# What is the correct way to compute lift in lift charts

How is "lift" computed? i was reading about "Gain and lift charts" in data science.

I picked the following example from https://www.listendata.com/2014/08/excel-template-gain-and-lift-charts.html

I am clear on how the gain values are computed. Not clear about lift values are computed? (last column in table)

## 1 Answer

Lift is computed by comparing performance with a random selection model. I'll explain with your example below,

1. assume that we didn't have any statistical/ML model for ranking/scoring the respondents.
2. In that case assume we did a random ordering of respondents.
3. A decile (10% of total population) is expected to have 10% of the respondents. In your case, there should've been (approximately) 488 respondents in 2500 cases.
4. But after ordering the cases by score, you are seeing 44.71% of the cases in first decile against expected 10% (in random/no model case). This gives the gain of 44.71/10 = 4.471.
5. For next decile, cumulatively you have covered 20% of the cases. You'd expect a random/no model scenario covers 20% of the respondents. But using scores, we covered 80% of them. That gives a cumulative lift of 80/20 = 4.