Use case
Social media data
Engagement rate, not follower count.
Follower count is the number people buy on and it predicts very little. Engagement rate, growth shape, and posting cadence predict considerably more, and all three require data over time rather than a screenshot.
We track the accounts, hashtags, and sounds you care about across platforms, compute the metrics that matter, and deliver them as a series you can compare.
Outcomes
What it is actually used for.
Each of these is a build we have scoped. They share the extraction and differ in what happens to the data afterwards.
- 01Influencer vetting on engagement rather than follower count
- 02Detection of bought-follower patterns from growth shape
- 03Competitor content and posting cadence tracking
- 04Campaign measurement across a hashtag or creator set
- 05Trend and sound detection while it is still accelerating
- 06Share-of-voice against a named competitor set
Platforms
Sources that feed social media.
Most builds combine two or three of these.
Deliverables
What you get.
- 01Profile and post records with computed engagement metrics
- 02Follower and view movement between runs
- 03Hashtag, sound, and keyword tracking
- 04Comment text where in scope
- 05One schema across platforms so comparisons are possible
- 06Delivery into your warehouse, sheet, or reporting tool
Questions
Asked before.
Can you tell us if an influencer's audience is fake?
We give you the signals — engagement rate against reach, comment-to-like ratio, growth shape, and cadence. Step changes in growth with flat engagement are the usual tell.
Can you compare across platforms?
Yes. Records land in one schema, so an Instagram and a TikTok creator can be assessed on the same basis.
Next step
Put social media data to work.
Tell us the outcome you are after and the market you operate in. We will come back with the sources, the fields, the schedule, and what it costs to run.