More Expectations and Less Loyalty

In our connected economy, where customers have more choices and higher expectations than ever, B2C companies struggle to get the most out of their customer relationships. They must do more to build an emotional bond between the customer and the brand. But they don’t have a unified customer view that spans all channels of interaction – with AI-driven recommendations for each customer to engage in the right way at the right time, every time. The result: missed opportunities, wasted time, and sub-optimal returns. 

Organizations also face ever-changing privacy regulations, the loss of third-party cookies, changing customer behavior, and siloed processes and systems, all of which make it harder than ever to increase customer lifetime value (CLV).  

A Customer Data Platform, powered by real-time AI-driven analytics, can help brands avoid these outcomes and improve performance and brand engagement. By turning data into intelligent actions, B2C companies can hyper-personalize brand engagement in real time to increase offer acceptance, cross-sell and upsell, loyalty, and ultimately CLV.

What is a Customer Data Platform (CDP)?

While definitions vary across industry experts, as represented below, most agree CDPs should provide a comprehensive, unified customer profile that can be shared across the enterprise.  

• Gartner: “A CDP is a marketing system that unifies a company’s customer data from marketing and other channels to enable customer modeling and optimize the timing and targeting of messages and offers.” [Source: Gartner Marketing Glossary]

• Forrester: “A CDP centralizes customer data from multiple sources and makes it available to systems of insight and engagement.” [Source: Forrester Glossary]

• Customer Data Platform Institute: “A Customer Data Platform is packaged software that creates a persistent, unified customer database that is accessible to other systems.” [Source: Customer Data Platform Institute Learning Center] 

CDPs collect customer data from multiple sources such as websites, mobile, call center, in-store, third parties, IoT, and enterprise data. They cleanse and unify the data and create unique customer profiles to be leveraged by other tools and technologies used by the organization, ensuring cross-organization access to a single comprehensive view of a customer. They eliminate the pain of grappling with data siloes and unlock the power of your customer data. 

But CDPs can also do more. TCS believes the role of a CDP should extend beyond data unification and point-in-time views to include AI-led recommendations orchestrated in real time across customer journeys that advance customer-facing marketing, product, and operations initiatives and optimize CLV and emotional engagement potential for each customer.

How is a CDP different than a CRM or DMP?

CRMs are used primarily, but not exclusively, by customer facing employees—sales, customer service, and support—to capture, track, and manage customer interactions, sales processes, and business transactions. They collect data from a limited number of transactional systems and usually do not incorporate interactions from channels such as websites, apps, loyalty systems, kiosks, or partners. Unlike CDPs, CRMs are not intended to support real-time marketing.

Data Management Platforms (DMPs) help organizations market more effectively to wide but specific audiences. DMPs collect and manage large, anonymized data sets of audiences from internal sources (CRMs, company-owned websites, and emails) and external sources (third-party data brokers and corporate partners). The data sets are most often used to create profiles and build look-alike audiences for advertisers who want to reach a wide but specific audience. DMPs rely on anonymity and have limited ability to integrate with first-party data.  In addition, DMP data is temporary, not persistent. Unlike CDPs, DMPs do not enable marketers to create single-customer profiles used for personalization.

A CDP complements CRMs and Data Management Platforms (DMP). CDPs not only integrate with CRMs and DMPs, but they also make those technologies more impactful by providing access to unified customer data.

What to look for in a CDP

CDP adoption is on the rise and organizations have several options from which to choose. Some offerings feature CDP-like capabilities that have been built on to existing marketing campaign automation tools. Others meet all requirements established by the CDP Institute and are RealCDP™-certified, and some CDPs extend even further to provide advanced customer analytics, hyper-personalization and real-time capabilities that build deeper customer engagements and drive loyalty as an outcome.

Look for the following key features in a modular solution that provides the ability to comprehensively orchestrate and coordinate with your existing technologies: 

Automated data unification: A CDP helps increase operational efficiency by automating data unification and ensuring teams and systems across the enterprise have access to clean, up-to-date customer profiles. With a single-source-of-truth for customer data, marketers and enterprise systems can gain accurate customer insights without concerns about data inaccuracies. Further extending the value, some CDPs leverage data unification to provide a user-friendly interface for efficiently analyzing customer behaviors, segmenting audiences, and determining the next-best-actions. 

Embedded real-time AI and ML: An AI- and ML-driven CDP with real-time capabilities generates data-driven insights that help the business understand the relevance, impact, and trajectories of customer behaviors. In short, only such a CDP can deliver effective and optimized contextual next best offers and recommendations with personalized journey orchestration in real time. 

Persona discovery and dynamic customer segmentation: Dynamic customer segmentation is anchored in analytics to help businesses market to continuously optimize customer groups. With historical purchase information, behavioral data, AI, and machine learning models, a CDP with persona discovery and dynamic segmentation can help brands target their campaigns to achieve the high conversion rates and lower costs. Dynamic customer segmentation is continuously refined to reflect changing customer interests, attitudes, and preferences. 

Next best offers and recommendations: Real-time customer analytics algorithms can leverage CDP data to surface next-best-actions and offers for each customer. The recommendations can be based on the customer’s brand interaction history as well as the interactions of customers that fall within the same persona. Examples of recommendation types may include Recommended Just for You (RJFY), Frequently Bought Together (FBT), Journey Next Best Action Recommendations (Journey NBA), and Top Trending Products. 

Journey orchestration: Journey orchestration links what were once ad-hoc interactions into a connected series of frictionless interactions that lead the customer along an engaging journey no matter when and where they interact with your brand. 

Each feature mentioned above yields incremental gain. When used in concert, they become a powerful engine for optimizing customer value and building deeper customer engagement.

Conclusion

A CDP can help brands use data-driven insights to deliver hyper-personalized customer experiences in real time to increase offer acceptance, cross-sell and upsell, loyalty and CLV. Not all CDPs are alike, however. To build deeper customer engagement and drive loyalty as an outcome, look for a CDP that goes beyond RealCDP requirements and provides advanced customer analytics, hyper-personalization, and real-time capabilities. 

TCS Customer Intelligence & Insights™: Comprehensive AI-powered, real-time CDP, customer analytics, and loyalty management.

TCS Customer Intelligence & Insights customer analytics software leverages AI/ML and real-time CDP capabilities to help brands deliver hyper-personalized customer engagements in real time and drive loyalty as an outcome. 

TCS Customer Intelligence & Insights collects, cleanses, unifies, and stores data from multiple sources into one location so business units across the enterprise can access a single, real-time view of the customer. TCS Customer Intelligence & Insights leverages advanced AI-driven analytics to turn data into action enabling organizations to reach the right people with the right message at the right time, resulting in improved brand recognition, customer engagement, and higher conversion rates.  

Unlike other CDPs, TCS Customer Intelligence & Insights is built on an extensible platform with pre-built, industry-specific analytics use cases that speed time to value. In addition, the low code platform enables business users to easily configure and build business use cases to meet their unique needs. TCS Customer Intelligence & Insights can be deployed on-premises or in the cloud based on data security and compliance needs. It’s agile, micro-services architecture complements existing marketing technology investments.