Our team brings a wealth of experience from both the client and consulting side across diverse industries.

We understand that every industry has unique challenges and requirements.  Our experience and knowledge helps us to provide tailored data analytics solutions that address the specific needs of each client.

Retail

Non-Profit

Sports

Game Design

Financial Services

Law

Modeling

An online retailer wanted to begin using forward-looking analytics (modeling, segmentation) to augment historical dashboarding and reporting.

  • Created an analytical data set that could be used across future modeling initiatives
  • Built upcoming 12-month gross revenue predictive models with associated gains tables, with separate models for new acquisitions, young customers, and customers with several years of history with the retailer
  • Developed a Holiday mailer response model

Game Design

A video game company wanted to predict the probability that a team will win a match, and improve the system by which players are matched for a 4 on 4 game.

  • Accounted for teammate and opponent strength in a 4 on 4 game
  • Accounted for time spent playing as a team, for synergy
  • We accounted for various roles in the game as having different impact on the result
  • Assigned reward or penalty at a team level, and then distributed that praise or blame to the individual team members justly
  • This also helped with better game matchmaking

Customer Segmentation

An online retailer wanted to create a customer segmentation to guide channel leads in campaign and communication list selection.

  • Grouped the various attributes into several dimensions, such as demographic, geographic, purchase type, purchase amount, etc.
  • Used the dimensional scores as inputs to a clustering segmentation to create six actionable segments

Campaign Design & Lift Analysis

A financial services company was seeking to create more structure around upcoming marketing campaigns. They sought to implement tests that would enable them to tailor creative copy and messaging to be more meaningful and to create reporting frameworks that would enable easy interpretation of results.

  • Built test grids and helped define cell quantities using the process described below to provide meaningful test results
  • Worked with internal teams to reach a compromise between strong campaign results in the present roll-outs and reliable test reads to strengthen future campaigns
  • Developed a few key tools to auto-generate the most commonly requested campaign metrics and views without necessitating ad hoc requests for each view
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