Virtual Conjoint

What Drives the Purchase Decision?

In developing a new product or reconfiguring an existing one, there are many combinations of variables (benefits, size, price, etc.) and ultimately, business choices that must be made that could dramatically affect marketplace outcomes. Decision Insight’s Virtual Conjoint research provides a systematic way to understand the optimal combination of variables and predict marketplace demand. Using Virtual Conjoint, we can test hundreds – even thousands – of concepts and combinations. This method determines how important each feature is to shoppers and the preferred combination – enabling major product innovation instead of minor iteration.

Shoppers are often eager to share what product they would buy from a group of options, but it’s difficult for them to articulate why – or what variables are driving their purchase decisions. Using a discrete choice design with advanced analytics, this proprietary approach applies the principles of shopper marketing to test product development, packaging, pricing, merchandising, and product placement solutions. In essence, Virtual Conjoint can effectively predict the market impact of potential product or pricing changes.

DI’s Virtual Conjoint approach is an effective tool to understand:

  • What are the appropriate price/size combinations for my brand(s) to maximize revenue?
  • Which combination of packaging features (and associated pricing) best improves purchasing vs. current configurations?
  • Which bundle of features and benefits is strongest for a new product concept?
  • How will incremental price changes impact demand?

At DI we believe in “team.” Decision Insight’s strategic consultants and advanced analytics experts work closely with clients to identify the most critical testing variables for your product and category. Often, a virtual shopping component is added to Choice studies to make exercises even more realistic. DI provides a custom “market simulator” as a key deliverable that enables the client to create their own “what-if” scenarios and predict their impact on future purchases.

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