AI-powered app review intelligence
Custom NLP and embeddings that classify app-store feedback into product-specific themes—with prioritization tied to sentiment, volume, and user-behavior impact.
80%
Faster feedback analysis
Challenge
High volumes of app-store reviews made it hard to extract actionable insights. An existing external tool could not capture product-specific issues, producing generic findings and forcing manual review—so teams prioritized poorly and missed drivers of experience, retention, and growth.
What we did
FocusKPI built a tailored AI solution using NLP and text embeddings to classify sentiment and map feedback to detailed, product-specific themes, delivered through a production interactive dashboard. A prioritization framework combined sentiment intensity, review volume, and impact on user behavior. Product and engineering feedback continuously refined the model, and insights were embedded into analytics and sprint planning.
Results
Reviews became actionable insight. Teams resolved high-impact issues faster, improved ratings and retention alignment, and continuously sharpened accuracy through internal feedback.
“This is exactly what I was looking for…we will use these insights to ensure our product and engineering resources address our customers' issues…this allows us to be more customer-centric and smarter with our investments.”
Why it worked
A rigid external tool was replaced with a model tuned to the product experience and wired into existing product workflows—so impact showed up in planning, not only in a report.
Discuss a similar engagement
We typically start with a scoped proof of concept before production deployment.