SwiftERM

SwiftERM identifies products each customer is most likely to buy next and presents an individual selection by email, timed to that person’s response patterns. The tool delivers recommendations away from the website and can pursue purchasing opportunities between return visits, aiming to increase revenue from existing customers without adding campaign-management work.

SwiftERM analyses live ecommerce data and continuously learns each customer’s changing preferences and buying intentions. It makes autonomous decisions about what to present and when to present it, updating as behavior evolves without relying on fixed journeys or segments.

The system integrates with existing ecommerce setups and can operate alongside current email marketing platforms, delivering emails at optimized times based on machine-learned insights and user response patterns.

SwiftERM emphasizes autonomy in decision-making, aiming to reduce manual workload and staff overheads while enabling a store to react to individual customer signals in real time.

Use cases

• Use with ecommerce stores to increase average order value and customer lifetime value