Case Study: Intuit QuickBooks optimizes email timing with Concord's predictive data science model

Intuit QuickBooks reduces email guesswork with Concord’s predictive model

Intuit QuickBooks faced the challenge of optimizing its email marketing cadence to both current and potential customers. To protect its valuable email lists and improve the effectiveness of its campaigns, it needed a way to predict the ideal time to send an email to each individual recipient. The company engaged vendor Concord for a data science and analytics solution.

Concord built and productionized a Recency Frequency Model (RFM) using machine learning to predict the perfect time to email each customer. This real-time insight was integrated directly into the marketing environment as a segmentation tool. As a result, QuickBooks marketing professionals gained visibility into the predicted outcome for every recipient, allowing them to determine the best course of action for campaign timing and significantly reducing the need for guesswork.

Intuit QuickBooks