Analytical model for Lead Qualification

Once that the product have been design and finished. Would you like to know how probable a given prospect will buy your product before investing sales efforts in this prospect? Would you value the information of knowing an estimate of the proportion of people with high probability of buying your product in a given segment?

The Logistic Regression allows you to classify a person or entity into groups based in their characteristics. For many marketing problems, these groups are buyers and no buyers. In the case of the sales department, they usually have a group of leads that may have shown some interest in the product. However, they may want to contact only those with higher probability of buying given the characteristics of the company.

On other hand, the marketing department may want to evaluate the proportion of potential buyers for different segments to assign marketing resources.

The Logistic Regression also allows you to know the relative weight of the characteristics that we take into account when you classify the prospects. Lets think about the following example: product, ready to eat pork that only needs to be warmed up. One variable that will determine the buying decision is the occupation of the consumer. Those consumers more busy with work will look for products that can be cooked faster. Member of certain religions won’t buy the product. What about people with fitness awareness. Will they buy the product? May be the pork has more fat than other meats, but they still value the flavor. And what about people with health conditions. In this case, the fat may have more influence in the decision. With the logistic regression we intent to give a weight to these and other variables, add them to the evaluation and get a conclusion about the probability of buying the product.

The formula for the model is the following: … (to continue reading, please buy the post for $3. Follow the link to Buy it Now)