ChatterboardAI sentiment analysis platform case study
A web app scoped, designed, built and launched for its founders: real-time sentiment intelligence from the comments under social media ads, turned into actions teams can take.
Engine
02 — Intelligence
Product
Web app — SaaS
Model
Consult to launch
Core loop
Comments → actions
The brief
The comments under your ads are the earliest, most honest feedback a brand gets (confusion, complaints, praise), but nobody reads them at scale. The founders came to us to turn that noise into intelligence.
The build
Noise in. Action out.
01 — Scope
Consult & scope
The idea pressure-tested with the founders into a buildable spec: what signals matter in comment data, and what a team actually does with them.
02 — Design
Design the intelligence
Real-time dashboards of sentiment trends, confusion spikes and complaint alerts that tell teams what to do next.
03 — Ship
Build the engine
The full web app built and shipped, tracked in Yamada. It runs sentiment analysis across ad comments at a scale no human team could read.
04 — Support
Launch the loop
Launched and supported since. Content teams answer confusion before it costs sales, and complaints surface in the comments, where they start.
What it does
Built to act on, not admire
Live
Real-time sentiment reporting
First
Complaints caught at the source
Loop
Feedback turned into content
Services in play