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TheDataTeam: Presenting Cadenz - An AI-powered Enterprise CDP

Rangarajan Vasudevan,Founder & CEO

The fans of neither Tom Cruise nor Steven Spielberg would forget the duo’s 2002 sci-fi blockbuster – Minority Report. In an iconic scene in the movie that portrays events occurring in 2054, a GAP store advertisement scans Tom Cruise’s retinas and immediately starts talking to him: “Welcome back to the Gap Mr. Yakamoto, how are those assorted tank tops working for you?” Even though his timing was off by more than three decades, Spielberg hit the bull’s eye with his prediction of the future of customer engagement, since big data & analytics already help organizations connect with their customers on a personal level.

Today’s consumer ecosystem is so advanced that they expect brands to instantly identify them and connect with them on a 1:1 level. Using a hyper-personalized approach, a business can not only identify subtle changes in market behavior, but also react to the same and provide the right products and services at the right time – without looking or seeming creepy. But oftentimes, large hurdles erect between this huge potential and organizations, accounting to challenges ranging from big data becoming bulk data to demand for data scientists, cost of employing them, and need for infusing them with domain expertise. Providing a solution to all the aforementioned hassles is Cadenz – a first-of-its-kind automated customer intelligence platform that provides enterprises with live behavior intelligence & actionable insights about their own customers. Cadenz, which was developed by TheDataTeam(TDT) – an AI company working closely with enterprises to enable the vision of ‘customer value without friction’, caters to a wide horizon of industries ranging from BFSI to Retail, Telecom, Airlines, and Oil & Gas. CIO Insider recently had an exclusive interview with the man at the helm, TDT’s founder & CEO, Rangarajan Vasudevan.

In conversation with Rangarajan Vasudevan, Founder & CEO, TheDataTeam

What are the kind of market challenges that inspired the development of Cadenz?
Customer-facing functions in many enterprises across industries have started to use analytics to guide decisions. This has become a necessity due to ever-increasing data collection, thanks to the penetration of the internet and the adoption of digital by most industries. Quite clearly, big data has long become bulk data. Delving deeper, it is also clear that this huge amount of data being generated is largely centered around end consumers, machines (mainly IoT data), or corporate entities or brands.

The generation of bulk data has led enterprises to seek insights at a micro

level, by understanding the preferences of each individual, keeping track of changes in the behaviors, and personalizing products or services. This process has been traditionally manual and hard-to-scale. It traditionally called for deep expertise in data science and data management-related competencies and skills. It’s not only that human-intervention makes deriving insights a slow process, they derive only siloed data that can’t provide live insights, which is a crucial aspect of reacting to the dynamic market behavior and being agile. All these result in poor ROI.

Cadenz relieves organizations from hiring and maintaining costly data science functions by providing them with behavioral intelligence and actionable insights about their customers in an automated way

Over the last five years, we first realized that today’s customer data management platforms really only catered to the marketing crowd. We refer to the technologies that emerged in this phase of the market as ‘Marketing CDP’ (or Marketing Customer Data Platform). Whereas, what we heard from our enterprise customers again and again was that they could not hire these data teams themselves fast enough, or could not retain them effectively even if top-notch talent were hired. What made matters worse was that the analytics function was expected to cater to the entire enterprise, that is, for all customer functions, not just marketing. Both these realizations made us invest into cutting-edge AI that is now available as Cadenz that directly addresses these problem statements.

What makes Cadenz unique and what are the salient features that it incorporates?
Simply put, point Cadenz to data in a domain it has seen before, it will generate insights that are actionable. That sounds like magic but in reality it is just good AI. Now, obviously the more removed the product is from the actual business problem being solved, the less usable its insights are. We have therefore productized Cadenz to cater to specific verticals to start off with, providing the vehicle for an army of use cases that are good to go.

Cadenz relieves organizations from hiring and maintaining costly data science functions by providing them with behavioral intelligence and actionable insights about their customers in an automated way. Simultaneously, in the process, it also overcomes the risk of failure, resulting in significant savings in cost and time for enterprises. In other words, Cadenz builds a knowledge asset for every organization with customers at the center, making sure that the actionable insights churned out by platform powers not only the marketing function or sales use cases, but also dramatically transforms other functions within the company like revenue assurance, fraud, risk control and much more.

We are talking about a whole world of different contexts across these industries and within each organization. How does Cadenz deal with this?
Since the crux of the matter always revolves around the intelligence derived from data, understanding what the data means in a particular context is of paramount importance. Cadenz excels in this. For instance, let’s take the BFSI segment. The pandemic has brought immense variability to the MSME sector, which directly translates into increased risk factor for various public and private sector lenders. It’s crucial for lending institutions to have precise intelligence about how many loans would go bad and whether they are reversible, which is a huge challenge.

In truth, around 60-70 percent of information required to figure out the risk factor involved with a loan already exists with the bank as raw customer data. This data, however, exists in multiple silos, some of which are complex mission critical systems by themselves. We are talking about years of data accumulation. Nobody has actually taken the time to put this data together. Cadenz starts building the solution by stitching this data together in an intelligent way. In the process, our AI algorithms determine risk indicators, categorizes them with respect to time and churns out actionable information, which significantly helps in risk mitigation while generating new insights. has also carved its niche in the telecom industry, especially by helping telcos optimize revenue generation from new-age opportunities like OTT platforms. Could you tell us a case
A large ASEAN telco was dealing with a number of issues, including disparate and siloed customer data, revenue loss due to OTT, lack of insight into user trends and intentions, and in turn, non-personalized interactions with subscribers. Cadenz helped the Telco translate raw consent-driven mobile appstream and clickstream-collected browsing data to automatically derived intelligence, based on customer attributes, categories & subcategories. It stacks up information like user preferences, content viewed repeatedly, and most downloaded & used apps. It then implements automated models to build live subscriber profiles. Having a full view of subscribers, their purchase history, and browsing behavior enables companies to personalize more effectively that too across different touchpoings.

Using Cadenz, the telco now tracks 500+ behavioral attributes for every subscriber to give a complete view to service agents and to monetize through partner merchants & brands.

What’s the future set for TheDataTeam?
The global customer data platform market is poised to grow from $2.4 billion in 2020 to $10.3 billion in 2025, growing at a CAGR of 34 percent. We believe that TheDataTeam is well poised to capture this market and carve a niche for itself, thanks to our flagship product Cadenz. Cadenz has a great number of marquee customers across Telecom, BFSI, Airlines, O&G, and Retail in the APAC region. With the current set of customers deriving significant value from the product, we will replicate the success stories across other regions.

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TheDataTeam: Presenting Cadenz - An AI-Powered Enterprise CDP