Yasna.ai
Yasna is an AI assistant for conversational research: collect facts, opinions, and ideas from any audience in any country or language.
This on-demand webinar is in partnership with:
Tanya Berlina, from Yasna.ai, talks of iterative early testing to reduce late-stage concept failure and improve validation confidence.
COMPLETE THE FORM TO WATCH THE VIDEO
Late-stage concept failure is often not caused by weak ideas, but by insufficient learning early in the process. Teams move into expensive quantitative validation with flat or reassuring scores, yet without clear guidance on what truly differentiates ideas or how they should be refined.
This session explores how an iterative, early-stage testing approach can help reduce risk before major investments are made.
Key topics covered:
- Why traditional early concept testing often leads to flat results and late-stage surprises.
- How iterative testing turns validation from a one-off checkpoint into a continuous capability.
- How AI-moderated, one-to-one interviews at scale combine qualitative depth with quant-style confidence.
- How teams gain clear refinement directions and deprioritise weak ideas before costly quant validation.
Drawing on real FMCG innovation examples, the session demonstrates how early, iterative testing helps teams move faster, align earlier, and enter large-scale validation with greater confidence.
Speaker
Tanya Berlina
Tanya Berlina is the Research Director for Yasna.ai. She has over 20 years experience in qualitative market research.