In most companies product development concepts are tested on their market potential before going into market. Since many marketeers (and their bosses) heavily rely on the test-results for giving green light to continue with the next phase, it is important to understand how this testing actually works.

In more than 50 percent of the cases BASES-testing is used. BASES is the Simulated Test Marketing (STM) tool suite of Nielsen and contains a number of STM tools. The concept screening tool BASES SnapShot is the most important tool for the evaluation of New Product Ideas, line extensions and relaunches. In SnapShot each concept is assessed on the basis of key parameters according to a secret black box algorithm. The Concept Potential Score (CPS) summarizes the results and indicates whether the concept goes into product development or not. The CPS is based on four criteria which should be considered in the development of successful design concepts: (1) Value Rating, (2) Purchase Intent, (3) Purchase Frequency and (4) Purchase Volume. However, some difficulties arise in the use of this criteria, if we analyse it with current knowledge from Marketing Science:

  • Value Rating indicates the degree to which consumers are convinced that the product (better) satisfies a need for a fixed price. The parameter does not provide any levers for optimization of the design. However Marketing Science provides test formats that analyse the transformation of subjective value and the probability in choices (see The Prospect Theory for more details). This approach could provide insights into how products and communication need to be framed to optimize the evaluation in terms of losses and gains. Other important points, which are not addressed with this Nielsen parameter are distinctive assets, the creation of attention and the building / refreshing of memory structures and shemata. Considerering this aspects would lead to a better evaluation of the product (→ retrieval bias effect).

  • The key figure Purchase Intent reflects the expected probability that a first purchase is made. However due to Marketing Science there might be a discrepancy between the forecasted and the actual buying behavior. This can be reduced by an improved measuring scale. For example, the 11-point Juster scale measure, which measures the probability of purchase, delivers more accurate results. Nevertheless, future behavior can be predicted only conditionally. The measure also provides no information about the cause of (non-)purchase and therefore no levers for design optimization. The Theory of Planned Behaviour (TPB) examines the variables that influence purchase intent. At the category level they can analyze why a category is liked and thus provide valuable knowledge for product design, development and advertisement themes.

  • Purchase Frequency indicates the expected frequency with which a product is purchased. This ratio is a loyalty measure as it represents the number of repeat purchases. This means it follows the Double Jeopardy Marketing Science Law and is therefore dependent on the size of the brands market share.

  • The key figure Purchase Volume predicts the expected number of items per purchase. However, fluctuation in sales volume based largely on sales promotions and seasonal variations (e.g. holiday season, bank holidays) and generally have little impact on long-term sales figures or loyalty.


To conclude, the Nielsen SnapShot criteria do not include current knowledge of Marketing Science and are only adding limited value for optimizing the design. However since BASES-tesing is used in over 50 percent of the companies it is difficult to work around it. The consideration of the SnapShot criteria from the perspective of Marketing Sciences leads to three relevant questions for the product concept development:

  • What do consumers really appreciate of products in the category (→ Theory of Planned Behaviour)?

  • What encourages consumers to try out the new product and what are the purchase barriers (→ Prospect Theory)?

  • What creates distinctive brand assets and builds or refreshes memory structures (→ Brand Salience Theory)?


Nielsen’s BASES-testings predict whether innovations have the potential to be successful in the market. The innovation database by Nielsen reveals that concepts that are judged potentially successful in the market are concepts that try to address real consumer (and/or currently unmet) needs. According to Nielsen, success is based on ‘demand-driven innovation’, with proper execution being more important than the concept itself. This means a well executed but mediocre concept is better than a brilliant concept with mediocre execution. This leads us to the question: How are succesful executions measured? Nielsen defines 12 success criteria for the testing of initiative and innovation executions. These criteria are summarized in the STM tool introScape:

The 12 criteria provide a good insight into how Perceived Value (at a price) and Purchase Propensity (Likelihood, Frequency, Volume) can be broken down on the Path-to-Purchase. An interesting aspect is the high emphasis on attractiveness (need / desire to benefit, credibility and acceptable disadvantages) and communication (communication link, clear / precise message). The STM tool introScape can easily be translated into design briefing criteria. In terms of testing the use of brand assets for building brand salience (also for building design languages across the portfolio), the criteria need to be further optimized. The success criterion findability is very unprecise, as it summarizes the findability of the point-of-sale, the correct section at the store and the place in the shelf. For testing new business model concepts the aspect route-to-consumer needs therefore more precise criteria.