Solutions | MKT Analytics

rEDirect℠ Dropout Prevention

rEDirect℠ is a predictive modeling solution that provides an early warning for potential high school dropouts. Not only does it deliver a student’s dropout probability years in advance of the event, it also highlights which interventions will have the most success in reducing that probability.

rEDirect℠ gives principals, counselors and school administrators a powerful tool to help guide students on the path to graduation and life success.

rEDirect℠ Presentation


Similarity Scoring

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: 

  • View the profile of the entered surgeon
  • See a ranked list of the most similar surgeons, with ability to adjust the length of the list
  • See how much each category of variables (education, practice, procedures, etc.) contributed to each similar surgeon’s score
  • Adjust category weights if there is a reason to feel some are more or less important

Lead Management for Debt Reduction

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. 

Versatile Analytics for Loyalty Program Management

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: 
  • Baseline performance reporting 
  • Analysis of promotional effectiveness 
  • Accurate and timely purchase and incentives earnings forecasting 
  • What-if? simulation models for testing program structure changes 

B2B Profiling and Market Segmentation

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. 

What-if? Simulation Supporting Recognition Program Design

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: 

  • Expand or remove programs 
  • Vary program time frames 
  • Change earning and attainment thresholds 
  • Set different thresholds based on salesperson tenure 
  • Input forecast assumptions for sales growth by product line 
  • View expected numbers of programs winners and overall ROI