On one of my many cross country travels, I ended up in a non Marriott facility. This is a rare occurrence, but in this instance I had no choice, and my loyalty was temporarily shifted to another large brand hotel operator. The next morning, I woke up and went to take a shower. I was not used to the tub and shower faucet mechanism. I had learned the various Marriott brands, so I knew, without thinking, how to operate their showers. However, this one had me stumped, and the reason why will explain this concept of monotonic lift.
As I lifted the shower handle upward, my expectation was that the temperature would change accordingly. As I slowly lifted the handle, the water grew warmer; this remained consistent. However, when I got about three quarters of the way up, the water started to turn colder. When I went back down, the water got warmer, but when I moved it up again there was a sudden drop in temperature. This was not monotonic at all. It was unpredictable, and I felt confused and did not trust this new shower faucet contraption. If there had been a monotonic lift, then as I lifted the handle, the temperature would have risen steadily.
In essence, monotonic lift is predictable. You know the effort it takes to change or improve results. When you slide the dimmer switch up, you expect the light to get brighter at a steady rate. In most businesses, a lift that is predictable in nature, across all segments and markets, is more valuable than any one growth metric. Predictable growth almost always beats the unpredictable spike. The point is that once you figure out a formula that consistently improves results, and that can be replicated in both a controlled scenario and multiple other scenarios, you have something a business person would call valuable.
Often this concept of lift applies to buckets or different measurements. The lift will be different depending on the bucket that you are considering, but the lift will follow a consistent pattern. The lift may be greater or smaller depending on the bucket, but the ratio will remain largely the same. This is the holy grail of metrics, the one that performs the same way even when working with different buckets or populations. Often, as you work your way to more efficiency, you look for metrics such as these because once identified you can start to rank buckets and set thresholds for them.
A useful case would be the largely elusive TTFV metric, the time to first value. This is an important metric because marketing research has shown that the time it takes for a potential customer to reach the first realization of value has a direct correlation with the conversion rate of users becoming paid subscribers. The goal in this instance would be to get a consistent conversion rate across several time duration buckets. Customers who reach TTFV in less than 15 minutes will have a high conversion rate, say 25 percent. Users who take longer than 24 hours to reach TTFV have a conversion rate of 5 percent. As you see this fall off, it should fall off consistently across buckets. When you achieve that, you know you have a predictable TTFV expectation. Just as I expect the water to get hotter as I pull the lever upward, you would expect that the shorter time people take to experience value with your product, the higher the conversion rate will be.
As you monitor this, you can quickly understand when something is out of alignment. When the lift is not predictable or shows a significant variance from expected results, you can look at noise or confounding issues that might be distracting your user population from realizing value faster. If the results you are getting are not monotonic, it is not always a new feature you need. Often it is better to improve the sample size, look at different time frames, or address things that might be confounding the people in a particular bucket. Unintended cross over often impacts TTFV, and you may not even realize it. This is why a monotonic metric, once established, is highly valuable, like a canary in a coal mine.
