How do you know how well your unified search and social advertising efforts are working? To answer this question, an incremental lift analysis is a must.
What’s an Incremental Lift Test?
Incremental revenue is earnings you wouldn’t have gained without a specific campaign. An incremental lift analysis, then, assesses the average revenue from two groups:
- People exposed to certain variables within a test group (two segments)
- People in a control group
A popular setup for an incremental analysis is testing the average revenue of the two segments of our test group:
- Those who converted from a paid search campaign over a certain period
- Those who converted from a paid search campaign and were added to a “cross-sell” audience exposed to a dynamic ad on Facebook (encouraging the purchase of a complementary item)
With #2, we want to identify the average revenue impact of the group that was added to the cross-sell segment on Facebook. Then, we want to compare this impact to our control group, i.e., those who weren’t exposed to a “cross-sell” dynamic ad on Facebook after making a purchase.
There are several things e-commerce advertisers should consider when implementing an increment lift test. In this example, we’re using Google Analytics.
- When deciding how long the campaign should be, consider the average time to purchase for first-time buyers and repeat purchases. The campaign should run, at minimum, for the full purchase cycle to best determine impact.
- Simplify creative and messaging iterations, and make sure they’re consistent across both paid search and social channels.
- Deploy both the Facebook Pixel and the Google Pixel using a tag management solution. View conversion data as directional within each publisher, and compare to conversion events/goals within your analytics tool early into the campaign flight. This ensures there are no noticeable discrepancies.
- Set up revenue goals (completed purchase or pre-order request) for the products being amplified in the ads. Be sure to use a monetary value here with the funnel turned on—if you’d like to track landing page success metrics such as where people bounce within the checkout page, input URLs for each screen page the user will see.
- Ensure the UTM parameters within ads all have a standardized naming convention, so that you can run funnel reports to analyze the path to conversion.
- A true measure of sales lift uses an attribution model that reveals the individual and collective contribution of each paid channel on the online (or, offline) conversion event.
- Select an attribution model within the analytics tool that your digital marketing team fully understands prior to launching campaigns. For the purpose of this analysis, the goal should be to view performance beyond post-click or post-impression metrics with a linear attribution model that gives each touchpoint along the path to conversion an equal weight.