Test Market Simulation (TEMASIM)


We support you with established tools that can be used even before the test market phase for existing product alternatives / substitutes, in particular for fast moving consumer goods (FMCG). The scientific fundamentals are based on the models of Parfitt/Collins, Markov, Silk/Urban.


TeMaSim is the classic method for market share forecast with measurement of purchase behavior and preferences, including market share calculation scenarios. The model emphasizes the modeling of first and repeat buyers. The model focusses on consumer goods whose regular purchase is critical for the product’s success.


With TeMaSim market shares for new products, line extensions and existing products with new marketing scenarios (like, for example, new communication, changed prices etc.) can be predicted.


The method predicts a product’s the long-term market share by combining two calculation models, the Trial-Repeat model (first and repeat buy) and the preference model, both of which generate separate market share forecasts. The long-term forecast is the median of the forecast value from both partial models. This is based on the assumption that the future market share of a new product consists of the first buy and repeat buy rate.

The Trial-Repeat-Model

The first buy rate (Trial) is a mix of the factors purchase probability (measured with a simulated test shelf or scaled, for example), brand awareness (=expected awareness), availability at POS (=distribution), as well as the probability that the customer will receive the product for free as part of a sampling and the probability that the customer will actually try it.


The repeat buy rate (Repeat) consists of the measured probability to switch from an established product to the new one and the repeat buy probability once the product category is chosen again.

Between the determination of the first and repeat buy rate is the use phase that takes place either at the test studio or at home.





The Preference Model

The preference model is based on data of paired comparisons of existing products and the new product.


The respondents select existing products as part of their product preference list (relevant set) before the “introduction” of the new product. This relevant set is then used for the paired comparisons. Generally, the relevant set includes all known and used products (main, side and substitute brands). In the next step, always a pair of products or brands, respectively, will be compared. Respondents distribute 11 points in a so called chip game among the products/ brands. Subsequently, purchase probability is determined using the arithmetic median.


The next step involves the respondents in a simulated purchase situation, in which they have to take or leave the new product. Those respondents that have chosen to buy the new product will now undergo the paired comparisons once more. This time, however, the new product will be included. Once again, purchase probability is determined.


The market shares of Trial & Repeat and Preference (Chip Game) are calculated separately first; thereafter, they are combined complementary into one market share.


The resulting market share is by definition based on 100% awareness and distribution since all respondents could see the communication and the product was readily available on the shelf. In order to get realistic estimates the results need to be weighed with awareness and distribution assumptions based of the experience of the client.


Of course it is possible to calculate different scenarios based on various assumptions of awareness and distribution.

The Conjoint Approach

A more sophisticated alternative to the test market simulation (TeMaSim) is the conjoint analysis (CBC):


In the framework of this approach market shares are calculated based on purchase decisions that have been identified in the conjoint approach (CBC).


Respondents have to express their purchase intention by selecting one (or none) out of several Choice-Sets consisting of predefined products (including price) of relevant brands (including competitors). Different retail price scenarios can be included in this step.


In addition, all relevant parameters required for calibrating and calculating market shares are compiled through a framework of questions.


Similar to the “classic” test market simulation…

  • Purchase decisions are made and measured both before and after introduction of a new product.
  • New products are introduced by communication, such as TVC, advertisements etc.
  • Competitor and test products are presented on the shelf including measurement of trial and repeat buys.
  • Test products can be sampled, for example.

Unlike the “classic” test market simulation, however, there is no chip game because preference is measured via Conjoint. This offers many cost savings in regards to possible variables in the marketing mix (e.g. prices, SKU sizes etc.).


Both methods guarantee a decisive business advantage! They prevent possible flops or faulty business strategies. To that effect they are demanding and complex projects:
Advertisements, package and products have to be market ready to a large extent. We ensure sufficient sample size for valid data on trial and repeat buy. Last, but not least the calculation of market share is done very carefully because decisive hints on “go” or “no go” are given.

Compared to a real test market both methods are much less time and cost intensive, less “public” and less susceptible to “disruptions”.