Hamilton Marketing Services

In the Hamilton Marketing Services case, we have a full-service pet-grooming company that has hired a company called Hamilton Marketing Services (a major marketing consulting firm that helps provide a wide range of marketing and advertising services) to help them with their pet-grooming business. The pet-grooming company called in with an idea to either offer a flat $40.00 per visit price or a $30.00 per visit price if the pet owner signs up for a series of four groomings. The pet-grooming company has hired Hamilton Marketing Service to see which pricing option would be better. The pet-grooming company suggested to send out a two sets of fliers: one with the $40.00 listing price to a sample of 80 customers and another set of fliers with the $30.00 price and requirement for signing up for four visits to a different sample of 80 customers. The pet-grooming company will track the responses, log the data, and the Hamilton Marketing Services will analyze which is a better pricing model.

For this case, I will be figuring out how many total customers responded yes to both sets of fliers for the different pricing options. Then I will construct a 95% confidence interval for the two proportions of responses between the two options. Using the results from these confidence intervals, I will see if there is enough statistical data to determine which pricing model to use.

Analysis Page

I have attached the excel sheet with the data analysis.

Conclusion

The conclusion that we came up with is that for the pricing option 1 with the $40.00 flat service rate for grooming, the confidence interval says that we are 95% confident that the proportion of customers who would prefer the $40.00 option would be between 11.2% to 28.7%. For the pricing option 2 with the $30.00 rate with the requirement of four purchased services, the confidence interval says that we are 95% confident that the proportion of customers who would prefer the $30.00 option would be between 9.2% to 25.8%. Given the data from these confidence intervals, we can assume that since the two intervals overlap we do not have enough data to determine which pricing option is better for the pet-grooming company. There would be a major difference between the revenue generated between the two pricing options, the first option having 16 people say yes, which equals $640.00 in revenue, while the second option had 14 people say yes, which equals $1680.00 in revenue. The major difference does not signify anything important because there is no statistical data to say that those that purchased the flat $40.00 service would not continue to pay the $40.00 flat service in the upcoming months to equal four treatments.

The major issue with this analysis is that we did not send fliers to enough people and did not send both pricing options out in each flier. This means that we cannot determine if those that responded positively to the $40.00 rate would not have responded positively to the $30.00 for 4 services option as well. Without the having both options of pricing to choose from, the statistical evidence that we obtain will not have much meaning because we needed to see what the customer’s option would have been between the two pricing options or the option to say no altogether for us to obtain information that we can truly analyze. The recommendation that I give is that we redo the flier idea to a higher sample size, give both pricing options in the flier as well as the option to decline service altogether, then analyze that data in seeing which would be the best pricing option for the pet-grooming service.