(hopefully!) communicates the intended end-user benefit. In more elaborate variants on this theme – which we recommend – one creates a small suite of concept statements or visuals that are crafted to intentionally vary the highlighted functionality and potential end-user benefits. These concepts are then presented to prospective customers/end-users for preference evaluation either singly or in rotation depending on the assessment methodology. Following Ries’ diagrammatic format, a concept test feedback loop might look like that presented in Figure 3.
Well-defined alternatives. When presented with these clearly defined alternatives, target customers can readily tell you which ones they prefer and why they prefer them. In a very real sense, these alternative concepts statements represent alternative descriptions of a possible future – a future that includes the envisioned new product, but viewed from differing functional and emotional perspectives. Asking respondents to compare alternatives and indicate a preference is the psychological underpinning of most product development research including conjoint measurement techniques. The comparisons can be structured as either qualitative or quantitative assessments
The Concept Assessment Feedback Loop Ries correctly emphasizes that the MVP must be testable from the customer/end-user’s perspective: do they understand it; can they use it; would they prefer it over existing options? Ries also mentions the need for eventually trying to sell a version of the MVP to potential customers – a process he labels as “the smoke test.” (Ries, 2011, p. 118) This is exactly what a well-crafted concept test is designed to do: test whether the target customer understands the offer, whether they know what to do with it and whether he/she would consider buying it (and at what price). Most importantly, a well-crafted concept test builds in diagnostics, something that is generally lacking in A/B testing. Diagnostics are designed to answer the “Whys?” (and the “Why-nots?”), such as: “Why did the majority of target customers prefer Concept B? And why did they reject our preferred option, the presumed slam-dunk Concept A?” The diagnostics provide clear direction for concept refinement: they are an essential element of a well-crafted concept test.
This feedback loop starts with identifying a potential opportunity, either through previous experience in the market, research or entrepreneurial inspiration. The next step is to specify the needs of the target customer: create the “customer archetype” that humanizes the process by identifying the lifestyle, the hopes and the needs of the category participant that we want to engage with our new offering. Testable concepts are then developed as a series of product/service descriptions that both address the potential business opportunity and respond to the specified needs of the target customer.
As we will demonstrate with the “Build-Measure-Learn” feedback loop, we can diagram a more complete representation of the concept assessment process; Figure 4 fills in the missing steps. Here, too, the process actually starts with a prior step: a qualitative category investigation possibly supplemented by other available data (e.g., Simmons, Nielson, custom panel study data, a syndicated report, etc.). The insights gained from this prior step are used to improve our understanding of the category dynamics and to sharpen our perception of the business opportunity.
We also can elaborate the final phase of the concept assessment loop. As is the case with an expanded “B-M-L” feedback loop, the final step in this feedback loop, the “Learn” node (here labeled “Revise Concept; Focus Direction”) is a decision point. Based on the analysis and the insights gained, the project team has at least three options:
- Identify a strong concept that provides the blueprint for an initial MVP and then enter Ries’ validated learning loop at the “Build” stage.
- Revise the current working concepts and re-enter the test cycle (the concept testing feedback loop) to seek further refinement.
- Acknowledge that the current approach will not meet expectations and then “pivot” in a new conceptual direction.
What customers want. Here, again, one learns “what customers want” through inductive logic and inference: studying preference patterns and their underlying drivers and allowing a holistic picture to develop. An agile product concept test can quickly identify the potential product features, attributes and benefits that will drive preference in a product category, thus providing a blueprint for the product development effort. This is possible even in a new category that is largely unfamiliar to the intended target group. (For an example, see the description of Qualitative Product Feature Optimization – q-PFO, on our website).
Qualitative, quantitative or combination assessment methodologies can be employed; the final choice depends on the time-frame, the level of finish that the concepts have attained and the decision-maker’s comfort with qualitative v. quantitative techniques.
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