1. Measure influence without personal user data

Lift measures the influence of a specific marketing activity on a specified variable like demos, subscribers, sales, or revenue by comparing people who experienced the activity (exposed) vs. those who didn’t (control), then measuring the difference. All without personal user data.

2. Create control groups retroactively, without experimentation

Lift uses historical data to create retroactive control groups: holdout groups who haven’t experienced a certain marketing activity. Now you can measure the influence of new channels, campaigns, or touchpoints fast, without a data engineering team, without experimentation.

3. Validate attribution with incrementality

Attribution tells you which touchpoints your customers encounter; Lift tells you which of those touchpoints had influence on a desired outcome and which didn’t. Together, you can validate marketing’s contribution to growth.

5. Campaign lift

Would you lose any sales if you paused branded search campaigns? Do LinkedIn ad impressions drive leads, even if people don’t click? Does a certain channel influence deals more than another? Lift will tell you.

6. Content lift

What impact does website live demo views have on demos booked? Does your in-feed education drive leads later? Does a specific product page influence sales more than others? Lift will tell you.

7. Program lift

How much influence does your newsletter have on leads? Do viewers of your video series convert higher than non-viewers? If you stopped blogging, would it matter? Lift will tell you.

8. Messaging lift

Does your messaging motivate action? Does your new ad creative drive more meetings than your old? Does your updated homepage influence SQLs more than before? Lift will tell you.