Case Study: Air Miles improves model accuracy by 50% with Posit Team

Air Miles boosts model accuracy by 50% with Posit PBC

Air Miles, a loyalty program company, faced challenges with its data science workflow, including slow model runtimes of eight hours and a lack of transparency from its drag-and-drop modeling tools. This was a bottleneck in their goal to create a more personalized customer rewarding system. The customer sought a more professional approach and turned to vendor Posit PBC for a solution.

By implementing Posit Team, including Posit Workbench and Posit Connect, Air Miles transitioned to using R and Python for more advanced modeling. The solution provided by Posit PBC dramatically improved their workflow, reducing model runtimes from eight hours to just one and automating previously manual tasks. Most significantly, the accuracy and recall of one of their main models improved by over 50 percent.

Air Miles