Using IBM Watson, Xaxis extracted actionable insights from Volvo’s historical site traffic. These insights allowed us to more accurately identify an audience with a higher chance of conversion. Xaxis then created bespoke algorithms for Volvo, designed to optimise all relevant client outcomes, and used mPlatform Co-Pilot to apply these algorithms in AppNexus. This use of machine learning allowed Volvo to optimise faster and to reduce the need for manual adjustment of campaign variables. In the end, it yielded a cost-per-action (CPA) that was 29% lower than the target set by the client.