About 16,000 queries a day, structured on one schema, feeding the models global brands rely on.
A consumer trend prediction company that tells global brands what people will want next.
Industry: Consumer and Market Intelligence
The company tells global consumer brands what people will want next. Its models are only as good as the social data behind them, and that data had gaps: sources it couldn't reach, and data that arrived in different shapes depending on where it came from.
Every new source meant more collection code to write and keep running. That work sat on top of the modeling its customers actually pay for.
It started small, with one-off pulls to cover the sources its models were missing. Those pulls became scheduled runs. Today about 16,000 queries go out every 24 hours, across several languages, with no one kicking them off. Monthly historical backfills fill in the past.
The company already had its own data systems, built in-house. It adapted them to run on the Datastreamer schema, so every source lands in the same shape. Enrichment and structuring now happen inside the pipeline, before the data reaches its models.
About 75M posts a month now flow through one pipeline, cleaned, enriched and structured. Adding a source means adding a component to the pipeline. What began as a way to fill gaps is the data layer the business runs on, and its data team spends its time on predictions.
Bring the sources you're missing into one pipeline, structured the way your models need them.
Used by market-leading intelligence platforms. Supported by a dedicated success team.