BeginnerFree 5 days · 50 tasks

Quick-Commerce Customer Retention Drop

New customers of a 15-minute grocery app stopped coming back after May. Build cohort retention, find the causes — a small-cart fee, one failing dark store, late deliveries or a coupon campaign — and size the problem.

Kiranakart Quick Commerce Pvt Ltd · SQL · Python (pandas, seaborn) · solved in your browser

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Create a free account to open the workspace, check your answers and earn a certificate.

The problem

Management does not know how far the repeat rate of new customers has fallen, which customers and stores are affected, or which of the recent changes is responsible. The Chief Business Officer needs a data-backed cohort analysis of orders from 1 January to 30 September 2026 to decide whether to change the small-cart fee, fix operations at particular stores or stop the coupon campaign.

How it works

Start the project — the 5-day timer begins and the workspace opens with every table loaded.
Solve 50 tasks in SQL or Python (30 basic, 15 intermediate, 5 hard). Each is checked instantly.
Write the final report in the workspace and add charts from your notebook.
Score = 70% tasks + 30% report review. 60 or more earns a certificate.

What you will deliver

Answers to the 50 analysis tasks (30 basic, 15 intermediate, 5 hard), solved with SQL or Python in the JobPrax workspace.
A final report written in the workspace for the Chief Business Officer: executive summary, data quality, findings and recommendations.
Two to four charts from your Python notebook, added to the report (for example a cohort repeat-rate line, a retention heatmap and repeat rate by channel).