1) How SuperEats improved customer loyalty for a food delivery app
The Scenario
SuperEats, a popular food delivery app, was looking to increase the purchase retention of food orders and boost customer loyalty.
The Challenge
Despite a substantial investment in a 50% discount offer on the first 3 orders to attract new customers, their daily active users were still very low after an initial bump within the first weeks of users being exposed to their campaign.
Investigating in UXCam
In order to confirm and measure the impact of the campaign, they had to first align on what ‘loyalty’ meant to across the team:
1. Identifying core value action: The key action here was placing food orders
2. Defining retention interval: They would only consider a user loyal if they were repeatedly ordering at least once a week.
How to set up the Retention report
- Start Action: Users who have had their first session (First visit).
- Return action: Event happened > Product purchase complete
- Return interval: In or after 'Each week'.
Recap of retention definition: User visits app → orders food → comes back at least once a week
Analyzing retention results
In the table, they saw how many visited the app for the first time, and how many are coming back every following week. Users are coming back but after week 4 they start to decline. You can see in this color gradient, when it’s darker, it’s higher retention rate and when it’s lighter it’s a lower retention rate.
Based on the retention table of the past 90 days, there were some key findings:
- A significant decline in user retention is observed from week 0 to week 4.
- Retention heat maps indicate a drop in retention rates after week 4.
- A closer examination of the data suggests a correlation with the 50% discount promotion.
The 50% discount promotion, valid for the first three orders, resulted in a pattern where users returned only when prompted by this specific discount. SuperEats acquired users at a cost of $100, but their orders only generated $50 in revenue before they stopped returning
We can see that users come, they have the voucher, they order something week by week until they see the full price. So only when they are prompted by a promotion, they come.
What we see in the retention chart, is that SuperEats is basically spending money to lose users. Ouch.
The Solution
To address this issue, SuperEats proposed a solution - offering points for every order to provide smaller, consistent discounts, which might encourage users to return. They can use the same retention table to see the results of their experiment.
2)How a gaming app increased retention by 10%
The Scenario
Puzly, a highly popular gaming app, identified the need to delve deeper into user engagement and boost the overall retention of its game.
The Challenge
Having invested considerable resources in developing and marketing their gaming app, Puzly faced the challenge of understanding how sticky the app truly was. Initial metrics indicated potential issues with user retention, prompting the team to explore UXCam's features for a comprehensive analysis.
Investigating in UXCam
Puzly leveraged UXCam's retention feature to gain a deeper understanding of user behavior within the app. The team built several reports, breaking down retention by a number of properties, including device type, geographic location, and app version.
How to set up the Retention report
- Start Action: Users who have had their first session (First visit).
- Return action: App Launch
- Return interval: In or after 'Each day'.
- Grouping : Device model
Upon analyzing the retention data, a significant revelation surfaced: users with low-end devices exhibited notably poorer retention rates compared to other devices. Intrigued by this finding, the team decided to investigate further and pinpoint the root causes.
Uncovering Issues with Low-End Devices
To dig in further and understand the root causes, the team saved the dropped out cohort and analyzed it using UXCam's pre-built dashboard. This analysis unveiled a concerning trend - users on low-end devices experienced high instances of crashes and UI freezes. It became evident that the Puzly app was not adequately tested and optimized for these devices, leading to a subpar user experience and subsequent retention challenges.
Addressing the Problem
Understanding the magnitude of the issue, the team delved into the allocation of device models across all Puzly users. Shockingly, 40% of users fell into the low-end device category. Recognizing the need for swift action, the team initiated a comprehensive optimization effort tailored specifically for these devices.
Results
Over the next several months, the team diligently tracked retention metrics. By addressing the issues identified through UXCam's retention analysis, Puzly not only resolved technical glitches but also significantly improved the gaming experience for low-end device users. This strategic intervention resulted in a remarkable 10% increase in overall retention.