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Data Masters in Action: Unveiling Chief Digital Officer’s most wanted asset


A Q&A with Marc de Forsanz, Global Head of Customer First, Insights & Data; Padmashree Shagrithaya, Global Head, Analytics & Data Science; and Naresh Khanduri, Vice President, Digital Customer Experience at Capgemini

A happy customer is a repeat customer – and a repeat customer results in higher revenues, larger profits, and lower costs for customer acquisition and retention. Not only this, but a happy customer also feels safe about transacting with the organization. Such customers deliver greater lifetime value to the enterprise. Every business knows this, but improving customer satisfaction, being relevant/meaningful, aligning to customer values and appealing to their beliefs is an ever-challenging goal.

Marc de Forsanz, Padmashree Shagrithaya, and Naresh Khanduri, are responsible for Capgemini Data-driven CX– an AI-powered offering that helps companies deliver next-level customer experiences. They discuss the need for Chief Data Officers to help organizations manage the customer journey seamlessly and in real-time across a range of channels, and how Data-driven CX builds on the work that many companies have already undertaken with customer-data platforms.

What’s the elevator pitch for Data-driven CX?

de Forsanz: Data-Driven CX enables clients to take full advantage of related customer data (transactional, behavioral, product) from all channels to impact customer acquisition, retention and advocacy (in real-time). In short, it’s an AI-augmented customer-data ecosystem. Customers interact with brands through a variety of channels – including marketing, ecommerce, customer service centers, and in-store visits. Data-driven CX aims to enhance the experience of customers across all channels through data harmonization and activation through AI&ML. Specifically for the Chief Data Officer, it ensures the data is high quality so there’s trust in the data, and that the data is collected, stored, and used in compliance with all relevant privacy laws and regulations.

How much of an issue is this, really?

de Forsanz: Customer data is both strategic for a company (scheduled end of third-party cookie, first party data) and complex to manage (multiple data sources, data quality, PII topics, legal regulations). Whether the subject is initially marketing or broader into areas like E-Commerce, Customer Service, It is essential to partner with a firm who is versed in turning data strategy into a competitive advantage. Capgemini’s own research has shown there’s plenty of room for improvement. To highlight a couple of challenges, 57 percent of marketers we asked admitted they’re missing important data points required to obtain a full view of their customers. And only 45 percent of firms believe they have the data they need to understand the connection between online points of contact and in-store behavior.

How is Data-driven CX different from a customer-data platform?

Shagrithaya: Our data-driven CX shapes the customer experience and drives analytics and engagement. It harmonizes the data about each customer. But it also makes that data contextual. Many of our clients have walked the path of building what’s known as a Customer 360 – but despite this, they find they’re not able to engage with the customer in a meaningful way. The approach, many a times, is to gather as much information about the customer, whether relevant or not and whether that’d be intruding into the privacy or not! Data-driven CX combines knowledge of the customer with the contextual information the company needs to deliver the most satisfying experience through responsible personalization. So, for example, if a customer visits a company’s ecommerce site because they have recently bought something, the context is “Why are they visiting?” Are they looking for a service, or for an add-on for the product, or for a different product entirely? Understanding their intent within context and then servicing that intent is important because it generates a positive outcome for the company, and provides a meaningful experience to the consumer.

How does AI help with this?

Khanduri: AI is all about understanding the customer’s intent. Behavior on the channel should be driven by the insights generated by the AI engine, not by some rule that somebody came up with because “it feels right.” Data-driven CX allows enterprises to examine each customer’s data (with their consent) and learn from it, and then let the AI help with the next interaction with that customer. It allows companies to anticipate their customer’s intent based on data, not gut feelings. The outcome is that the customer has a better experience – they believe that the organization truly understands their needs – and they become more loyal to the brand. That’s the ultimate goal – a loyal customer who advocates for the brand.

And that’s an outcome with many financial advantages for a company…

Khanduri: Exactly. From the perspective of engaging with customers, the biggest investment a company makes is the cost to acquire that customer in the first place. Companies invest in traditional and online advertising, marketing campaigns, search-engine optimization, and so on – all to encourage that customer to make their first visit to a channel. And today, if the chosen channel does not deliver a personalized, unique experience, the company can lose that customer – often, for good. The bottom line is, it’s more cost effective to serve a customer you already have than to acquire a new one – and Data-driven CX is designed to help companies build that loyalty.

Shagrithaya: It can also reduce the total cost of operation for the enterprise. Some companies have implemented a customer-data platform but they do not think through the underlying questions of how to treat data of customers coming in from multiple channels in a consistent and coordinated manner, or how to activate the same through appropriate AI/ML algorithms. By not addressing these questions up front, they would have made the whole process more expensive than it should be. Data-driven CX helps bring those costs under control by providing the CDO with the tools to properly manage all aspects of their company’s data.

How does a company get started on this journey?

de Forsanz: Data Scientists, data analysts and business users need reliable customer related data to build analytics, AI use cases and an optimal Omnichannel experience. The beginning of all stories are the use cases which will drastically increase the performance of a department or the whole enterprise when this vision is shared. I encourage CDOs to identify their pain points with customer data right now. They should identify which departments are using customer data, how they’re using it, what they would like to do with it, and whether they’re achieving those goals.

Khanduri: We try to determine the use cases they want to activate – but also encourage them to adopt a holistic picture of their needs. They can start with a single business case – but at the same time, they should be planning to support other potential cases. If they’re trying to improve a single use case but not planning for others, they will not be able to solve all of their business challenges. For example, if they’re trying to convert sales leads into sales, they should also be looking at how they will improve after-sales service for those new customers.

As they look to enhance their customer experiences with a solution such as Data-driven CX, what can CDOs do to maximize their success?

Khanduri: One thing that has always surprised me is that few people actually ask, “Do I have the right data?” They’ve collected whatever data is available and they’ve created a customer profile with it, but they haven’t actually figured out if it’s the data they need to achieve their business objectives. I encourage CDOs to have that conversation with those who use data in their company – to examine the data they have in the context of their business objectives and the experiences they want to deliver to ensure they are collecting the information they need.

Shagrithaya: CDOs sometimes look at what they’ve already done and wonder why it’s not working for them. They’ll point out to me that they’ve invested in CRM, they’ve invested in Customer 360, they have a customer-data platform – and they were told this was all going to help their sales team – but they’re still not able to move the needle with respect to their KPIs, for example, of increasing the lifetime value of their customers. That’s a common starting place when we’ve had conversations with potential clients. We typically start with an architecture review to understand the existing landscape and propose appropriate end state architecture, with the existing investments in mind so that our clients need not shelve their current investments altogether to move to the new platform.

de Forsanz: That’s one of the things Data-driven CX does really well. It builds a perfect asset for the CDO to manage customer data, so all departments in the enterprise can unlock the value in the company’s data.


Padmashree Shagrithya

In her diversified career spanning over 25 years has crafted and led multiple large and complex transformation programs delivering strong business outcomes for many clients, leveraging Data, Technology, Machine Learning and Artificial Intelligence.


Marc has solid knowledge in digital (website development, CRO, UX/UI design, brand content, traffic generation (Google SEO certification, Openclassrooms SEA certification, bloggers outreach). He also is also well versed in data science and machine learning capabilities.

Naresh Khanduri

In his current role as Data-Driven CX Lead, he helps clients maximize, and scale business value across CX channels. He specializes in combining Experience data with Enterprise data and applying advanced analytics, artificial intelligence to build immersive experiences.