In this case study, we will showcase how a successful retail app marketing team can help improve new user activation by 60% using funnel analysis.
The retail industry has seen significant growth over the past few years, and the increasing popularity of retail apps has played a crucial role in this development. The COVID-19 pandemic has further accelerated the adoption of retail apps as consumers have shifted towards online shopping.
Retail apps offer convenience, personalization, and seamless shopping experiences to users, leading to increased customer loyalty and retention. With the ever-growing competition in the retail industry, it has become essential for retailers to adopt mobile technologies and stay ahead of the curve.
In this case study, we will explore the latest industry background and development prospects for retail apps. We will examine how retail apps are transforming the retail industry and providing unique shopping experiences to customers. We will also delve into the challenges faced by retailers in implementing retail apps and the ASO strategies they can adopt to overcome these challenges.
Additionally, we will showcase how a successful retail app marketing team can help improve new user activation by 60% using funnel analysis. Through this case study, we aim to provide insights into how retailers can leverage the power of app store optimization(ASO) and optimize their retail apps to drive customer engagement, retention, and loyalty.
After implementing the above strategy, the app marketing team was able to improve new user activation by 60%. The following metrics demonstrate the success of the strategy:
A mature retail app had been experiencing a decline in new user activation and needed to implement strategies to improve this metric. So the app found ASOWorld for help from ASO experts. Then our team decided to conduct a funnel analysis to identify the areas of the app that were causing new users to drop off.
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Improving a retail app's new user activation by 60% can be a challenging task for several reasons:
For the retail app, retention and app stickiness are critical metrics. Our team tracks retention at the most granular level possible across the customer lifecycle. The retention funnel's initial stages are focused on providing a simple onboarding experience with minimal friction. As merchants become more acquainted with the app, it shifts its focus to providing incremental value in terms of features and solutions.
The frequency with which users use the app is an indicator of whether the app adds value to their lives. Those who use the app on a daily or weekly basis are clearly the most engaged and have the highest retention rates.
In terms of growth, the team examines how their retained user base expands over time, as well as the level of engagement within each cohort. This allows them to be proactive if the engagement of a specific cohort appears to be waning.
Our team helped the client create a funnel to track the user journey from download to activation. They identified the steps where users were dropping off and made changes to the app to make the process smoother. For example, they simplified the registration process, reduced the number of required fields, and improved the app's speed.
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Based on the stages of the customer lifecycle, our team divides the user flow and the product into different conversion funnels. An onboarding funnel, for example, focuses on users from their first app launch until they complete their first few transactions.
We've also created funnels tailored to specific product features. They have funnels, for example, where users can create their first SKUs and update product quantities. Each feature has its own funnel, which measures conversion and stickiness at a granular level.
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On a broader level, funnels are used to track the overall health of user flows and determine whether or not product and marketing initiatives have an impact on funnel conversions.
Our team uses analytics tools to identify drop points in the funnel. We analyzed user behavior and found that many users were lost during the signup process. We've found that users are reluctant to provide personal information, which is a requirement for registration.
Therefore, the app simplifies the registration process by reducing the number of required fields and giving users the option to register using their social media accounts. This reduces friction in the signup process and makes it easier for users to activate their accounts.
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The team improved the onboarding process by offering users a more personalized experience. They used data analytics tools to gain insights into user behavior and preferences, and then provided users with recommendations and offers tailored to their specific interests.
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The team can easily A/B test UI/UX variations to improve the user experience with personalized experiences. Furthermore, feature flags allow them to build and iterate on products more quickly, as well as launch new features without the need for full-fledged app releases. This increases the likelihood of a new feature's success by testing it with a small group of users, modifying it based on feedback, and eventually rolling it out to all users.
By using a data-driven approach that included funnels analysis, the retail app was able to increase its activation rate by 60%. The app marketing team was able to identify the areas of the funnel where users were dropping off and make changes to the app to improve the activation rate. They simplified the registration process, reduced the number of required fields, and optimized the onboarding process to provide users with a personalized experience.
The team's efforts resulted in increased user engagement and revenue, and the app marketing team was able to achieve its goals of improving the app's performance.
Mobile Growth,User Retention,App Growth Case Study,
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