A Consumer Brand

01 / The challenge

Start with the real problem.

The marketing team relied on manual spot-checks of social mentions, often missing sentiment shifts until they'd already become a bigger issue. There'd been a couple of internal attempts to address it by them already.

02 / The solution

A system built to fit.

I built a monitoring pipeline that scores sentiment across mentions in near real time and alerts the team when sentiment shifts sharply.

1. 01

   Kicked off with a series of short conversations with their team to understand the workflow the new system would actually need to fit into.

2. 02

   The first working version for Consumer Brand came together quickly using Python, which left more time for testing edge cases in their data.

3. 03

   Ran the first version alongside Consumer Brand's existing process for a few weeks rather than replacing it outright, to build confidence before full cutover.

4. 04

   Set up basic monitoring so Consumer Brand's team would know quickly if performance started drifting, rather than finding out from a downstream complaint.

03 / The results

What changed.

• Cut time-to-detect a negative sentiment trend from days to hours
• Gave the team a single dashboard instead of manual searches
• Covers social mentions and review platforms alike
• Set up with basic monitoring so thier team would catch any drift early, not after it became a problem