It turns out that such a lift index Slift converges to the ratio of the area under the cumulative lift curve (A UC), which is illustrated in Figure 1. If the distribution of the buyers in the 10 deciles is random (no regularity is found), then the cumulative curve would converge to the diagonal line, and Slift would be 55% (but converges to 50% with more partitions). In the best situation when S₁ = Σ ᵢSᵢ < 10%, Slift = 100%. In the worse case when S₁ = Σ ᵢSᵢ (and rest of Sᵢ = 0), Slift = 10% (but converges to 0%). That is, the lift index has a nice property that it is independent to the number of the responders. It will be 50% for the random distribution, above 50% for better than random, and below 50% for worse than random distributions.