Views from the Hills by R. E. Stevens, GENESIS II (The Second Beginning) E-Mail views@aol.com

The Disposable Test Market (DTM)

Something needs to be done. We are spending too much time and money introducing market failures to the public. Over recent years, we have seen new products fail at a rate of 90% in the first 12 months of their introduction into the marketplace. That means that this year alone there will be approximately 16,000 product failures placed into the market.

It is only when the brand is placed in the market that the truth of success is really known. The Disposable Test Market (DTM) is an economical diagnostic market in miniature.

The DTM has been developed to replace Simulated Test Markets (STMs) that have played an important part in the introduction of those market failures.

STMs use simulated store shelves, in small rooms, seed money and verbal purchase intent. The DTM uses Real Stores, Real Shoppers, Real Money and above all Real Purchase Data.

Reality, not simulation, leads to better business decisions.

DTMs are cost competitive with STMs and much less costly than test markets. STMs draw their conclusions from a base of 300 households while the DTM method utilizes 2,000 households.

"Assessment in Context" for better decisions Into the Future

Last Friday, July 29, 1994, a meeting was conducted here in the Hills of Kentucky with the purpose to explore ways in which the DTM System could be enhanced now that Elrick & Lavidge has adopted the method as one of their lead services. Present at the meeting were:

Dr. Frank Bossu, Vice President, E&L Consulting Services
Mr. Gary Dispensa, Manager, Statistical Department, E&L Consulting Services
Mr. John Harris, Field Manager, E&L Consulting Services
Dr. Richard Fox, professor, University of Georgia "Masters of Marketing"
program and author of a new consumer/marketing research book to be
released this summer. and this retired old man

The meeting was long, very active and rewarding. I look forward to the updating of my method developed in the early 1980's especially in the year one forecasting model. More on the progress to follow. 


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