App reviews play a key role in how applications rank on Google Play and the Apple App Store. In this post, we want to share how we approached the App Store Optimization (ASO) of a client’s fintech application.
How Do App Reviews Influence Rankings and Downloads?
App reviews impact both rankings and downloads in two main ways:
External ASO factors: Reviews are a ranking factor in both Google Play and the Apple App Store. Positive reviews are taken into account by the algorithms of these marketplaces.
At the same time, positive reviews also have a social effect that encourages downloads. Users naturally tend to trust applications with strong ratings and positive feedback. A high number of positive reviews therefore increases the number of downloads because of the trust they generate among potential users.
Analyzing Reviews of a Fintech App and Its Competitors
One of our fintech client offers an app for its financial products, available on both Google Play and the App Store.
All of our client’s competitors also have their own apps, some of them with a longer track record and a larger user base.
We launched this ASO & AI project with three main objectives:
- Analyze our client’s reviews to identify internal improvement opportunities.
- Understand the brand perception reflected in the reviews and identify the distinctive competencies generated by our competitive advantages.
- Study the strengths and weaknesses of competitor apps based on their reviews in order to carry out a benchmarking process.
To achieve these objectives, we designed the following process for this :
- Data mining of reviews from our client’s app and competitor apps.
- Analysis of the extracted data.
- Extraction of conclusions and recommendations.
- Implementation roadmap to improve the app.
Data Mining
The first step in the analysis was data mining, extracting reviews from our client’s app and from its four main competitors.
Naturally, we did not have direct access to competitor reviews. Since we could not access them through their Google or Apple profiles, we developed our own program to download them.
Using this proprietary solution, we downloaded a total of 5.8 million reviews from our client’s application and from its four main competitors.
Analysis of the Extracted Data
From the extracted data we identified:
- Complaints related to our app
- Weak points of our application
- Strengths of our app highlighted by users
We also performed the same analysis on competitor apps and were able to identify their strengths, weaknesses, and the competitive advantages they are perceived for.
Based on these findings, we selected five attributes and assigned a score from 1 to 5 to each app based on user ratings, as shown in the following table.
Using this information, we created a Kiviat Chart, which allowed us to visually compare all the apps and quickly identify the attributes where we were better positioned and those where we had clear opportunities for improvement.
In addition, we developed several buyer persona profiles to support the identification of improvement opportunities.
Extraction of Conclusions and Recommendations
Benchmarking
Both our client and its competitors position themselves in the market around several common attributes.
Through this analysis, we discovered that users of our client’s app were not clearly perceiving some of the attributes we were trying to position around in the market.
By analyzing competitor reviews, we found that some competitors were successfully positioning themselves around those competitive advantages. We leveraged these learnings and incorporated them into the recommendations for our client.
Recommendations
After analyzing the data from both our app and competitor apps, we developed the following recommendations:
- Customer support
Improve customer support by responding faster to user requests and clearly indicating the resolution status of each issue: received → under review → responded → resolved.
- Communicating account charges in advance
Notify customers in advance about charges that will be made to their accounts so they can anticipate them.
- Improve product shipping
Our client needs to send physical products to users. We identified recurring complaints about delivery times, so we recommended revisiting the shipping policy with the logistics provider.
- Communication of technical issues in the app
Send in-app messages whenever the IT team detects technical issues so users are aware of the situation. These notifications should include an estimated resolution time, updates if delays occur, and confirmation messages once the issue has been resolved.
- Information about “levels”
User profiles in the app have “levels” based on certain KPIs. Moving up a level unlocks improvements such as better conditions or additional discounts.
Through the analysis of reviews, we discovered that users wanted more visibility into how close they were to reaching the next level. We therefore proposed a system that shows progress toward the next level, including the current KPI values and how much is required to “move up”.
Implementation Roadmap for Recommendations
After the client approved the implementation of these recommendations, we evaluated them using an effort/value matrix and developed a roadmap based on the expected impact of these improvements on the app.
The roadmap will begin on March. From Relevant Group, we will share the results we achieve after implementing these recommendations.
