- Invest in analytics tools that can capture and analyze all the touch points for each user.
- Treat each desired conversion event as a dependent variable while gradually adding the type, frequency, and attributes of each touch point preceding the conversion event as independent variables.
- Then, let your statisticians or analytics team figure out what main effects and interactions are driving the desired conversions.
“Last-Ad Wins,” the most common version of attribution models, has been the on the chopping block for years, but it manages to remain the answer for many marketers because of its simplicity. Well, Xuhui Shao says a change is needed. As we enter a new ecosystem of real-time bidding (RTB) and audience buying we have access to much better data and clear information about consumer touch points and how effective each touch point is in driving conversion. At a basic level, attribution is the analytics process of determining how effective each media buying channel is at producing the desired advertising outcome. So, the minute marketers dabble in cross channel advertising campaigns, they’re faced with an attribution conundrum. Giving the last ad 100% of the credit hardly seems fair. A more accurate attribution model takes into account the countless events taking place along the consumer’s path to conversion. For the full story, read Xuhui latest column, “Attribution in Real-Time Audience Targeting” on ClickZ. Here are steps advertisers and agencies can take to move beyond the last-ad attribution model: