Ovative worked in partnership with LiveRamp to leverage intelligent and people-based A/B testing to help the client realize optimization opportunities and reduce ad spend.
While it is assumed that digital channels drive a significant amount of in-store conversions, the challenge of not only measuring total attributable but also incremental revenue has many retailers relying on online sales to estimate the impact of their digital efforts. Online attribution models suggested that this top-ten retailer’s display media was driving a large piece of total online revenue, but there was no way for them to measure if this was true at the total enterprise level or if the revenue attributed was in fact incremental.
1. LiveRamp and Ovative Group partnered together to provide the retailer with a solution to their measurement problem.
2. A/B testing was designed and implemented for a major display event. The analysis of the test was enabled through the joining of anonymized CRM, online & offline transaction files, and display impression logs via identity linking with LiveRamp’s unique capability and use of IdentityLinks (IDLs).
3. Ovative developed and provided the client with a custom proprietary reporting environment, which enabled analysis of the data across a plethora of customer-level attributes to unlock key, actionable insights that would have otherwise gone undetected.
4. Based on test results aimed at optimizing to enterprise ROAS, the retailer made it a new best practice to deliver display impressions only to those customers also receiving direct mail. They are now conducting further testing into the incrementality of display when delivered with other digital and traditional channels.
5. The client will continue to incorporate learnings from each test into the expanded program, focusing on cost-efficient tactics to achieve the biggest ROAS impact. They will also create additional segments using identity linking and further test new optimizations while evolving the overall program to deliver better targeting and higher return while minimizing cost.
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