Hospitality

Welcome to the third edition of Forum, the TCS Retail thought leadership journal.

This edition focuses on how you can reimagine your customer engagement and provide a superi-or customer experience.

The confluence of the five digital forces of Mo-bility, Big Data, Cloud, Social and Analytics have empowered retailers to reimagine the shopper’s journey. In this era of Digital Darwinism and rad-ically changing consumer behavior, listening to customers and contextually engaging customers with deep personalization are the best bet for long term profitability and customer loyalty. This implies a transformational change in the underly-ing business model, processes, and tools.

This edition highlights our perspective on how you can personalize the customer journey to heighten customer engagement, why it is impor-tant to have a 360-degree view of the customer, how to design a compelling customer loyalty experience (CLX) to deliver long term value to your customers, and what it takes to build a uni-fied view of the customer to know them and their needs better.

We are also happy to share our point of view titled ‘How Retailers can Create the Right Social Circle’ based on TCS Global Trend Study—‘Mastering Dig-ital Feedback’, that offers insights on social media trends, adoption, and investments. 650 consumer company executives worldwide participated in the survey, lending this study a focused retail industry perspective.

We look forward to receiving your suggestions and feedback at [email protected].

Wishing you a very happy 2014!

Warm regards,Pratik Pal


ContentCurate Digital Customer Engagement with Extreme Personalization

Unified View of Customer: It’s All About Customer Experience

How Retailers Can Create the Right Social Circle

Customer Loyalty Experience: You Can’t Afford to Ignore It

Realizing Unified View for Better Customer Engagement: Understanding What to Build

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Curate Digital Customer Engagementwith Extreme Personalization

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Curate Digital Customer Engagement with Extreme Personalization

Across industries, many organizations have cre-ated successful business models by institution-alizing interactions, which enables seamless and continuous conversations with customers across every contact point. However, is it consistently sufficient? More importantly, is it sufficiently con-sistent? Inconsistent interactions can often lead to consumer mistrust, potentially making such efforts more damaging than enriching.

To foster long-term relationships, retailers must offer meaningful personalization. With various digital forces at play, and more significantly, use cases connecting two or more digital channels, a one-to-one relationship with consumers may no longer be a distant dream—it is a fast approach-ing opportunity that needs to be seized. The operations, marketing, technology, and corporate teams will have to come together to define the constructs of designing and delivering these per-sonalized interactions which means that the rules of the retail game need to be redefined.

Commoditization of retail: Why is personalization important?

Customers and retailers are increasingly adopting digital channels, and this has resulted in the avail-ability of and access to product data, reviews and comparisons, price, promotions, and stock levels. This ubiquitous availability of rich data has pushed

digital customer interactions towards transac-tions. While customers are demanding more from retailers—lower prices, better value, larger range, quicker fulfillment—information democratization is the over-arching theme. Customers are con-sistently seeking better deals and this has com-moditized retail, forcing retailers to differentiate themselves through value-added interactions. A transaction becomes more valuable when it involves a personalized interaction—it creates a serendipitous experience by enriching product discovery.

When interactions are defined well, designed to interconnect, and delivered consistently, they nur-ture loyalty. For retailers, personalization will play the single biggest role in their customer experi-ence management efforts (refer Figure 1).

Consider some alarming trends. Around 80 per-cent of retailers confirm that they intend to spend more on paid searches this year, but only 32 per-cent will spend more on behavioral targeting of shoppers.1

“Being on par in terms of price and quality only gets you into the game.

Service wins the game.” - Dr. Tony Alessandra; marketing and behavioral

sciences expert

1 The State of Retailing Online 2013: Marketing & Merchandising by Forrester Research Inc.

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For many global retailers, the focus seems to be on:

• Attracting more traffic to their digital proper-ties.

• Improving conversion rates through rich product data, inventory visibility, checkout optimization, support form factors, extended range of products, and seamless cross chan-nel fulfillment.

The strategy to acquire a loyal customer base therefore cannot be restricted to:

• Merchandizing a wide range of products, also known as endless aisle. This is a con-cept that competitors can quickly replicate.

M

XL

L

Driven by pre-de�ned marketing strategies rather than customer insights, restricting the overall impact.

Driven by data and event aggregation reducing granularity, creating generalizations, and limiting the e�ectiveness of personalization e�orts. Does not acknowledge the unique customer context within each segment (group pro�ling).

Slower data processing owing to the time taken to acknowledge the relevant customer context for each market segment.

Impossible to create a string of personalization dialogues; almost always requires restarting the conversation.

Provides contextual and tailored customer experience based on interaction and transaction trails.

Generates granular customer data, which helps ensure relevant, personalized services.

Enables quick, accurate, and cost e�ective data processing due to the nature of data stipulation.

Allows the usage of a combination of techniques to cater to cold-start (product/ content) problem; anonymous/ new customer.

Segmentation Approach Extreme Personalization Approach

Hi, how can I

assist you?Hi, hope you are

enjoying your new

TV !

Customer Experience

Context-Based Dialogues

Personalization

Figure 1: Segmentation approach vs. extreme personalization

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• Price reduction or competitive pricing, also known as price matching. Retailers cannot win by losing margins.

• Omni-channel presence. Channel congruen-cy is inversely proportional to channel profit-ability, making omni-channel presence more of a necessity than just a customer experi-ence strategy.

Long lasting differentiation can be created only by providing relevant, consistent and high quali-ty experiences—the key differentiator. The rapid proliferation of channels, backed by increased customer adoption, has made retailers define or redefine their cross-channel retail strategy. Today, IT projects are being executed to create a seamless omni-channel experience. In an omni-channel eco-system, it is important for every channel to have an equally important role in fulfilling customer expectations and contributing to a positive brand experience.

Consider this. While waiting at the train station, a person might pull up a mobile app or visit an e-commerce site, and add some items to the shopping cart, compare products, or read product reviews. On reaching home, the person might turn on her desktop PC and continue the journey by completing the transaction, resulting in a longer interaction. Would it be right then to treat the first interaction as a failure? It is a fact that mul-ti-channel conversations result in obtaining more data points to identify the customer’s context and preferences. Traditional CRM and analytics plat-forms might find it challenging to handle this level of dynamic granularity, but when harnessed in the right manner, this data can help create moments of customer euphoria.

Manifesting extreme personaliza-tion

On digital channels, product recommendations constitute the first step in personalizing the user experience. The algorithm for product recom-mendations has evolved from ‘you-may-also-like’ prompts to clickstream-based intelligent recom-mendations. Some companies are experimenting with linking product recommendations with the customer’s in-session activities, wisdom-of-crowd, basket-affinity for products, and product linkages to drive personalization use cases.

While this is definitely a step forward, enter-prise-wide personalization has a much wider implication on the customer experience. Contex-tually appropriate deep personalization scenarios can considerably reduce the cost of acquiring and retaining customers. Comprehensive customer centric marketing can lead to up to three times improvement in Customer Lifecycle Value. 2 Keep-ing customer experience as the primary goal of extreme personalization will deliver these funda-mental benefits:

• Product and content discovery to enable long tail content monetization

• Consistent and efficient enterprise-custom-er conversation to optimize conversation volume

• Opportunities to create serendipitous en-gagement and ensure relevant and fresh customer experience

2 Personalized Marketing Drives Buyer Readiness and Sales; published March 2013, accessed December 2013http://www.marketingprofs.com/charts/2013/10235/personalized-marketing-drives-buyer-readiness-and-sales

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However, this requires a fresh and comprehensive approach that challenges the status quo by incor-porating the following actions:

• Creating 360 degree customer profiles: When based on the foundation of unified customer information, enterprise-wide personalization (refer Figure 2) can lead to dramatically differ-ent and perpetual customer experiences.

Customer information is an amalgamation of each relevant customer interaction—profile, transactions, and interactions. To create a 360 degree view of the customer, it is imperative to record every customer interaction. These interactions could be of varied types—adding items to the wish-list, purchasing items from the gift registry, ‘showrooming’, downloading mobile apps, scanning coupons, conversations with customer support agents, social media activities, and product reviews.

It is critical to define the scope and extent of the customer view which is manageable and sufficient for the level of personalization being envisioned. The extent of customer interactions to be considered in deducing the personali-zation service should be limited to the con-

text which needs to be catered to. Not every interaction will contribute to the richness of personalization service; rather a meaningful combination of interactions might create that moment of euphoria.

Typically, creating a 360 degree view begins with a loyalty-program based customer da-tabase tagged with transaction history. This knowledge base could form the backbone of the retailer’s personalization efforts. Customer profiles and transactions from digital channels are also a good starting point.

• Profiling product and non-product content: The other major aspect of personalization is the content set. Through the evolution of dig-ital channels, rich product metadata such as product specifications, keywords, genre, and product hierarchy is readily available. When mapped with customer interactions, this prod-uct data can be transformed into meaningful product linkages or ontology derived from data modeling techniques. Similar profiling for non-product content such as buying guides, FAQs, and campaigns should be used for con-tent personalization.

Product Pro�le

Content Pro�le

Consumer 3600

Social

Metadata

Knowledge Base

Customer D

B

Transacti

ons

Ingestion

Layer

Personalized

Services

StoreInteractions

WebActivity

SocialActivity

CallCenter

Locations &Commerce

Web

StoreInteraction

Mobile

f

Figure 2: Obtaining a 360 degree view of customer

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By using a combination of customer profiles, and product and non-product ontology, retailers can create various levels of personalization scenarios. Rich customer profiles—where personalization scenarios such as similar, related, associated, and popular products are enabled—facilitate effective one-to-one personalization.

For customers who interact anonymously via different digital channels, or for customers who are new to the enterprise, the cold-start problem can be managed by mapping partial profiles based on current in-session transactions to mathematically similar profiles. The personalization scenarios can be extended to practically any medium of conver-sation with customers: email campaigns, contact center conversations, and in-store connect among others.

The breadth of personalization scenarios, extrap-olated by the uniqueness of entity profiles makes controlling personalization scenarios challeng-ing. By leveraging available explicit knowledge, automated intelligence systems help control and administer personalization scenarios successfully. For example, available business rules or context data can be fed through a rule-based reasoning algorithm and can then be combined with case-based reasoning models to gather inferences from past experiences.

Automated intelligence techniques such as rule-based reasoning, case-based reasoning, genetic algorithms, model-based reasoning, and neural networks help support extreme personalization initiatives. For an enterprise, it is imperative to identify and use the right combination of these techniques, thus making it possible to invoke the appropriate technique based on explicit and implicit knowledge. This approach will cover the full spectrum of one-to-one, one-to-segment, and

one-to-many personalization use cases and will specifically help address challenges around anon-ymous customers, product or content cold start, and above all, using personalization for nurturing loyalty. When enterprises are able to achieve this, personalization scenarios can be extended to practically any medium of conversation with cus-tomers—email campaigns, contact center conver-sations, and in-store connect among others.

Conclusion

The manifestation of personalization as an enter-prise-wide capability is no longer a distant dream for retailers. A unified view of customers and content can power the transformation to extreme personalization. To realize success, the transforma-tion should be governed by the following tenets:

• An enterprise-wide, common personalization vision aligned with the customer engagement strategy and the overall marketing plan

• Enterprise-wide data strategies such as gran-ular and real-time data ingestion layers for personalization

• Definition of progressive personalization dialogue services within the enterprise data constraints, relevant to customer context, which complement every customer commu-nication—email, customer accounts, and call centers

• A process design that aligns omni-channel operations with the comprehensive personali-zation approach

• Personalization platforms to allow configur-able business rules, which can be simulated against customer experience and organiza-tional goals

10


Gaurav leads the Retail Digital Domain team at Tata Consultancy Services. In this role, he works with retailers in US, Europe, APAC, & LATAM to shape and realize their digital transformation initiatives. He interacts with an eco-system of retailers, academia, and niche start-ups to re-imagine the digital customer value proposition, customer journey design, digital multipliers for stores, cross channel order orchestration, customer and associate mobility, omni-channel loyalty, and online operations services. He can be contacted at [email protected]

• A Test–Learn– Recalibrate–Test–Evolve cycle with no end state

Deep personalization offers an immense opportu-nity to counter the commoditization of retail. It is a race towards excellence where the customers have begun drawing the finish line. Every retailer will be pushed to get there, but those who take the lead in the right direction, on time, will derive maximum value.



12



Becoming truly customer-centric is at the top of every retailer’s agenda, as a result of both the changing nature of the customer as well as the re-tailer’s relationship with the customer. The modern customer is gadget-savvy—a social citizen always exploring to derive the best value across channels. Faced with rapidly eroding customer loyalty, retail-ers are scrambling to woo well-informed customers with innovative service offerings and personalized value deals. Today, it is common to see retailers diversify their business to span various areas such as general merchandise, electronics, grocery, fuel and automobile, financial services, entertainment,

and wireless services, to name a few. Likewise, re-tailers are now interacting with their customers through multiple channels such as in-store, direct mail, online, social, mobile, kiosks, and surveys. Cre-ating a unified view of the omni-channel custom-er is recognized as a fundamental pre-requisite for customer centricity and personalized engagement.

The traditional customer lifecycle that followed a sequential path is being replaced by a non-linear shopper journey spanning multiple touch-points, as shown in Figures 1 and 2. Customers interact with retailers across touch points for purpos-

Discover

Explore

Buy

Engage

Downloadapp

Blog

Like onFacebook

Postreviews

Viewbanner ad

ViewYouTube ad

Viewprint ad

Watch videoon mobile

Compare/shoponline

WatchYouTube ad

Watchtutorial

Readreviews

Purchasethrough

call center

Shoponline

Purchase viamobile

Purchasein store

Figure 1: Traditional customer lifecycle Figure 2: Digital customer lifecycle

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es ranging from product searches, information gathering, price comparisons, reviews, ratings, to purchases, and sharing feedback.

Most retailers have, over a period of time, built silos of customer data across brands/business units and channels, either as a result of acquisitions or because of customer engagement initiatives sponsored and executed independently. In or-der to detect patterns leading to a purchase and understand post-purchase behavior, retailers must not only identify each customer uniquely across interactions but also analyze the masses of data generated by various channels.

At the heart of creating a unified view of each customer is the capability to build a central reposi-tory of customers and prospects that integrates an ever-growing body of customer data and insights. Customer data comprises basic customer identifi-

cation information de-duplicated across their re-lationships, and their extended profile in terms of demographics, sociographics, and psychograph-ics. It is derived from linking the customer’s trans-action histories, interaction histories, and insights gleaned from across a retailer’s multiple brands or business units and channels. Customer data is also derived from the customer’s online and social media footprint, their context information and from syndicated data, as demonstrated in Figure 3. This unified view of the customer helps retail-ers streamline their business processes and make informed decisions to offer personalized services.

Innovations such as Big Data-based ‘listening’ and ‘sentiment mining’ now make it possible to read millions of conversations taking place simultane-ously across multiple online forums. For enhanced understanding of customer behavior, customer insights should be combined with the customer’s

Figure 3: 360-degree view of customer

SocialActivity

ShoppingBehavior

ShoppingHistory

f

SocioeconomicStatus

Drives aToyoto Lexus

Used to use apre-paid cell phone

Travels abroadtwice a year

Visits neighbor-hood store twicea month

Teenage daughterbuys fashion jwelleryonce a month

Redeemsloyalty points

Had searchedfor insurancebut did not buy

Returned ablender

Bought aSamsung LED TVand an iPad

Is actively talkingabout buyinginsurance

40 followerson Twitter

Over 300friends on Facebook

14


core profile. Insights can be generated from con-tact center transcripts and notes; blogs and other social media; surveys, news and other articles; complaints received via web forms; email, online forums, online chat sessions; and customer service notes and instant messaging logs.

‘Context’ Awareness

Another recent and very relevant layer of informa-tion available to retailers based on voluntary dis-closure is the customer ‘context’. When combined with an individual’s profile and behavior, ‘context’ provides a new and effective tool to enable accu-rate and relevant just-in-time steps to deliver the next best action, thus maximizing conversion.

An individual’s ‘context’ includes multiple dimen-sions, mentioned here in increasing order of matu-rity:

• Location (current latitude and longitude)

• Time (time of the day, week)

• Access type (device, browser, app)

• Proximity (shops and attractions, modes of transport, nearby people )

• Actions (searching, currently playing—music, video, games)

• Physiology (heart rate, emotion, or stress level)

• Environment (weather, temperature)

Generating Insights and Acting on Them

Harvesting useful insights from such a holistic knowledge repository opens new frontiers for customer engagement. A powerful set of analyti-cal tools built on top of this super-repository can help retailers infuse customer insights into their merchandising, marketing, eCommerce, mobile, social, and in-store business processes in several ways (refer Figure 4) such as:

• Running more accurate targeted marketing campaigns across channels or for micro-seg-ments to identify context-driven next-best-action

• Tracking a customer across brands and channels, reducing churn by establishing ‘reconnections’

• Leveraging customer insights-based local-ized assortments in-store, dynamic pricing, and customized promotions

• Proactively responding to life events such as ‘getting engaged’ or ‘relocating’, through tar-geted communications on relevant products and services

• Providing ‘right recommendation’ on new products based on current customer loca-tion—near a store or in an aisle

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Mobile

Personalized shopping toolsPredictive appsNoti�cations & alerts

Supply Chain

Marketing

AcquisitionCampaign modelingCross-format shoppingPersonalizationTargeted promotionsContext-driven next-best actionRetentionChannel optimizationSegmentation & pro�tablilityPreference management

Customer Service

Informed responseService di�erentiationProactive intervention

Location decisionsService di�erentiation

Labor deploymentFraud control

Loyalty tier movementService desk e�ciency

Layaway e�ciency

Stores

Online & Social

SSO & seamless omni-channel experiencePersonalization

Cross-format recommendationSentiment analysis

Forum & eventsReferral & complaint redressal

Social reputation management

Strati�ed replenishmentDemand forecasting

Planning & Merchandising

Macro-space optimizationLocalized assortmentOnline assortment optimizationDrive dynamic/EDLP pricingReal-time competitive pricingPrice simulation of new product launchClearance optimization

Segments

Decision tree

Trip dynamics

Context

Preference

Behavior

Sensitivity

In�uence

ShopperInsights

Figure 4: Infusing customer insights into business processes

16


Figure 5: Cross-channel customer analytics

Increasing Analytical Maturity

Increasing Analytic

al Matu

rity

Pro�leanalytics

Market basketanalytics

eCommerceanalytics

Supply chainanalyics

Interactionanalytics

Context-awareanalytics

Merchandising &Pricing analytics

Marketing &Loyalty analytics

Socialanalytics

Criteria-based segmentation

Cross-channelsegmentation

Goal-basedsegmentation

“Neo-segmentation”

n=1Personalization

Segment migrationanalytics

RecencyFrequency

Basket sizeA�nity-Product,Brand, Store,Channel

Paymentanalytics

Productlifecyclecorrelation

Tripanalytics

Anchoritem

Time factoranalysis

Consumerdecision tree

Lifestageanalysis

Pro�tability/CLTV

Spendforecasting

Cross-channelpurchasebehaviour

Retail frauddetection

Basket contractionanalytics

Time-to-eventforecasting

Consumptionanalytics

Mobile frauddetection

Tra�cClickstream

AbandonmentConversion

Consumerbrowse tree

Searchanalytics

Time-partinganalysis

Consumer-drivenonline Assortmentoptimization

Replenishmentstrati�cation

Survey responseanalytics

Voiceanalytics

Videoanalytics

Real timeemotiondetection

Locationanalytics

In-store path& sequence analytics

Tra�c andconversationanalytics

Active “needstate” and “trip-type” analytics

Real-timeeventdetection

Storedemographicpro�le

Pricesensitivity

Consumer-driven storeclustering

VoC forproductattributes

Price simulator Consumer-drivenassortmentoptimization

Consumer-drivenmacro-spaceoptimization

Test &learn

Sales driveranalytics

Propensityanalytics

Campaignresponseanalytics

Loyaltyfactoranalysis

Size ofwallet

Share ofwallet

Y-o-Y trendanalytics

Earn & Burnpatterns

Hazardmodelling

Channeloptimization

Next-best o�erengines

Churnmodelling

Activity analytics -Likes, Shares, Posts,Recomme-ndations

Friends &followers

Textmining

Sentimentanalytics

Reviews &rating impactanalysis

Personaclassi�cation

First-timeresolution

Servicelevel

Socialgraph

Socialin�uence

Social SoV

Viral lifetimevalue

Followervelocity

CrossChannelCustomerIntelligence

Figure 5 illustrates an analytical toolkit that can enable insight-driven actions, in the order of increasing maturity inside-out.

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Building a Customer Insights Repository

Over the last eight years, several retailers have embarked upon their customer engagement journey with the Customer Master Data Manage-ment (CMDM) platform, which establishes unique customer identities and holds relatively static customer profiles. The CMDM platform has been successfully integrated over time with operation-al systems such as CRM and Loyalty to facilitate better data integrity and segmentation. However, analytics on the data collected has continued to be relatively fragmented, with a heavier reliance on external shopper panels, customer surveys, or market demographic reports provided by syndicat-ed data companies.

Recently, there has been significant interest in expanding customer databases to make them

integrated analytical repositories that also hold relatively dynamic and derived information about customers (refer Figure 6). For example, integrated information may provide insights into a custom-er’s last three months’ purchase volume, loyalty points, product preferences, contact preferences, preferred store location, social influence, and so on. This enables the analytical use of more ac-curate granular-level individual, local, and more accurate data.

Retailers are increasingly building customer intel-ligence as an ‘internal capability’, reducing their dependency on externally procured analytics. This offers them more flexibility to slice and dice data for specific marketing, merchandising, pricing, or promotional strategies and events, while using ex-ternal data providers such as Experian™, GNIP, and DataSift selectively to enrich individual, house-hold, or demographic information.

Uni�ed Viewof Customer

Context Awareness

Social Activity

Interaction Linkage Purchase Behavior

Demographics & Sociographics

Customer Identity

Figure 6: Realizing the united view of customer

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The Privacy Predicament

An online survey conducted by Forrester on US marketing data collection reveals that consumer privacy concerns top the list of constraints impact-ing effective collection of consumer data amongst US companies.1

Creating and leveraging a unified view of custom-ers raises several questions regarding consumer data privacy and usage for various marketing initi-atives. Some of the leading questions are:

1. Is it ethical to use information provided by a customer in one context for purposes other than what it was sourced for?

2. Are insights used for purposes that benefit only the retailer or do they benefit the cus-tomer as well? Does the consumer see them as ‘relevant’ or as an ‘intrusion’?

3. Privacy awareness and laws are only becom-ing tighter by the day. In such circumstances, how do we obtain more voluntary customer information?

The rewards associated with managing consumer privacy responsibly include increased trust, con-sumer loyalty, and brand value enhancement. It is clear that retailers who take consumer privacy seriously with a view to build trust and a long-term relationship will be preferred by customers. A key recommendation on handling customer privacy responsibly is to treat customer insights

programs as opportunities to improve customer engagement practices at each point of interaction, conducted as parallel business process activities. Additionally, customer engagement programs should provide incentives to customers to disclose information at every point of interaction to create meaningful win-win scenarios. A privacy govern-ance council should be constituted and vested with the responsibility to develop consistent privacy policies and practices across the retailer’s business units.

Conclusion

Retailers no longer need evidence that a unified view for each customer is imperative for deeper customer engagement. The traditional approach is to build a formal Master Data Management system together with analytical data warehouses. The relatively new approach is to quickly build an analytical platform leveraging new data sources and technologies to accelerate business value. However, retailers must tread this path carefully, addressing customer privacy concerns effectively while leveraging customer insights to derive busi-ness benefits.

S. Janardhan leads Customer analytics and Big data domain practice for TCS’ Retail & CPG Industry unit. He works with TCS’ strategic customers on conceptualization & blueprinting of Customer centricity programs leveraging Digital technologies. Janardhan also works with TCS’ innovation labs on Big-data based solution development for Retail. He can be contacted at [email protected]

1Forrester research, US Interactive Marketing Data Collection Online Survey published August 2011, accessed November 2013



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Social media-driven 360-degree customer views can dramatically boost retail performance and keep customers loyal. In October 2013, Walmart Chief Marketing Officer Stephen Quinn an-nounced that the retailer was achieving a tenfold ROI on its Facebook and Twitter investments com-pared to its return on other advertising spends.1 Walmart has invested hundreds of millions on so-cial media, including the acquisition of four social media companies.2 Such spending and returns, however, are far from the norm.

Lack of investment is not the culprit. In our study, retailer social media investments ranked second out of 11 industries that provide consumer prod-ucts and services, surpassed only by consumer packaged goods.. The average retail company spent $25.3 million last year on social media, com-pared to $18.8 million per company across all 11 consumer industries. (Exhibit 1).

In our 2013 global research study on how large companies, including 87

retailers, were using social media, we found that less than half of retailers

generated a positive ROI on their social media efforts.

Based on a survey of 650 consumer company executives conducted as part of the TCS Global Trend Study titled ‘Mastering Digital Feedback’ on how companies are using social media

1Christopher Heine: Walmart’s Social is Getting 10X ROI and Tens of Thousands of Daily Interactions. Adweek, October 4, 3013. http://www.adweek.com/news/technology/walmarts-social-getting-10x-roi-and-tens-thousands-daily-interactions-1529122Rachael King: Walmart, GE Move Close to Nab Silicon Valley Tech Talent. The Wall Street Journal, June 25, 2013. http://blogs.wsj.com/cio/2013/06/25/wal-mart-ge-move-close-to-nab-silicon-valley-tech-talent/

0.915.5

1.023.0

1.1

1.9

1.3

3.5

1.4

1.4

1.7

0.2

4.1

1.2

19.6

19.2

24.2

21.8

17.2

25.3

20.1

3.3

26.9

18.8

5

1

2

2

0 5 10 15 20 25

Banking/FinancialServices

Consumer PachagedGoods

Health Care Servicesand Products

High Tehnology

Insurance

Media andEntertainment

Manufacturing

Retail

Telecom Servicesand Equipment

Travel/Hospitality/Airlines

Utilities

Total

Global Industries: Average 2013 Spending per Respondent on Social Media and Spending per $1 Billion

in Average Respondent Revenue (in US $Million)

2013 Social Media Spending ($millions per $1 billion revenue)

2013 Social Media Spending

Exhibit 1: Global Consumer Industries Social Media Spending

21


Retailers also deploy significant numbers of full-time employees on their social media efforts—an average of 53 (and a median of 18). (Exhibit 2) Moreover, retailers say they plan to increase their social media spends to an average of $30.6 million annually by 2015—second only to consumer pack-aged goods manufacturers.

Instead, a narrow focus of social media on market-ing and service is the major reason for most retail-ers’ lackluster social media ROI. Our study found that, far more than any other functions, market-ing, service and sales, regularly follow consumers on social media—69 percent, 63 percent and 59 percent respectively. (Exhibit 3) Only 30 percent of brand/category managers say they do. Among respondents from product development and dis-tribution, the numbers are even lower—21 percent and 15 percent.

This is not to say that diligent use of social media in marketing and customer service isn’t critical to retail success. With intense competition, especial-ly on price, retailers are on the mark when they use all the tools at their disposal to reach consum-ers with targeted offers. The same can be said about customer service after the sale. Large num-bers of consumers are dissatisfied with their retail experiences and complain through social media.

According to a 2013 study by Arizona State Uni-versity’s Carey School of Business, for example, more than 50 percent of U.S. consumers weren’t satisfied with the products they purchased or the service provided by retailers during the past 12 months. According to the report, the number of dissatisfied consumers has been on the rise—from 32 percent in 1976 to 45 percent in 2011. In ad-dition, more than half (56 percent) of consumers who complained about retailers claimed that the

5921

53

61

63

42

49

102

53

61

54

28

19

15

24

11

18

48

18

20

17

15

2

3

2

0 20 40 60 80 100


Consumer PackagedGoods


High Tech

Insurance

Manufacturing


Retail

Telecomm Servicesand Equipments


Utilities

Global Industries: Mean and Median Number of Employees Working Full-Time on Social Media Activities

Mean Employees Median Employees

Exhibit 2: Mean and Median Number of Full-Time Employees on Social Media Activities

69%

63%

59%

30%

25%

25%

22%

21%

15%

14%

7%

6%

5

5

%

0% 20% 40% 60% 80%

Marketing (includingProduct/Brand management/

Social Media Marketing etc.)

Customer Service (inclu-ding call centers, social)

Sales (including head-quaters and �eld sales)Product Management

(Product Brand Managers/Brand Strategists etc.)

HR

InformationTechnology (IT)

Product manufacturing/service

Research/Product Engineering& Development etc.

Distribution/logistics

Legal (compliance, etc)

Risk management

Finance/accounting

Retail: Which Business Functions Use Social Media Regularly to View Consumer Comments

Exhibit 3: Business Functions Use of Social Media

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companies did nothing about their issue—an increase of nine percentage points from two years ago. Additionally, the number of consumers that complain via social networks has nearly doubled from 19 percent in 2011 to 35 percent in 2013.3 The Arizona State University study found that dissatisfied customers complain to an average of 28 people—about double the number that would have complained if the retailer had resolved the problem.4

Although social media is critical to marketing and customer service success, it also offers retailers an unprecedented opportunity beyond market-ing and service to create differentiated customer experiences. These can include better merchan-dising, assortments, products, and cross-channel experiences. To do so, retailers need to ‘listen’ to customers and create a social-media-driven 360-degree view of them. In this article, we ex-plore the value that this view can provide and how retailers can generate greater value from social media across their operations, stores and online venues.

Beyond Marketing

Building a 360-degree customer view requires more than transaction history. It includes cus-tomer attitudes, expectations, experiences and product needs—most of which can be gleaned from the remarks consumers make about retailers in social media. In fact, four attributes make social media the best medium for tracking consumer needs and wants—the volume of consumer com-

ments social media generates, the permanence of those comments, their unvarnished quality, and the ability to measure comments.

Social media is spawning enormous volumes of consumer comments. It’s essentially a huge and never-ending focus group session. Most retail-ers conduct episodic focus group sessions with consumers; social media provides a focus group 24x7, with many more consumers. Additionally, these comments are permanent—they remain ready to be collected and analyzed on the Inter-net. Social media comments come directly from consumers—that is, they’re unfiltered—unlike the comments that consumers make about retailers in their stores that either don’t make their way up to the top management or are heavily edited (espe-cially if negative). Finally, all these social media comments can be categorized through sentiment analysis and other software and counted. That makes consumer feedback through social media measurable. When feedback is measurable (espe-cially if it’s coming from hundreds or thousands of consumers), it’s much harder to be discounted and ignored.

Social media data is especially important for high-value customers who represent the lion’s share of retailer’s profit and are expensive to acquire. Yet 75 percent of companies don’t know where exactly their most valuable online custom-ers are congregating and talking about them.5

However, some retailers do know and are using so-cial media to deepen customer relationships with more than marketing offers. For example, in 2013

3E. Holmes, “Shopping Dissatisfaction Is on the Rise But Savvy Complaints Get Attention,” The Wall Street Journal, Dec. 18, 2013. Arizona State Uni-versity surveyed about 1,000 households.4Arizona State University’s Carey School of Business press release, November 26, 2013. http://wpcarey.asu.edu/news-releases/2013-11-26/new-customer-rage-study-out-holiday-shopping-season5The Next Conversation: Taking Social Media from Thought to Action. Harvard Business Review Analytic Services Report, December 2010

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UK supermarket giant Tesco launched the world’s first ‘socially created’ wine. Members of its social media community were invited to become tasters of proposed wines—Shiraz and Chardonnay. Tesco also received hundreds of suggestions for the wine brand’s potential name and bottle style.6

Crowdsourcing new ideas can deepen relation-ships with customers and can provide a steady stream of new ideas with strong business im-pact. Often, that stream of ideas can yield more powerful results than surveys or other traditional research. In 2007, for instance, Dell Inc. launched IdeaStorm, an online community where customers could post product ideas and vote for them. Since its launch, IdeaStorm has generated more than 15,000 ideas and the company has implemented more than 500, ranging from a Linux-based oper-ating system to providing customer support in the languages Dell customers speak.7 Similarly, in 2008, Starbucks launched Mystarbucks.com and invited its customers to share ideas on the portal. The site has generated more than 150,000 suggestions. A number of highly profitable ideas emerged from the effort, including equipping stores with Wi-Fi, providing digital rewards on Starbucks Cards, and offering lower-calorie beverages.8

Social media is also playing an increasingly im-portant role in managing and understanding the service experience. Social media can also be a more cost-effective channel than call centers to resolve complaints, and customers are increasingly expecting to be able to conduct more business on-

line. When a retailer uses social media to resolve complaints, it not only creates a positive impres-sion with that customer, it boosts its image with the customer’s social circle. That creates a domino effect.

Leading retailers are turning to social media to drive sales once customers are in stores. Using mo-bile features such as scanning QR (quick response) codes and short-range wireless communication capabilities, retailers are pursuing ‘social shop-ping’. Walmart’s Shoppycat, for example, advises consumers on gifts based on their friend’s social media posts. Starbucks rewards customers when they check into stores with Foursquare. Clothing retailer Gap shows the number of Facebook ‘Likes’ on selected garments in its stores. The 440-store, UK-based fashion chain Topshop partnered with Pinterest to encourage shoppers to pin their favorite products on the retailer’s web site to their own Pinterest pages. The chain also installed giant touchscreens in its flagship stores so customers could discover the items most popular on social media.

Online reviews and rankings are growing in im-portance. They can have significant impact on customer purchase decisions and a retailer’s reputation. As Jamie Nordstrom, president of the online business of $12 billion U.S.-based depart-ment store chain Nordstrom, put it: “We built our business based on word of mouth. Social media is that same word of mouth on steroids”.9

6“Tesco Redefines Social Drinking With Community-Created Wine,” by Emma Hall, Advertising Age, June 30, 2013. http://adage.com/article/global-news/tesco-asks-followers-create-social-wine/242850/7Shel Isreal: Dell Modernizes IdeaStorm. Forbes, March 27, 2012. http://www.forbes.com/sites/shelisrael/2012/03/27/dell-modernizes-ideastorm/8Starbucks press release, March 29, 2013.http://www.businesswire.com/news/home/20130328006372/en/Starbucks-Celebrates-Five-Year-Anniversary-Starbucks-Idea9Joe McCarthy: Nordstrom Direct President: Social Media is Word of Mouth on Steroids. Luxury Daily, November 8, 2013. http://www.luxurydaily.com/its-not-about-channels-nordstrom-direct-president/

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Building and Acting on a 360-Degree View

To deploy a 360-degree customer view across the organization, retail companies need to adopt spe-cialized social media tools and integrate them with other customer processes and systems, including campaign management, retail analytics, CRM and business intelligence.

Sentiment analysis is an important social media tool. It analyzes and interprets the positive or negative tone of online comments by applying complex scoring systems to the words or phras-es consumers are using when they talk about a product, company or brand. Sentiment analysis also leverages machine learning to build an ongo-ing understanding of how language is changing in light of communication standards such the 140-character limits on Twitter. Sentiment analysis can help companies rapidly understand how they stack up against competitors and can and prioritize incidents and route them to the right employees for immediate action.

Social media analytics are also a big part of the equation and should be merged with customer and store analytics to enable ongoing testing and learning. Social media should be integrated into the retailer’s CRM system and can enrich customer data models. There are three elements to a rich data model:

• Core and extended demographic attributes (e.g., name, gender, income, region and oth-ers that predict buying behavior

• Transactions (purchases, store visits, website clicks, etc.)

• Interactions (social media comments, call center and website chat interchanges, etc.)

This data can offer a wellspring of insights to dif-ferent retail functions: e.g., how marketing should personalize product recommendations; how call center executives should converse with phone customers; and for store personnel, the buying preferences of high-value customers.

Breaking Down Silos

To create a social-media-driven, 360-degree cus-tomer view, all functions in a retail company need to share customer social media data. However, social media is often housed in silos, which can hamper, even thwart, its enterprise use. According to our study, only 23 percent of retailers manage social media with a highly cross-functional ap-proach—four or more functions working closely together. A greater percentage—more than 30 percent—manage social within a single function.

To knock down the walls, retail organizations should create and/or revise the company’s social media strategy to encompass multiple functions. The broader the strategic ambit and accountabil-ity for social media, the more individual units will get involved. If the strategy is too narrow, such as only a marketing focus, individual functions may hoard social media data. For example, if custom-er service doesn’t share social data that reveals a problem with a particular product’s packaging, buying executives won’t be able to work with manufactures to resolve the issue. In addition, different parts of the organization may interpret social media data differently.

Silos also inhibit the sharing of best practices. Because social media is a relatively new phenom-ena that is growing quickly, managing it is much more art than science. Since there aren’t decades of best practices to follow, companies that want

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to beat competitors must consistently share their lessons learned across the organization.

Organizing for Social Media Impact

In our study, only 40 percent of retailers said their organizational structure for social media work was effective or highly effective. More than half plan to reorganize how they manage social media by the end of 2014.

Forty-five percent of respondents say their com-panies centralize social media within marketing. Social media efforts driven primarily by marketing can narrow its focus to marketing objectives, such as generating store traffic. To achieve greatest impact across the organization, retailers should establish a centralized social media group led by a non-functional executive, such as chief digital or customer experience officer, to create a collabora-

tive inner social circle. However, only 9 percent of respondents say that social media reports to such an executive. (See Exhibits 4 and 5)

When any one function controls social media activities, it can be difficult to establish an inner social circle where multiple functions collaborate. Without this collaboration, retailers won’t be able to turn continuous shopper feedback into rapid adjustments to store layout, merchandising, prod-uct assortment, marketing campaigns and service policies. Instead, we recommend that retailers cre-ate one big ‘social circle’—a group reporting to the top of the organization that has representatives from across functional areas and which is charged with collecting and analyzing social media data. (See Exhibit 6)

8%

9%

6%

4%

7%

6%

23%

6%

3%

10%

10%

%

7

%

%

0% 05% 10% 15% 20% 25%




High Tech

Insurance

Manufacturing


Retail

Telecomm Services andEquipment


Utilities

A Chief Digital O�cer: Which Function or Person Controls Your Company’s Social Media Activities

Exhibit 4: Which function controls Social Media activities?

7%

2%

4%

10%

10%

9%

0%

3%

0%

10%

10%

%

%

0% 4%2% 6% 8% 10% 12%




High Tech

Insurance

Manufacturing


Retail

Telecomm Services andEquipment


Utilities

A Chief Customer Experience O�cer: Which Function or Person Controls Your Company’s Social Media Activities

Exhibit 5: Which function controls Social Media activities?

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Walmart is a case in point. In 2011, it formed @Wal-martLabs as part of its ecommerce division. The cross-functional group is charged with integrating the company’s stores, e-commerce site and mobile channels. @WalmartLabs is based in Silicon Valley with a second office some 30 miles away. Walmart has found cross-functional teams to be critical to its success with social media. For example, in 2013 industry data and company forecasts projected lackluster back-to-school sales. With only 14 days to go before the beginning of the season, @Wal-martLabs created a ‘strike force’ with ecommerce and PR to stage a one day sale to stimulate back-to-school sales.10

To build impact and organizational acceptance, a centralized social media group should evolve over time. In its first phase, the group can be organized as a service organization that supports marketing, sales, store operations and the service organiza-

tion. During the second phase, the digital role takes the helm and supervises and aligns those functions.

Speed Bumps in the Road

Social media is speeding the clock which presents a number of obstacles to achieving its full poten-tial. Retailers must manage outsized volumes of data while building the capability to quickly seize sales opportunities and meet consumer expec-tations of 24/7 availability. Retailers must also be able to provide a steady flow of fresh content, incentives and perks to cultivate a rapidly growing number of one-to-one customer relationships. Retailers must also be able to separate the wheat from chafe. Given the sheer volume of social media content, companies must have a strategy to ignore ‘noise’—social media comments that

Central SocialMedia Group

CorporateLevel

Manufact-uring

MarketResearch

R&D

SalesCustomerService

MarketingProduct

Management

Role in Social Media

Collect Analyze Direct (issues to the right functions/level of �rm)

Analyze further Act (on issues that need immediate response)

Weigh and act on issues of larger magnitude - Broad reputations attacks - Major Resource investments - Etc.

Exhibit 6: Implementing a Large Internal Social Circle

10Walmart blog post: http://walmartlabs.blogspot.com/2013/10/walmarts-back-to-class-cyber-monday-new.html

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are not relevant to them. The pervasive noise also makes it difficult for retailer messages to rise above the clutter. Companies must arm their teams with technology that makes social interactions respon-sive, intelligent and relevant for all stakeholders. Finally, culture can be a significant obstacle. Retail organizations must cultivate cultures that respect consumer opinion. In our survey, we asked re-spondents to rate key success drivers to achieve benefits from social media. Having a company culture that strongly values consumers’ opinions about products and practices was among the most important.

Conclusion

Retailers such as Walmart and Tesco show that social media is far more than a marketing tool, although the marketing benefits of social media alone are more than enough to justify the invest-ment. Social media provides retailers with an unprecedented tool to collect and act on customer feedback—to create new products, identify neces-sary changes to service policies, and all in all, keep one’s best customers loyal.

However, harnessing social media requires that retailers combine the data that it generates with other data that they’ve had for years about their customers. Even more so, it demands that retailers build a big internal ‘social circle’—a centralized group that analyzes the data and determines what actions should be taken by the relevant business functions. That, in turn, demands a culture that places customer input on a pedestal, and thus makes it easy for retail executives to listen and act on the treasure trove of customer data that they can now tap through social media.

Harshdeep, Retail Digital Consultant, works with leading global retailers to explore social media and re-im-agine their digital eco-system for better customer engagement. His responsibilities include conceptualizing and developing retail solutions around social media, customer journey design, and customer and associate mobility. He can be contacted at [email protected]

Gaurav leads the Retail Digital Domain team at Tata Consultancy Services. In this role, he works with retailers in US, Europe, APAC, & LATAM to shape and realize their digital transformation initiatives. He interacts with an eco-system of retailers, academia, and niche start-ups to re-imagine the digital customer value proposition, customer journey design, digital multipliers for stores, cross channel order orchestration, customer and associate mobility, omni-channel loyalty, and online operations services. He can be contacted at [email protected]



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This is a fitting statement on the rapid commod-itization in the retail industry. Commoditization and consumerization have made the seemingly simple, yet incredibly difficult-to-master, game of customer experience a necessity to outpace com-petition. For consumers, the cost of switching to a competitor has never been lower. It is clear that customer loyalty is eroding—be it the elimination of multi-year contracts for wireless phone or cable providers, the minimal effort required to switch from one retail bank to another, or the ability to buy any product, anytime, anywhere at the lowest price.

Customers do not give a second thought about switching to a competitor if they can find better pricing or perceive that they can receive better service elsewhere. The competitive landscape is also changing rapidly with new, innovative, and fast moving competitors constantly entering the market. In addition, with the rise of social media and mobile devices, retailers have little control over customer conversations or their physical context. Retailers can choose to engage in social conversations to their benefit, but the conversa-tion will go on, with or without them. Retailers can optimize store layouts and displays but they cannot stop mobile comparison shopping. The

only differentiator that can work as a solution is an exceptional customer experience (CX).

However, while many retailers have started fo-cusing on customer experience, they often miss out on customer loyalty, a critical component of a CX strategy. Rather than deliver an omni-chan-nel customer experience, retailers adopt a siloed approach and loyalty is treated as a set of incen-tives offered as a separate program, only em-ployed after the first sale. In fact, long-term loyalty should be the outcome and vision of a dynamic CX strategy that draws the customer experience into a synergistic whole, cutting through siloed functional and channel behavior. Retailers should design loyalty for specific customer segments and sub-segments and must embed it into the cus-tomer experience. The benefits of this approach include:

• Enhancing the overall customer experience

• Increasing purchase size

• Accelerating purchase cycles

• Ensuring completed purchases

These benefits when combined with social media, amplify the loyalty effect and value.

Gaining Deep Insights into Customer Segments

Designing and executing a compelling Customer Loyalty Experience (CLX) strategy requires a deep

“All we have left is customer experience.” - A representative from a consumer company

at the 2013 Social Media Shake-up conference, Atlanta, GA.

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understanding of customer segments and sub-seg-ments. Using an ‘insight-to-outcome’ design approach will help define the data and focus the analytical methods to generate actionable insights and offer a superior customer loyalty experience. With long term loyalty as a defined outcome, re-tailers need to tune data collection and analytics to uncover critical loyalty drivers as customers move through different stages in the customer experi-ence lifecycle across multiple touch points. It is possible to even uncover new segments based on loyalty characteristics. Following are a few of the loyalty drivers one should look for:

• Intrinsic and extrinsic drivers of customer behavior

• Loyalty triggers

• Attachment criteria

• The right rewards for each segment

Figure 1 illustrates how new insights from social and unstructured data, when used in combination with conventional data sources, help create a com-plete customer profile.

Using Social Insight to Identify Action and Loyalty Drivers

For most retailers, social media data and analy-sis is limited to the marketing department using this data to measure the share of voice and spot keyword trends and issues. As a result, other departments such as sales, support, and product management, miss the opportunity to capture insights that would enable them to have a greater impact on the CLX. Using social and unstructured data can help identify customer behavior such as loyalty and reward drivers, the channels used by various segments, and the games customer seg-ments prefer to play. All these are critical insights that will help define the CLX programs.

For example, in a recent CX engagement with a large retailer, we learnt that a significant portion of their target segment comprised savvy-shopper moms with children under the age of thirteen. This segment tends to seek loyalty programs that offer discounts for future purchases and uses feature phones rather than costlier smart phones. Without this knowledge, gleaned from social insights, it might have seemed logical to develop a mobile application that encourages social sharing with other moms. That strategy would have failed with this important target segment. Instead, we designed programs around text messages with coupons and discounts, which generated a favora-ble response.

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ts

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es

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ata

Focus Groups

NPS Reports

Surveys

Surveys

Research

Analysts

TranscriptsCall Center

CRM

ERP

Uns

truc

ture

d D

ata

Customer

Internal Data

Third Party Data

Figure 1: Sample data sources for customer insights

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Customer Loyalty Experience: Aiming for the Right Fit

After obtaining a deep understanding of the customer segments, and the key loyalty and engagement drivers, retailers tend to believe that they are ready to identify programs that will deliver a superior CX, translating into long-term loyalty. While retailers might find it tempting to brainstorm a host of programs that seem like sure winners, they might not deliver the value and loyalty, nor align with the drivers and behaviors that customers exhibit. It is also important to avoid copying the competition with the belief that their CLX programs are backed by extensive research. For instance, most companies build mobile apps not because their customers want it but because the competition already has one.

Retailers need to begin by defining the desired CLX outcomes and associated KPIs. This will ensure that the CLX programs are aligned with their goals and progress can be measured through defined KPIs. Next, retailers need to identify the loyalty drivers and behaviors uncovered from the custom-er insight processes that will deliver the desired outcomes for each step in the CX lifecycle—from the first touch point through purchase and re-pur-chase. This includes identifying the appropriate channels—in-store, mobile, web—and contexts to avoid forcing customers into a channel they do not engage with.

The end result of the ‘incentive to outcome’ pro-cess (refer Figure 2) is a clearly defined CX map that includes a complete view of customer seg-ments, desired channels, loyalty drivers, target outcomes and KPIs, and programs to deliver an exceptional customer experience.

Calculating the Costs, Priorities, and Return on Customer Experi-ence

When retailers have a deep understanding of customer segments and their loyalty drivers, they might believe that the CLX programs they have identified are good enough to be implemented right away.

However, many of the CLX programs that retailers identify might be great for top-line revenue, but implementing and supporting them could be cost-prohibitive. It might require a paradigm shift in how the staff engages with customers, requir-ing a large training effort, reorganization, or hiring new staff. Not all changes to the CX translate into a proportional level of value to customers or the business. A sustainable CLX needs to deliver real and lasting value to customers and must be prof-itable.

1Loyaltyoutcomes &KPIs

$2Drivers &behaviors 3

Engagementchannel/context

4Incentives& rewards

Loyalty -Incentive design

Assessment -Behavior/DriverassessmentAction to Outcomes -

Outcome mapping

Figure 2: Incentive to Outcome process

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A Return on Customer Experience (RoCx) analysis will help retailers identify the programs that create a win-win situation for customers and business alike, and will help prioritize the programs they should pursue first. To conduct a RoCx analysis retailers need to:

1. Identify and weigh the scoring criteria. These criteria may include cost, competitive differ-entiation, time or complexity to implement and innovation among others.

2. Score each of the CLX programs against the value it will bring to the business and cus-tomers (refer Figure 3).

The result will be a clearly defined set of programs with a greater promise of success and Return on Investment (ROI).

Conclusion

To survive and thrive in today’s hyper-competitive retail market, retailers must provide an exception-al customer experience that will ensure customers keep coming back regardless of competitive influ-ences. Designing a Customer Loyalty Experience will not only help retailers identify programs that deliver long term value for customers and gener-ate a positive ROI for their business, it will also give them customer insights that would have other-wise gone unnoticed.

CLXProgram

Touc

hpoi

nts

RetailChannels

Value of theCLX program

to thecustomer

Value of theCLX program

to theretailer

RoCxScore

Cost of processes/process change

Cost of sta�,training,re-organisation

Cost of technologyand insight

Cost of rewards(discount, points,badge)

f

Figure 3: Return on Customer Experience (RoCx) Analysis

Tonya McKinney leads TATA Consultancy Services’ Digital Strategy Consulting and Solutions capability. Ms. McKinney has spent more than a decade innovating and executing integrated, digital marketing practices and programs at companies such as Computer Associates, SBC, and Siebel. She has worked with organizations and firms that were first in their space to introduce and execute social strategies and has helped organizations inno-vate, develop, and deliver digital/social offerings to the market place.

Bill Quinn is a member of TATA Consultancy Services’ Digital Strategy and Solutions team. Mr. Quinn has spent 14 years working in venture-backed technology companies developing bleeding edge solutions in website performance monitoring, testing and change control solutions for ERP applications, and crowdsourced digital advertising. Bill has led product management and marketing teams in the development and execution of met-rics-driven product roadmap and digital marketing programs.


Unified View of Customer: It’s All About Customer ExperienceRealizing Unified View for Better CustomerEngagement: Understanding What to Build

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Realizing Unified View for Better CustomerEngagement: Understanding What to Build

Obtaining a ‘unified view of the customer’ is the new collective focus for retailers. Many retailers have Loyalty and CRM databases which exist in silos in the enterprise. However, retailers are still undecided when it comes to choosing an optimal data management platform for handling volu-minous customer data and real-time analytics. A common thread of thought amongst retailers is figuring out whether to invest in a formal Cus-tomer Master Data Management (CMDM) suite or to build/buy an alternate ‘Customer 360-degree repository’ purpose-built for analytics. To under-stand this better, it is important to compare the capabilities of MDM solutions and a 360-degree customer analytical repository.

Capability differences: CMDM vs. Customer Analytical Repository

Figure 1 illustrates the typical capabilities of CMDM solutions, compared with the additional capabilities that an analytical repository is intend-ed to address.

Based on Figure 1, a few key observations that stand out are:

• For a 360-degree customer analytical repos-itory to be effective, it needs several foun-dational capabilities that are inherently part of typical CMDM solutions. Hence, there is significant overlap in the capabilities of both technologies.

• With customer engagement increasingly go-ing digital, a CMDM implementation cannot be successful without tracking the multi-di-mensional relationships between a customer and the retailer.

CMDM solutions have matured significantly in the last decade, with respect to underlying data models, user interfaces of customer systems, and services to consume or update the master data.

Figure 1: Capability comparison: CMDM vs Analytical Repository

Advanced matching and survivorship

Integration withcustomer

operationalsystems

Historicaldata

capture

Transactionlinkage

Interactionlinkage

Intergration withcustomer

analytics system

Mobility activitylinkage

Contextlinkage

Aggregated analytical attributes

Implicitpreferences

Social activitylinkage

Customerdata governance

Customer-retailerrelationships

Customer pro�leattributes

Identityresolution

Consumer dataServices

Aggregatedrelationship

measures

Data cleansing& data quality

management

Explicitpreferences

Metadatamanagement

Security & role-based access

3600 CustomerAnalytical Repository

(Pure analytical capability)

CMDM(Pure MDM capabililty)

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360-degree customer analytical repositories are an emerging trend, with companies offering ready-to-deploy Big Data-enabled solutions that can be used to create a 360-degree view of the customer. The capability differences can be understood from the following two dimensions that relate to the way such customer data systems are built and used in the current context:

Customer data creation and consumption In medium-to-large size retail organizations, formal CMDM installations service multiple operational processes such as Loyalty, CRM, online user reg-istrations, mobile registrations, Layaways, and so on, in real-time as well as offline mode. Trans-action-style MDM implementations involve the orchestration of business processes between the operational systems and the CMDM solution to achieve a specific outcome such as new user regis-tration. On the other hand, 360-degree customer analytical repositories are evolving with respect to hard-ware, software, and the nature of workloads they handle. Hadoop-based systems have traditionally supported high volume analytical processing and are maturing with respect to handling high volume individual read and write transactions such as those originating from a new customer registration or change in the customer profile information. Pro-prietary Big Data vendor products and in-memory appliances have started addressing these capabili-ties well.

Customer Data Management

• Identity resolution: Leading CMDM solutions now bring a high degree of maturity with regard to identity resolution, and they even cater to industry-specific needs. However,

most lack the ability to identify individuals outside of enterprise applications, such as social media interactions—an area that 360-degree customer analytical solutions actively explore within the boundaries of customer privacy and consent.

• Governance and data quality: CMDM systems have been built to formally govern data including data quality tools, coun-try-based address and name standardization and stewardship functions. However, this is not necessarily an out-of-the-box function delivered by leading 360-degree customer solutions.

• Analytical data capture: 360-degree cus-tomer analytical solution implementations have a sharper focus on the omni-channel customer, and are constantly aggregating cross-channel metrics on purchases, web and in-store activity, social activity, response to communications and individualized pref-erences.

Overall, the focus is more on psychographic than on the demographic and sociographic aspects.

• Data consumption: Formal CMDM solutions provide a fine-grained set of data services that can be knitted together into coarse-grained functions, but these are generally re-stricted to reading and managing customer records. Analytical repositories, on the other hand, need to deliver a richer set of services that publish analytical metrics about the cus-tomer, perform analytical functions or create target lists, and allow end-users to slice and dice data to analyze what-if scenarios.

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Realizing Unified View of the Customer: Is MDM a prerequisite?

The question “Can I implement a unified view of the customer (UVC) without an MDM?” can be interpret-ed in two ways:

Can I implement a UVC without an MDM discipline?

It is clear by now that the fundamental capabilities required for customer data management are a prerequisite for implementing UVC. No UVC imple-mentation can afford to ignore them, although the level of sophistication may vary.

Can I implement a UVC without a formal MDM solution?

Basic customer data integration can be a starting point to achieve a universal view of the customer. An implementation without a formal MDM solu-tion can be a starting point to achieve customer data consolidation without the sophisticated capabilities of a formal MDM solution. Howev-er, the retailer must have access to a basic set of data management tools for quality management, de-duping or identity resolution, metadata man-agement, data integration, and to persist changes to customer data.

Capabilities such as source data history and black-lists or watch lists will have to be custom-built into the data repository.Over time, retailers can migrate the ‘master’ part of the repository into a formal MDM solution when the need and business case are established.

Conclusion

The growing demand for Omni-channel custom-er information and real-time customer analytics at ‘points of presence’ is introducing significant change to the architecture of customer data hubs. The need to author customer data anywhere, anytime and deliver real-time personalized com-munications across channels consistently requires customer data hubs to cater to a wide variety of workloads. This requires a shift from traditional customer data platforms to newer ‘Big Data cus-tomer repositories’ co-existing with high-response data platforms. Creating a robust realization plan for a unified view of the customer involves a care-ful study of the business purpose, corresponding benefits, and workloads. The architecture data model design and technology considerations are closely linked with each other and are bound to evolve over a period of time. Inadequate planning upfront can result in several challenges, ranging from business disinterest due to the lack of per-ceived benefits, re-work, or even the inability of the solution to scale up to meet desired work-loads.

Retailers who want to quickly leverage customer information for analytical purposes can start with the creation of an analytical repository by using basic customer data consolidation infrastructure such as data matching and quality management.However, the long-term roadmap needs to include the development of a more formal MDM discipline combined with analytical usage. This solution should have the capability to serve multiple user bases and consumption patterns in a scalable manner while preserving data integrity.

S. Janardhan leads Customer analytics and Big data domain practice for TCS’ Retail & CPG Industry unit. He works with TCS’ strategic customers on conceptualization & blueprinting of Customer centricity programs leveraging Digital technologies. Janardhan also works with TCS’ innovation labs on Big-data based solution development for Retail. He can be contacted at [email protected]

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InFocus

TCS showcased ‘Re-Imagining Retail’ Solutions at NRF 2014

TCS participated in NRF 2014, held on January 13th and 14th. More than 300 visitors from top retail companies visited the TCS booths.

TCS Retail solutions were demonstrated to visitors. Over 70 delegates showed interest in our solutions and saw the solution demos.

TCS’ Innovative Products for Retailers at the NRF Booth #1401

• My Home IoT/Interactive Campaigns: Man-age, monitor, and get personal shopping assistance.

• Immersive Shopping/3D Store using Leap Motion: Experience online shopping through personalized 3D Heads Up Display (HUD).

• AR Navigator: Provides shoppers special promotions and interesting product/catego-ry details through a TCS smartphone app.

• Peri Vista: Obtain a 360 degree view of the customer by integrating enterprise data

• Google Glass: Enhance the customer’s shop-ping experience.

• Orchestrated Commerce : Supports both B2B & B2C scenarios.

• Optumera : Shopper-centric Merchandise Optimization Suite

• POS/mPOS/cPOS: Point of Sale (POS) solu-tion ready for cross-channel sophistication and rapid implementation

TCS

NEWS RACK

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• Store Power: Store empowerment through an iPad application that store managers can leverage on the store floor

• Shoppable Window: Engage customers and enable shopping on a closed store window.

In addition to our booth presence, we were the premier sponsors of the Big CIO Party (co-spon-sored with SAP) and the Retail Insiders Party (where we were one of several sponsors).

We met 300 and 250 CIO level connects respective-ly, at each of these events. We also hosted a dinner at Lambs Club for 40 of our clients.

TCS participates in World Retail Congress, LATAM

TCS Latin America participated as a co-sponsor in the World Retail Congress (WRC) held in Sao Paulo, Brazil, from Oct 31 to Nov 1, 2013. This was the first time that WRC was being held in Latin America

where the economy is growing at 4% and the ge-ography has an optimistic outlook for retailing. Over 300 delegates participated in this event. Busi-ness leaders from retailers such as Spar Interna-tional, NetShoes, Mango, Walmart Brazil, Grupo Pão

de Açúcar, and Procter & Gamble discussed retail challenges, shared best practices, and provided strategic business insights.

Mr. Ankur Prakash, EVP, TCS Latam, made a pres-entation on omnichannel retailing and participat-ed in a panel discussion with Mr. Gordon Camp-bell, CEO, SPAR; and Mr. Flávio Dias, e-commerce Vice-president, Wal-Mart Brazil. This session ex-plored the opportunities and challenges of inte-grating omnichannel retailing in Latin America.

TCS Co-innovation Network Update

TCS Co-Innovation Network (COIN™) is a rich and diverse ecosystem that connects us, our custom-ers, and entities including venture capitalists, trade bodies, start-up companies, strategic alli-ance partners, and academic and research insti-tutions. The common goal binding all the entities is to build and nurture collaborative innovation that enables you to stay ahead of the curve. In this issue, we present two of TCS’ COIN partners—Clar-abridge and iKEN—engaged in delivering inno-vative solutions that address real world business challenges.

Clarabridge - Intelligent Customer Experience Management

Clarabridge is the industry-leading intelligent Customer Experience Management (CEM) solution that harnesses all available sources of consumer feedback generated during the customer jour-ney. Facts and context, sentiment and emotion are monitored, measured and routed to the right audience at the right time. With out-of-the-box templates and reports, retailers can get actionable insights from day one and increase revenues, de-crease costs, and centrally manage the customer experience.

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• Clarabridge Analyze enables customer expe-rience analysts and administrators to not only listen to all sources of customer feedback, but to also understand it to obtain a holistic view of their customers.

• Clarabridge Act listens to customer feedback from all listening posts and provides business users with real-time dashboards, scorecards, and actual customer feedback accessable through browser, tablet, or smart phone to help them fix issues and engage with the customer.

• Clarabridge’s Intelligence Platform makes real action possible with insights from countless outlets.

iKEN – Artificial Intelligence based Consumer Analytics

iKen Solutions is a software product company that specializes in intelligent business systems backed by hybrid AI (Artificial Intelligence) techniques (expert system, case-based reasoning, neural net-works and genetic algorithms). It is an IIT Bombay research spin-off.

Products:

• MoogaSM : It is a comprehensive Consumer 3.0 analytics framework for N=1 personal-ized experiences. It acts like a backbone for all personalization and recommendations across different types of verticals (online/mobile/ipTV/DTH/Retail/BFSI, etc). http://www.infinitemoco.com

• iKen Studio: It is a completely web-based development environment to develop and deploy applications, knowledge-based decision support systems, websites and BI (Business Intelligence) applications backed by or enhanced with artificial intelligence (AI) techniques especially integrated archi-tectures of expert system and case-based reasoning. It is one of the first complete On-line Web-based Development Frameworks to develop and deploy Decision Support Sys-tems, Knowledge-based systems, Web-sites and applications backed by Expert Systems, Case-Based Reasoning, and Hybrid AI Tech-nologies.


TCS’ Retail Industry Solutions Unit

The Rules of Retail have changed. These New Rules bring new opportunities for the retail in-dustry—opportunities that might themselves become game changers. More and more, inno-vative retailers—using brilliant strategies, advanced technologies, best practices, and opera-tional excellence—grow revenue by delivering satisfying buying experiences wherever their customers are and whenever they want to buy. Tata Consultancy Services has partnered with eight of the top 10 US and five of the top 10 UK retailers in this journey. Our innovative busi-ness solutions and comprehensive portfolio of offerings, help retailers use these rules to guide them and build deeper and stronger customer relationships, reduce cost and increase efficien-cy through our integrated IT, BPO, and Infrastructure services and proprietary Retail Industry Solutions.

ContactTo share your feedback and continue our conversation, please write to [email protected]

About Tata Consultancy Services Ltd (TCS)

New Rules. New Game. Lead the Retail Revolution.

Tata Consultancy Services is an IT services, consulting and business solutions organization that delivers real results to global business, ensuring a level of certainty no other firm can match. TCS offers a consulting-led, integrated portfolio of IT and IT-enabled, infrastructure, engineering TM and assurance services. This is delivered through its unique Global Network Delivery Model, recognized as the benchmark of excellence in software development. A part of the Tata Group, India’s largest industrial conglomerate, TCS has a global footprint and is listed on the National Stock Exchange and Bombay Stock Exchange in India.

For more information, visit us at www.tcs.com

All content / information present here is the exclusive property of Tata Consultancy Services Limited (TCS). The content / information contained here is correct at the time of publishing. No material from here may be copied, modified, reproduced, republished, uploaded, transmitted, posted or dis-tributed in any form without prior written permission from TCS. Unauthorized use of the content / information appearing here may violate copyright, trademark and other applicable laws, and could result in criminal or civil penalties.

Copyright © 2014 Tata Consultancy Services Limited TCS

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