Scavenger AI identifies customers showing reduced purchasing activity

Scavenger AI has introduced a new software solution designed to help businesses identify customers who have become inactive. The tool tracks customer purchasing intervals and flags those who have exceeded their typical buying cycle.

The software calculates the average purchase interval for a company's customer base. This metric allows businesses to set benchmarks for predicting when a customer is likely to make their next purchase. For example, if the average interval is 45 days, the system can then identify customers who have not made a purchase within that timeframe, indicating a potential decline in engagement.

Scavenger AI aims to improve customer relationship management and mitigate customer churn. By automating the tracking and notification process, sales teams can prioritize outreach to these identified "cold" customers. The company emphasizes that this moves businesses from relying on guesswork to making data-driven decisions.

Utilizing this data, companies can plan targeted re-engagement campaigns. These might include special offers or direct communication for customers whose last purchase significantly predates their usual buying habit. Scavenger AI states that its tools enable businesses to analyze and interpret customer data, fostering proactive measures to enhance customer retention.