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strategy and business
 / Summer 2012 / Issue 67(originally published by Booz & Company)


Rethinking the Product Launch

Businesses try to avoid these failures, of course, by applying ever more sophisticated techniques for testing the customer value proposition of a new product or service. These methods include surveys, focus groups, and conjoint analysis (the use of statistically weighted surveys to compare combinations of product attributes). But customer value proposition efforts can fall short for any number of reasons. Sometimes the wrong research method is used: for example, conjoint analysis where rapid prototyping would be more appropriate. Sometimes the right statistical method is used, but it is misapplied. Sometimes the results of the research are not considered in the context of the brand’s existing position, the market realities, or the would-be innovator’s capabilities system. And at times, good ideas fail because of problems in execution.

Creating a successful customer value proposition takes intuition and experience, but the odds of success go up if a structured process is applied. This process should bring together the three practices of market-back analysis, Darwinian competitive review, and capabilities-forward assessment.

Market-Back Analysis

Actions speak louder than words, but all too often, market research merely asks for words; it simply questions consumers about their attitudes, likes, and dislikes. Instead, the focus should be on understanding consumer behavior: for example, the trade-offs consumers make when considering a purchase, and the factors that drive them to switch brands, products, or channels.

One way to gain this knowledge is to marry data from surveys — explorations of individuals’ preferences and expected future behaviors — with information about their actual behavior. This has the advantage of grounding what people say with insight about what they do. Another approach is to develop statistics-based research on product options: either conjoint analysis or one of its variants, such as maximum difference analysis. This technique presents consumers with a series of feature and price bundles and infers from their choices which product attributes or features are most important to them. A third approach is to create simulated shopping experiences, which mimic as closely as possible the choices that consumers face in the real marketplace.

These analyses can become the basis of customer segmentation, allowing you to focus on specific groups of customers on the basis of their priorities and price sensitivity. Consider: Who are your target customers? Which attributes and product features matter most to them? Where is your “headroom” — the best opportunity for picking up customers and market share? What would it take to get customers of other providers to switch to your products or services?

For this article, simulating an analysis for Wendy’s, we surveyed a group of potential quick-service restaurant consumers, asking them what attributes they most value in their fast-food restaurants. The patterns of consumer preferences identified by the analysis sorted naturally into five distinct segments, as noted earlier:

• About 21 percent of survey respondents ranked convenience and familiarity as important attributes. Members of this segment are looking for a pleasing ritual and don’t want to be surprised.

• About 19 percent of respondents mentioned price affordability and convenience as valued attributes. This is the price-sensitivity segment. Its members also tend to favor delicious food and perceived healthiness, so long as it doesn’t cost too much.

• About 18 percent of respondents are interested only in convenience. No other attribute receives an above-average mention from them. They focus on the quick in QSR.

• About 16 percent of the respondents cared most for pure indulgence. Within this group, more than half rate delicious food (in general) and taste (of the hamburger itself) as important attributes.

• The last category, I want it all, encompassed only 10 percent of respondents. Unsurprisingly, they ranked nearly all the attributes highly. More than half of them valued taste, delicious food, and being familiar with the store; more than 75 percent valued perceived healthiness and convenience. The only low-ranked attribute was price.

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  1. Ken Favaro, David Meer, and Samrat Sharma, “Creating an Organic Growth Machine,” Harvard Business Review, May 2012: Toward an expansion strategy, building on these techniques and more.
  2. David Meer, “A New Way to Gain Customer Insights,” s+b, Spring 2012: More detail on conjoint analysis and its use for organic growth.
  3. Maureen Morrison, “How Wendy’s Found Itself, Slipped Past BK Into No. 2 Spot,” Advertising Age, Jan. 9, 2012: Recent in-depth story about the chain’s revitalization.
  4. Corey Yulinsky, “Making Customer Segmentation Deliver,” s+b, Winter 2011: A four-step process for making segmentation drive improved performance using sophisticated data.
  5. For more thought leadership on this topic, see the s+b website at:
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