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While often overlooked for obvious email marketing metrics such as opens, clicks and conversions, lift gives you a true reflection of your email campaign performance and ultimately your customers’ behavior.
Using this thesis, we ran a test campaign for a client, and by adding a control cell in the campaign data we were able to measure and demonstrate the effect of lift.
Here’s what we did:
2 segments:
Segment 1 = would receive the normal Friday campaign
Segment 2 = would be sent a campaign with personalized content and landing pages (based of previous behavior and activity)
We let this campaign run for 1 week (7 days) before analyzing any results.
Once we were confident there was transactional data from the campaign, we began to analyze the results. The key metric we were interested in was the amount spent per customer from the date the initial email was dispatched to the end of the 7th day.
The results:
Segment 1 (normal campaign) average order value = £64.64
Segment 2 (campaign with personalized content and landing pages) average order value = £66.43
The key learnings were the difference highlighted between the normal campaign and personalized campaign. This demonstrates the lift generated when sending a personalized email to a customer, as this is the true impact over your normal email marketing campaign. In this case, the lift was £1.69 per recipient. The key differentiator is that opens, clicks and conversions don’t take into account the change in customer behavior that lift actually measures.
By using lift as your key performance metric, you can truly start to account for the impact of your email marketing and testing.
What metrics are you using to measure email performance? I would love to hear your thoughts and success stories.
