We Sell Everything in Software (WSES) Inc., sold innovative off-the-shelf products and had customers across the world. WSES specialized in providing software solutions for different industries such as defense, clinical research, consumer goods, capital markets, security, banks, retail, and insurance among others. Although the products were commercial off-the-shelf, many clients required personalization and after sales support which WSES was happy to provide.
WSES did not have a structured approach to take decision regarding chasing a sales lead. Therefore, it incurred pretty high marketing cost including their travel costs, client visits, time spent by the sales team/technical experts/support staff, and logistics costs; most importantly, this list excluded the cost of advertising, which in effect meant that the advertising costs were over and above the ones mentioned.
The marketing team had several beliefs about chance of winning a deal across different geographical locations, different domains, etc. However, none of these beliefs have been validates. Jack Williams, the CEO of WSES, was worried that despite having such a huge expenditure list, the sales conversion possibilities based on the pipeline was at best an ancillary information, as there was no substance in justifying ‘‘gut feeling’’. Thus, WSES engaged Liz with a Ph.D. in statistics to understand if they could determine a structured approach to check whether the beliefs of the marketing was in fact correct or not. Jack also believed that simple statistical analysis can help WSES with useful insights about sales conversion.
Learning Objective (Maximum of 500 Characters):
The case can be used as a resource for teaching statistical concepts such as hypothesis tests such as Z test, t test, proportion test, two sample t tests for proportion and mean, ANOVA, Pearson correlation, bi-serial correlation, etc. The case uses the context of sales conversion and can be used to discuss how statistical concepts can be used to derive insights in the sales and marketing context. The case can be used as part of courses such as quantitative techniques, data science, business analytics, and machine learning at graduate level.
 Names of all companies and individuals are changed to maintain the confidentiality