Data Analysis Project

Client: Tata CLiQ   Date: 23rd May, 2023

About the Client:​

Tata CLiQ is the flagship digital commerce initiative by the Tata Group—one of India’s most respected conglomerates. As a multi-category e-commerce platform, Tata CLiQ offers a premium range of fashion, electronics, beauty, and lifestyle products. Known for its curated selection, omnichannel presence, and customer-first approach, Tata CLiQ combines trust with technology to deliver seamless shopping experiences across India.

The Challenge​

Operating in a highly competitive e-commerce space, Tata CLiQ faced data-related roadblocks that were impacting decision-making. With mounting pressure from market dynamics—fraud risk, fast-changing customer behavior, and the need for personalization—traditional analysis methods weren’t enough.

The key challenges included:

  • Detecting and preventing fraud in real-time

  • Understanding lifetime customer value

  • Responding to shifting consumer behaviors

  • Personalizing marketing efforts for micro-segments

  • Tracking sales and performance across teams and regions

  • Unifying data from multiple touchpoints for meaningful insights

Our Solution​

We helped Tata CLiQ implement Qlik Sense, a powerful BI platform, to structure and analyze their data more effectively. This enabled the brand to:

  • Monitor customer behavior and transactional trends

  • Detect fraud and fake transactions with structured data models

  • Analyze customer data across demographics, interests, and shopping habits

  • Predict customer lifetime value and reduce churn

  • Create targeted, data-driven marketing strategies

  • Generate region-wise and agent-level performance reports

The Outcome

Through Qlik Sense, Tata CLiQ transformed its analytics capabilities.

They could now:
✔️ Detect fraud patterns early
✔️ Optimize campaigns with behavioral insights
✔️ Monitor internal performance with real-time dashboards
✔️ Build stronger, data-backed marketing strategies

With Qlik Sense, the company can now conduct structured data analysis to identify specific indicators of potential fraudulent activities, including fake transactions. The platform enables the company to delve into intricate customer behavioural data, gathering insights from various sources such as demographics, preferences, attitudes, lifestyles, interests, and belief systems.
J Kumaran
Project Director

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