AETA Case Study Baileys Mini Case Study Beck's Gold Case Study Beck's International Case Study Birds Eye Case Study CMA Case Study Coca Cola Zero Case Study DYMO Case Study Efasit Case Study Enzym Lefax Case Study Hasseröder Case Study Heinz Green Ketchup Case Study ibutop Case Study Iglo 4 Sterne Menue Case Study Kathi Case Study Landliebe Case Study Langnese Cremissimo Case Study Lefax Case Study Leitz Case Study LEKI Case Study MC Iglo Case Study Milka Case Study Moet Case Study N-Ergie Case Study Niederegger Case Study Nivea Case Study PerfectDraft Case Study Sheba Case Study TV Hören und Sehen Case Study Verpoorten Case Study Vorwerk Case Study WD-40 Case Study WD-40 Smart Straw Case Study WeightWatchers Case Study Wrigley´s Extra Case Study


Despite significant scientific progress and increasing attention to new product development (NPD), the new product success rate has not really improved in the last 50 years. One of the challenges in marketing research is the forecast of launch and relaunch successes and failures. Only 6 per cent of all new products launched become a greater success. – 94 per cent do not. – 73 per cent of all new product introductions end as flops within their first three years of existence.  The cost of these failures in the U.S. market alone is estimated to be well over $100 billion annually. The same is likely to be true across Europe.

Only a limited number of marketing researchers are aware that reliable predictions of new products market performances are possible with a relatively small number of respondents. The sequential analysis has been developed in the US and has been a top military secret for some time.The advantage of the sequential analysis that it allows significant tests with a low number of respondents (often 30 respondents are sufficient).This is an important benefit if the interviews are expensive, if only a limited number of test products are available or the research budget is small.The sequential analysis is often called “significance trouser” because its graphical design looks like a pair of trousers. In the areas which are outside of the “significance trouser” the results get significant (chances for error 0.05).

When Coca Cola Zero was launched in Germany we decided to conduct a validation study. We wanted to check the predictive power of the “significance trouser” in combination with our brand choice criterion. We purchased the first available Coca Cola Zero products in Germany. 76 qualitative interviews with Cola light product category users were carried out. 44 (= 58%) were interested in product trial and used Coca Cola Zero in a home use test. A second interview was carried out after home use.

In 16 of 44 cases (= 36%) Coca Cola Zero was preferred after home use.The prediction is done under ideal marketing conditions (100% awareness, 100% distribution, 100% product trial interest) and therefore has to be calibrated with real market values (awareness and weighted distribution). The prediction proved to be reliable. Only small deviations of the predicted market share to actual figures were observed. Coca Cola Zero became a large success in Germany - as predicted.

The Heinz and WD 40 case studies show other validations of the “significance trouser” in combination with our brand choice criterion.

Methods used: 30 explorations, analysis using the „significance trouser“ method and the $ales Effect brand choice criterion.