Case Study: Sampling Analysis
Sales reps are an expensive and inefficient means of sampling upper level course texts. From analyzing sampling data for several large clients, we know that sales reps are missing on average 50% of the market with their comps, while oversampling by at least 50%.

CMOS VLSI Text Sampling Analysis
*based on an actual report that was provided for a major publisher

Quantity Sampled by Publisher
Number of faculty teaching from CMOS textbooks in TWM Database within 3 years
Samples by Publisher confirmed in TWM Database
Samples by Publisher not confirmed in TWM Database
(potential wasted comps)
% of Qualified Adoptions sampled by Publisher (231/400)
% of Qualified Adoptions not sampled by Publisher (169/400)
% of Publisher Samples confirmed by TWM as accurate (231/1,280)
% of Publisher Samples potentially wasted (1,049)

Potential $$ Sampling Budget Wasted (1,049 x $10* per sample - $10,490)

* includes unit manufacturing cost of the sample plus shipping/handling.

Note: The $10,000 in potentially wasted comps is just the beginning. Most publishers retain the names of professors sampled for internal mailing lists for future mailings and promotions. In addition, many publishers send follow-ups to professors receiving sample copies. Finally, many inaccurate samples end up in the used textbook market, where the cost to the publisher in lost sales is significant.


TWM Sampling Solution
If a professor does not have a review copy of your title, you have a 0% chance of getting the adoption. If you could ensure that every sample went to a professor teaching from a competing text within the past 1, 2 or 3 years, wouldn't that solve your sampling problems?

TWM develops small, targeted, up-to-date mailing lists that its clients use to auto-sample upper level technical, computing, mathematics and physics titles.