DevRev enhances BigBasket's UX and design for new feature rollouts

The company

BigBasket is India’s largest online grocery store. Its mobile apps offer retail solutions like subscription delivery, on-demand delivery, and vending machines. This case study focuses on BigBasket’s subscription delivery app called bbdaily. Millions in India use the bbdaily app to order household needs to their doorsteps every day.

The challenge

With a fast-growing user base and constantly updating features, BigBasket’s design team was entrusted with delivering the best experiences on the bbdaily app. However, the team didn’t have any tools to monitor user behavior, conduct UI/UX research, or carry out testing. Which led to the following challenges:

Limited insights into behavior and research

The mainstream app analytics tools were limited to metrics and charts, lacking any visual insights. Events did not reveal the complete picture behind the interactions. Whether it was UI/UX research or experiments on the Beta releases, the team’s capacity to improve the design continuously was slow.

UAT was a long and cumbersome process

User Acceptance Testing (UAT)—a core requirement at BigBasket—usually took more than 5 days to complete. This was because of the limitations in reaching out to customers by email and call. Very few customers participated in UATs, affecting the sample set.

Moreover, the process kept 5-7 designers blocked from doing any other tasks.

The solution

DevRev PLuG's implementation revolutionized how the design team monitors user behavior, especially regarding new features and design changes. With this tool, the team now has a suite of analytical solutions at their disposal, allowing them to examine and understand the impact of critical features closely.

This enhanced capability to track and analyze user interactions enables more informed and effective design decisions, contributing to an overall better product experience.

Identifying conversion bottlenecks in Add-to-Cart journeys

The bbdaily team used user and session analytics data to redesign the ‘Add-to-Cart’ user flows for better conversion rates. Designers could make iterative changes and monitor the interactions on heatmaps. They could drill down funnel analysis with session replays to get more clarity on the drop-offs and relevant issues.

Monitoring new feature updates

BigBasket improved its services using DevRev's advanced tools, User 360 and Session 360. These tools helped them track new features and identify areas needing optimization. Notably, they upgraded the map feature, making it easier for users to add delivery addresses.

The updated map feature made adding delivery addresses quick and easy, saving users time when placing orders.

Helping the Dev team replicate crashes and app freezes

The design team provided the development team with links to data on app crashes and freezes. This enabled the developers to visualize better and understand the app issues. With this comprehensive context, they could replicate and address the problems more effectively, leading to quicker and more efficient issue resolution.

The impact

BigBasket used detailed visuals and relevant information to understand their app's issues better. This approach helped the business improve quickly, leading to a better user experience.

400+ Hours of UAT reduced to a few hours

By utilizing session replays and heatmaps for User Acceptance Tests (UATs), the BigBasket team minimized the need to contact customers directly for feedback. This approach overcame the limitations of relying on a small group of customer samples. In certain instances, with DevRev's assistance, the team could even complete UATs in as little as 2 hours, significantly speeding up the process.

3x Lower complaints, 100% more conversions

The ongoing efforts of the product design team in monitoring and enhancing the app led to a notable increase in 'Add-to-Cart' conversion rates, which effectively doubled over time. This improvement also resulted in customers encountering fewer issues while using the app, leading to a substantial decrease in customer complaints.

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