Prediki PROMPT

Predictive Research for Online Market and Product Testing

Context for PROMPT

Prediki PROMPT is usually applied alongside some sort of formalized product development methodology, such as a stage-gate system or a design-thinking approach. Whenever these processes call for a user-centric input or a prototype test, possible users or target groups can be asked to predict the future of the current state of an idea.

A product developer can use the usual action standards (liking, differentiation, relevance, etc.) or ask respondents to rate the new product or variants for the very attributes it is designed for. For communication concepts or advertisements, a LURE prediction pattern (an acronym for Liking, Understanding, Relevance, Effectiveness) works best. The key purpose of attribute questions is simply to put each respondent into a holistic frame of mind, to look at the innovation from multiple relevant perspectives. The prior existence of a normative database for these attributes does not matter.

The remainder of the context required for participants is produced through prediction questions about the targeted sub-segment’s future development and about a future KPI of a key competitor. These questions establish the relativity of the various needs and desires of the new product’s category in participants’ minds. They produce authentic insights about that competitor’s strengths and weaknesses and about general trends affecting the target market, as seen by the community. At the same time, the resulting predictions can be used to assess the precision of their collective forecasts - by comparing short-horizon forecasts to real world results - even before the new product has seen the light of day.

The learning effect from feedback about each participant’s earlier predictions further increases the accuracy of the method as the new product progresses along the development stages. Once context is thus established and trained, the respondents can be exposed to monadic prediction questions asking for each new product variant’s likely success, expressed in the same KPI as used to forecast competitor’s success.

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