WEBINAR DETAILS

How manufacturers and NPD teams can act on early trends before they go mainstream, using early singals from successful new product launches to prove every call.

Most trend forecasts are an expert's opinion: a confident narrative, printed once a year, impossible to audit, and stale before it reaches your desk. Gravel Early Trends inverts the model. Every trend is clustered upward from thousands of real successful new product launches - their descriptions and full INCI lists - so every number clicks through to the exact products and ingredients that prove it.

In this session, Gravel AI co-founder Karen Ho walks through the live platform: how canonical trends are built from evidence, how emerging product concepts surface from real co-launch patterns, and how any brand's portfolio and recent launches can be read against the market in minutes - objectively, with the proof in front of you.

What you'll learn (concrete takeaways)

· Why "early" is the point — how to spot a trend forming in new launches before hype and mass adoption, and what that's worth to R&D and commercial timelines.

· Evidence over opinion — see a canonical trend opened to its granular signals, sample products, and highlighted INCI/description evidence — auditable, not asserted.

· From trend to concept — how emerging white space and the ingredient kit to serve it are pattern-mined from how trends actually co-occur in products.

· Brand vs Market in minutes — read any brand's whole portfolio and recent launch trajectory against market trends, three share lenses per trend, pure data — no recommendation, no spin.

· How it stays honest — the monthly refresh, the map-or-flag taxonomy (no hallucinated or single-brand trends), and why every figure remains traceable over time.