Product Component Optimization: Finding the Ideal Combination
Savvy marketers know that when it comes time to put all the components of a new product together, consumer insight is valuable.
But, the savvy researcher knows that traditional monadic testing of each individual component is not only time consuming and expensive; it doesn’t take into account interaction effects among components and provide that critical holistic view.
Whether optimizing the components of a new or reformulated food or beverage (when RTi can actually include taste as one of the components tested) or fine-tuning the value proposition of a new banking product, RTi researchers are experts at leveraging choice-based techniques and modeling to provide quantitative guidance in the early product development stage.
- Adaptive Conjoint (ACA) — handles a large array of components
- Discrete Choice (CBC) — closer to real purchasing, and handles price well
- Adaptive Discrete Choice (ACBC) — handles a large array of components, offers component level pricing and can replicate real purchasing
Oftentimes, RTi designs a Component Optimization test so that it incorporates a full product test, eliminating the need for additional research later and reducing our client’s research spend. And adding to the ROI, we provide a powerful and highly user-friendly simulator
. It’s so simple to use that what-if scenarios can be input and run during meetings, and powerful enough to automatically determine and display the optimal bundles among any identified subgroup.