Case Study: a large retailer in the US achieves 20% higher customer conversion with Tredence's multi-touch attribution and spend optimization

a large retailer in the US lifts customer conversion 20% with Tredence

The marketing team at a large retailer in the US faced a challenge in optimizing their customer acquisition spend. Their existing model could not accurately measure the contribution of each marketing channel, as it used a simplistic first-touch attribution method. They partnered with Tredence to develop a new framework that would accurately value each channel's role in the customer journey and optimize their marketing budget for a higher return on investment.

Tredence implemented a solution using a multi-touch attribution model based on Markov chains to calculate the precise contribution of each channel. They reallocated the budget using linear programming to maximize ROI. As a result of Tredence's work, the retailer achieved an approximately 20% higher customer conversion rate with the reoptimized spend.