Been diving into sentiment analysis for our app’s messaging and roadmap.
What creative implementations have you noticed? There seems to be more potential than just analyzing reviews, but I’m curious about actual cases that impacted metrics.
Ran sentiment analysis on our dating app’s onboarding feedback. Users kept hitting “overwhelmed” and “confused” on the first 3 screens.
Stripped signup down to email and photo only. Everything else happens after they see matches. Completion rate shot up from 34% to 52%.
Did the same with app store reviews, breaking down sentiment by feature. Users loved instant chat but hated photo approval wait times. Built auto-approval for basic photos and only flag suspicious ones for manual review.
The trick was connecting sentiment to specific actions instead of looking at general feedback. Way more useful than those broad sentiment scores.
Pay attention to when you send push notifications. Testing different times can show big differences. We found mornings worked best for us. It increased engagement by a lot. Avoid busy times like evenings if possible.
I track sentiment in support tickets to spot which features frustrate users the most. Complaints spiking during onboarding? That’s where I focus dev resources. Running sentiment analysis on social media also helps identify unclear marketing messages. We found our value proposition was too vague, which hurt sentiment every time we launched campaigns. The biggest win was analyzing user feedback by cohort. Users complaining about pricing complexity had 40% lower lifetime value. After fixing the pricing page copy, conversion increased by 23%.
We dig through chat logs looking for words that signal when customers are about to bail.