Solutions

A medical information company sought a way to provide to device manufacturers lists of surgeons similar to their existing customers as a tool for enhancing those companies’ sales prospecting efforts. Product purchase data was not available for the surgeons, so a traditional lookalike model based on purchase vs. non purchase was not an option. 

Available data for each surgeon included educational history, current practice location, primary specialty, hospital affiliations, procedures performed and manufacturer payments received. Because much of this data is categorical, common clustering algorithms were also not a feasible solution.

MKT Analytics devised a probability-based similarity scoring solution, where highly common values such as a given primary specialty received lower weighting in the scoring. Less common values, for example, a match on fellowship location, garnered higher weighting. The similarity score derived from the sum of all the weights for the available variables. 

The deliverable is an interface that allows the user upon entering a surgeon’s name to: 

A law firm focused on debt relief had leads coming in faster than they could handle them and from many different types of sources. In the short term, they had a choice of adding lead management/sales resources or figuring out how to prioritize leads in order to not pursue ones with little chance of closing. They chose the latter. 

MKT Analytics developed a logistic regression model based on lead source, debt amount, state, lead age and other factors to predict a closing probability for each lead. The law firm was able to eliminate 40% of all leads before first contact, and gain a much greater sense of the value of each lead source. 

A major tire manufacturer’s loyalty / incentive program for its independent Dealer channel has a complex structure with a lot of moving parts. MKT Analytics is a long-time partner, helping with all performance aspects of the program. Among our decision-driving services are: 

A fasteners and tools wholesale distributor was interested in profiling their customer base to understand how to better market to it. MKT Analytics provided a comprehensive report on sales concentration, customer retention and acquisition, geography, crossover between major product categories and more. 

We also appended SIC codes to develop on opportunity matrix. Using average sales per customer and industry penetration rates, we built a matrix creating four opportunity segments tied to a general strategy for customer management. Those industries that were above average in both sales per customer and penetration rate fell into the Retention quadrant. Those high in sales but low in penetration were Acquisition targets. The strategy for those industries with lower sales and high 

penetration was Cross-Sell/Up-sell. And for the low/low combination, it was Divest. 

An insurance and wealth management company was looking to restructure its incentive and recognition programs after having spent many years with the same template that featured over a dozen different ways opportunities for recognition and rewards. One challenge was to create a design that would expect to boost sales performance while staying within the same budget guidelines as prior years. 

Another was the two main product lines created net revenue in vastly different ways. 

MKT Analytics conducted a thorough analysis of overall sales performance, program performance, individual salesperson product mix, salesperson reward attainment across multiple programs and staffing trends over a five-year period. The output was a versatile, comprehensive What-if? simulator that allowed a planner to: