Pricing & Promotions Research

Approaches

• Conjoint / Choice Modeling

  Machine Learning analysis of reactions to experimentally designed combinations of prices (and sometimes features), typically presented in a competitive context with consumer decision-making processes in-mind allows you to fine-tune your offering.

• Monadic Cell Testing

  Presenting consumers with your concept at varying price points allows you to assess whether a small price change will impact demand or large change will impact perceptions of your offering’s quality or value.

• Hybrid Testing

  Conjoint or choice modeling within monadic test cells allows you to compare the impact of going to market with very different pricing structures while optimizing your price under the winning approach.

• Sequential Monadic or Gabor Granger Price Testing

  Showing someone multiple prices for the same product lacks the brand equity insight and non-conscious precision of monadic cell testing; but sometimes the risk of a bad decision only warrants a modest research investment.

• Price Sensitivity Meter (Van Westendorp)

  If you want to set your price based on the quality perception you are trying to communicate, you can ask these classic four questions to guide you to the right neighborhood.

• A/B Testing

  When run on a small scale, in-market test-and-learn approaches can be relatively low-risk and highly effective, primarily for ecommerce and loyalty promotion applications.