Will Scully-Power


Last Click Attribution: A Simple Way to Misallocate Your Budget
July 31, 2010, 7:42 am
Filed under: Behavioural Targeting, Datarati | Tags:

Campaign Action

With many new options in the marketplace for purchasing display media, advertisers are taking a hard look at the value of each “link” in the traditional advertising value chain, from agencies to networks to data providers.

The links in the purchase funnel (display ads, search, etc.), however, still manage to escape similar scrutiny.

Imagine if you rewarded your ad server with the bulk of your media budget, simply because they are closest to the ad’s final placement. Last-click attribution essentially takes the same approach. While reluctantly accepted for its simplicity, the model’s strengths end there.

Currently, a substantial number of our advertisers are applying a last-click attribution model for their campaigns.

Advertisers are well aware of its shortcomings, which have fueled the debate about display attribution models for years.

Recognising these challenges, DataXu’s Advanced Analytics Group frequently works with customers to analyse their unique attribution data and develop customised strategies for their display campaigns.

Taking a look at this data for six campaigns, the team identified some interesting trends.

Data Insights & Trends

– For all campaigns, last click attribution ignored 97% of spend driving conversions — which often results in over-spending in search and re-targeting, and under-spending in display that drives demand creation.

– The recommended attribution period for short consideration products, such as CPG, is two weeks. In the campaign shown above, this window includes 90% of impressions that converted.

– The recommended attribution period for long consideration products, such as Insurance and Autos is five weeks.

– The length of time it takes to attribute 90% of conversions varies by 250%; each product requires its own distinct attribution model.

Ultimately, no two campaigns are alike, and what drives their success is tough to predict at the outset, but incredibly valuable to understand.

More: www.dataxu.com

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