5 Min Read
Boosted App Rating from 3.8 to 4.5 via Strategic In-App Rating Flow
Addressing a low ★3.8 Play Store rating, I designed an in-app feedback flow using user-centered principles. By directing satisfied users to public reviews and others privately, we raised the rating to ★4.5, demonstrating how design can drive real business results.
1. The Business & User Problem: A Disconnect in Satisfaction
Our app's average rating on the Play Store was 3.8 stars. This was a significant issue for several reasons:
Acquisition
Low ratings deter potential new users from downloading the app.
Credibility
A sub-4-star rating can signal quality or trust issues to users and partners.
Feedback Skew
We suspected that many happy users weren't leaving reviews, while unhappy users were more motivated to go to the store to complain about specific issues (often bugs or edge cases we were already aware of).
The core user problem was that there was no easy, timely, and appropriate channel within the app for users to provide feedback, especially positive feedback, in a way that could influence the public store rating.
2. The Strategic Goal: Turning Happy Users into Advocates
Our primary objective was to design an in-app experience that would:
Capture feedback from users within the app context.
Encourage happy users to share their positive experiences through public reviews.
Offer frustrated users a private channel to voice concerns, avoiding negative public reviews driven by emotion.
Boost our Play Store rating to accurately reflect real user satisfaction.
3. Research & Hypothesis: Why 3.8?
Before designing, I needed to understand why the rating was low.
Review Analysis
Based on our analysis of existing Play Store reviews, I categorized feedback themes such as bugs, missing features, poor onboarding, and specific frustrations. This analysis confirmed a pattern: Users are often motivated to leave reviews when they encounter a problem.
User Surveys
I asked users about their past experiences with rating apps and what factors would motivate or prevent them from leaving a review.
Key insights:
The Power of Timing.
"It really depends on when you ask me to rate. I’m more likely to give feedback when I’ve just had a good experience."
The Risk of Direct Routing.
"If I’m already frustrated, sending me straight to the app store just makes me want to leave a bad review."
The Need for Speed and Simplicity.
"I’ll give a rating if it’s quick and doesn’t interrupt what I’m doing."
Capturing Direct, Actionable Insights.
"I’d rather give feedback in the app if it’s easy, not just rate it publicly."
How-Might-We Statement
I translated our findings into actionable design goals by reframing challenges as How Might We (HMW) questions. These guided the design process and kept us focused on real user needs. To ensure a holistic view, I categorized them by Thought, Feeling, and Action.
Hypothesis: Implementing a well-timed, two-step in-app rating prompt – first capturing sentiment internally, then directing positive users to the store – would increase the volume of positive store reviews and reduce negative ones, thereby raising the average rating.
4. Design Process & Solution: Crafting the Feedback & Rating Experience
Working closely with the Product Manager and Engineers, my design process focused on creating a smart, multi-stage feedback capture system:
➤ Flow Mapping
Defined the ideal user flow, starting with an initial prompt, branching based on user input, and handling different outcomes.
➤ Initial Concepts & Wireframes
Explored UI patterns for the initial prompt, opting for a direct star rating input as it's a familiar pattern and provides immediate, quantifiable sentiment.
Key Design Decisions & Rationale
➤ In-Moment Experience Rating
Show a 1-5 star rating in a modal right after positive user moments (explained in flow mapping) during high engagement to capture immediate feedback when their experience is fresh.
Rationale:
This provides immediate and feels like a natural way for users to express their satisfaction level. It’s a lower cognitive load than a Yes/No for many users and sets the stage for capturing why they rated that way.
➤ Conditional Branching based on the star rating provided:
↳ If 1-3 Stars
Users are presented with a follow-up screen asking, "How can we make things better?" This feedback is submitted directly to our internal systems.
Rationale:
This intercepts unhappy users before they go to the public store. It gives them a direct channel to voice frustrations where we can address them, often defusing negative sentiment and preventing a potentially harsh public review. It also provides us with specific, actionable negative feedback data.
↳ If 4-5 Stars
Based on Google's regulations, we cannot customize their rating display. As an alternative, clear copywriting is provided to users so that the in-app rating, which allows direct input to Play Store, is triggered and appears.
Rationale:
The rating data is automatically recorded internally. Clear copywriting helps guide the user to the next action. The native in-app rating from the Play Store also reduces the steps needed compared to them manually opening the Play Store.
➤ Capped frequency & simple opt-out; lean, usable interface.
Show simple rating requests at good times and don't bother users if they dismiss them, making it quick and easy to share their thoughts.
Rationale:
To avoid bothering users and potentially causing negative feedback, we limit how frequently rating prompts appear and respect their decision to dismiss them. By using clear and easy-to-understand screens, we make giving feedback quick and effortless, which encourages more users to participate.
5. The Impact: Quantifiable Success
The results post-launch were significant and exceeded expectations:
Our average Play Store rating increased from 3.8 to 4.5 stars within 3 months of the feature's full rollout.
We saw a 42% increase in the volume of new Play Store reviews, with a significantly higher proportion of 4 and 5-star ratings.
We captured valuable direct feedback from users who rated us negatively in-app, providing our team with actionable insights for product improvement without negatively impacting our public rating.
6. Learnings & Reflection
This project powerfully demonstrated how solving a business problem (low rating) could be achieved by deeply understanding and designing for the user's feedback journey.
The two-step filtering mechanism was key to directing positive sentiment publicly while capturing negative sentiment privately for product improvement.
Timing and context are paramount for in-app prompts; a poorly timed prompt can be detrimental. Close collaboration with data was essential here.
Small, well-executed features can have a massive impact on critical top-level metrics like app store ratings and acquisition.
