Jar improves customer insights and increased conversion rates using DevRev

The company

Jar, one of India's fastest-growing fintech startups, modernizes the traditional habit of saving in physical gold by offering users an option to micro-invest in digital gold. Its custom-built mobile apps have helped more than 15 million users streamline their journey to building digital wealth.

Aiming to attract a million more users each year, Jar plans to expand its offerings to include a broader array of financial instruments for diversification.

The challenge

Limitations in understanding users

One of the most significant challenges for Product Managers (PMs) today is effectively capturing and analyzing user pain points within the app. While conventional analytic tools provide exhaustive metrics, PMs are still limited in understanding the 'why' behind them. For Jar, understanding users was even more complex as most users are not tech-savvy and are often reluctant to share feedback.

Jar wanted faster product iterations, for which it conducted user testing and interviews. However, these manual methods were non-scalable, consuming up to 15 days to yield any actionable insights. This slow feedback loop left Jar dissatisfied, impeding its efforts to rapidly enhance its offerings.

Undetectable conversion drop-offs

Ankit Dhawan, Jar's lead PM, consistently sought to optimize conversion flows. Dhawan shared how they aimed to enhance the gold subscription autopay journey. Yet his team noticed increased drop-off rates soon after rolling out the changes, defying their expectations. Moreover, while a conventional funnel analysis tool showed the percentage of users dropping off at each step, it failed to provide any actionable diagnosis.

Inability to reproduce users’ issues

A large portion of Jar's user base comes from lower and middle-income groups who access the app on low-end devices. This made it difficult to replicate issues. While tests passed on a few devices and emulators, there was a lack of visibility into bugs leaving developers unable to diagnose the root causes.

The solution

Understanding at scale

Jar’s product team used DevRev PLuG to scale user research and analysis. Instead of spending several weeks extracting data manually, the team filters out user segments using events, user behavior, functional issues, performance, APIs, and more. This was possible because DevRev PLuG collects granular data from the app and makes it available in a few clicks.

The product team could find answers to unusual behavior such as: Why are users spending over 120 seconds on the login page? and Why do many users navigate back and forth between a few screens without completing a key journey?

As a standard practice, Jar started using DevRev PLuG after every new release for faster validation. The team quickly spotted what was wrong without waiting for user complaints. With access to contextual insights linking technical errors with struggling behavioural patterns, Jar could continuously improve user experience.

Drilling down on the reasons for drop-offs

DevRev's Funnel Analytics unlocked insights beyond just drop-off percentages. By exposing technical failures causing user struggle, Jar could pinpoint the reasons behind declining conversion rates on critical journeys. For instance, when analyzing the gold subscription journey, the team identified issues related to data loading and screen rendering. Armed with this visibility, the product team could share a link with developers to replay the issue along with logs to troubleshoot and deploy fixes swiftly.

Replicating user issues

DevRev PLuG auto-captures issues like crashes and UI freezes happening on real user devices. These issues can be then filtered by OS, phone model, network, app version, and so on. Many issues that couldn’t have been replicated on an identical device environment or a browser-based emulator, were now possible.

The impact

"DevRev has made hypothesis testing effortless" Dhawan stated.

Significant time saved in research and analysis

By validating features directly against user session data, Jar significantly reduced reliance on manual user interviews. This enabled the team to dedicate more bandwidth to interpreting insights and identifying optimization opportunities.

3% Lift in conversions

The gold autopay subscription is Jar’s high-impact conversion journey. Within a few days of funnel analysis on DevRev PLuG, the team could rectify issues resulting in a lift of 3% in conversions.

Increased developer productivity

DevRev PLuG increased developer productivity by providing real-time insights into user struggles and by facilitating collaboration with the product team. It helped Jar uncover bugs impacting customers directly, allowing for prioritized issue resolution without additional explanation.