Tata CLiQ is an Indian e-commerce company started in 2016 based out of Mumbai. It is owned by Tata Digital Limited, of Tata Group. It is based on an omnichannel marketplace model. It operates in four major business lines, Marketplace or the Mall, Electronics, Lifestyle & Beauty and the Tata Cliq Luxury. Operational at all serviceable pin-codes in India, it houses all the major brands in each of the categories it operates. It is the largest luxury platform in terms of the assortment of brands on its platform. The brand is synonymous with authenticity and trust.
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At its Mumbai headquarters, there are more than 800 employees. It has been building its presence in Bangalore for the last two years, where its product and tech teams are based. In their omnichannel business model, data plays a pivotal role in all their initiatives and decisions. The company has a central Data Science & Analytics team to empower all the verticals with various analyses.

We interviewed Sayandeep Bhowmik from Tata Cliq, for this case study. Sayandeep has been at the company for over 3 years. He has spearheaded many projects providing critical inputs to solve business problems. He heads the Business Insights team at Tata Cliq. Business Insights Team which focuses primarily on analytics is a part of the Data Science and Analytics vertical. It is 15 members strong with over half of the team dedicated to analytics and insights, and the rest are data scientists & data engineers.
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The team provides insights to various stakeholders & teams. Fulfilment, product analytics, category analytics, marketing analytics, customer understanding, are a few of the key areas of work for the team. They together focus on delivering value to all stakeholders, enabling them to make data-driven decisions. Sayandeep and his team live by the pillars of "customer and data obsession".

The central analytics team played a pivotal part in providing data & insights to all other teams. For these teams, coding or querying was not in their primary skillsets. But data plays an integral part in their decision-making process. While the Analytics team would help them with the required data and insights, some of the data requests were repeatable & ad-hoc in nature. The team wanted to solve these kinds of requests and free up their resources, concentrating on other advanced problems. Also, making the other teams self-sufficient for their non-complicated data needs and making each and every member data empowered.

Once the problem was identified, the analytics team brainstormed on the possible solutions. One obvious solution was to have individuals in all the teams who are data champions and could help the team with providing the required data & analyses. But it defeated the whole purpose of making each one feel data empowered. Hence, they were on the lookout for a solution that was easy to use, required no coding skills and is self-serve. The teams should be able to use the solution effectively to get data for their needs, once configured.

They conducted primary research to find solutions that were available in the market. After looking for a few options, they chose Sprinkle. Sprinkle proved to be the best fit for their case based on their needs, economic sense & scale of operations.

Sprinkle set up a preliminary proof-of-concept (POC) with the Data Science & Analytics group at Tata Cliq. The teams together brainstormed on various facets of the problem and how to together solve them using the Sprinkle capabilities. Regular scrum was set up initially during the POC, where the teams would discuss problems like the structure of the databases, on which warehouse should the data reside, etc. The onboarding process was smoothly facilitated by the Sprinkle team.
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Sayandeep Says “The Sprinkle team has smoothly facilitated the onboarding process. Good availability & swift response from the Sprinkle team helped us a lot. Their flexibility, accommodative nature and strong working relationships have proved invaluable. In all, it has been a very good experience”.
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The warehouses and storage were configured on Sprinkle. The sprinkle support team helped set up the platform, build models, and optimize processes. It was then made available to the larger teams across the company, to be used for all their data needs.

The ad-hoc data requests to the analytics team have decreased. In a short span of time, there are power users of Sprinkle in different teams. These power users are themselves pulling relevant data from Redshift, doing analysis, preparing reports, performing pivots, creating views and slices, doing trend analysis, creating visualizations as per their need. These users are also training other users who are not that data-savvy. They have also started to use the Sprinkle platform.
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The time taken to perform an analysis has reduced significantly. Fetching data is no longer a problem. And top of that it has become easy to create views from data & generate reports.
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Sayandeep says “For example, just before a review meeting, the team can generate insights quickly. And based on the insights, the business teams can make decisions on what brands to keep, what assortments to plan, etc. The business teams can clear their mental space to focus on things that need their attention”.
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The teams are on the journey to be data empowered as they feel closer to the data with Sprinkle. Sayandeep says “Raising the general data awareness of the individuals is the objective of the firm, thus enabling them to take data-backed decisions”.