Alienation Testing (IHUT)

Product changes — whether to ingredients, formula, packaging, or branding — can have real consequences for consumer loyalty. Highlight helps brands understand the risk before making a change that could drive away their most loyal customers. Through a robust, in-context quantitative evaluation, Highlight measures the true impact of a proposed change on current users and helps teams set data-driven action standards for moving forward.

Whether you use co-determined action standards or Highlight’s best practice formula rooted in consumer preferences and overall liking, you’ll walk away knowing exactly what the risk is — and what to do about it.

Key Questions Addressed

•     We are considering a product / formula / packaging change — is this going to alienate my current consumers? What will the magnitude of this change be?
•     What new product / formula / packaging should I institute that will minimize the impact on my loyal consumers?

Common Outcomes

•     Alienation impact — quantitative understanding of impact of product change on current consumers
•     Performance scorecard — relative metric performance of in-market vs new
•     Penalty analysis grounded in sensory metrics
•     Open-ended themes around reasons for performance — likes, dislikes, (if applicable, head to head favorite and why)

Methodology Guide

 Quick Hits

•     Quantitative
•     N=200+ (At least n=100+ first reads)
•     Sequential Monadic
•     ~3 weeks turnaround (ship to results)

Typical audience: current / lapsed users of the specific product being changed

For more information on designing your audience and sample size, see here.

Standard Inputs (Highlight Blueprint)

•         Overall Liking
•         JAR scales for key sensory / product attributes relevant to the change being made
•         Comment on Likes
•         Comment on Dislikes
•         Head-to-Head Preference (if applicable)
•         Purchase Intent

+ Can add from any of our available / recommended questions and/or write your own

Stimuli: physical product samples of both current and new product versions sent to participants, fully blinded

Standard Outputs

•         Alienation impact score — quantitative measure of product change risk among current consumers (see here for more details)
•         Performance scorecard comparing in-market vs new product across key metrics
•         Penalty Analysis grounded in sensory metrics
•         Summary of key themes from open-ended questions (likes, dislikes, preference rationale)
•         Data visualization for all survey questions
•         Crosstabs with customizable banners + statistical significance testing

Reach out to your Customer Enablement rep if you have any questions about leveraging Highlight for this use case!