How these IIT-Kgp alumni are solving the curious case of app uninstalls

What happens when friends from college get together for a drink? Ideas are discussed and startups are built. This is exactly how Retention.ai was built. It all started when Manan Shah, Abhimanyu Dikshit, Amritanshu Anand and Anshul Singhle were having a drink in their friend’s house. Someone had called their friend saying there was an app that needed to be tested by a group of 100 people. And for every download of the app, the individual would receive Rs.100.

This got the four thinking and the idea of Beta Glide was born. At that point in time they believed the idea of app testing to be lucrative and interesting. However, the team found the idea was not working or selling. While working on Beta Glide, they realised that app creators, product managers and marketers faced a bigger problem: the abyss and mystery of uninstalls.

Pivoting Beta Glide to Retention.ai

"We already had most of the work done in Beta Glide to see if the app was working across multiple devices. We just needed to create a compelling solution for the product and marketing teams," says Manan Shah. This lead to the birth of Retention.ai.

The team already had data from the seven to eight months of work at Beta Glide to queries on why the app crashes, what the users’ network was , whether he/she was using 3G or WiFi, and what the engagement was. "The backend needed to be restructured," adds Manan. After three months of hard work, in January this year, Retention.ai was launched. According to Manan, Retention.ai helps people answer the question – ‘why was my app uninstalled?’

The team is getting on board one big client every week, trying to increase its current pool of 15, and is working with over 40 million devices. "With Retention.ai our clients are able to reduce the cost of wooing customers back by 40 per cent," adds Manan. The team is backed by angel investors - Pratyush Prasanna, ex-VP of Paytm, Puneet Soni, Chief Product Officer, Flipkart and few others. They also have raised USD 50,000 investment recently.

Working out patterns

Manan explains that their work begins once the marketing team figures out how many users had uninstalled their app. The Retention.ai team then identifies the user, what he/she was doing before they uninstalled the app, what campaigns they were receiving, and other details. The team then helps the marketing team figure out which campaign produces the maximum number of uninstalls.

"We then figure out how long it will take for an individual to uninstall the app. The average timelines are one day, seven days, 15 days or a month," adds Manan. Retention.ai also tells the product management team what the individual was doing before choosing to uninstall, if the app crashed and if he/she had received too many notifications.

The product also helps the marketing team know the average lifetime value of customer and how many transactions he/she made in the stipulated time period. On this basis, the team can decide how much money it can spend in wooing back each customer. "From our dashboard, you can create direct campaigns that can target individuals or groups and one can also decide the cost of acquisition," says Manan.

With a complete analysis of the customer's behaviour pattern on the app, Retention.ai also helps its clients to be more proactive. Based on the analysis, they can figure out which customer is mostly likely to uninstall the app. The marketers can, in turn, decide whether they want to retain that customer or not. Through an algorithm that follows the principles of pattern recognition, the team can decide if an individual will uninstall the app or not,” says Manan, adding that in the future, the team is intending to add marketing campaigns to the mix. "We want to tell the marketers what campaigns will be effective in retaining a customer," he says.

He adds, "We also give our clients competitive analysis that helps them target users who may be using their competition's app”. Also, on the basis of the apps that a user uses, Retention.ai also builds a profile of the user to understand their purchasing power.

The market for data

The idea of data analysis or use of intelligent means of understanding raw data has caught on like a house on fire. With every aspect of an individual's life being driven by the digital revolution, it's become imperative for organisations to get a better understanding of consumer behaviour through data analysis. Organisations like Aureus Analytics aim to do just that. The Big Data analysis market is said to be USD 125 billion.

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