Key metric is the metric that currently needs your attention the most. Lean Analytics calls it “The One Metric That Matters”. So, what’s the difference between improving any metric that is under average versus improving your key metric?

Well… it depends if your business has profit bottlenecks or not.

People look for the key metric because you can only concentrate on improving one aspect of your business at a time. But there’s another aspect too - improving the key metric is supposed to increase your revenue or profits the most.

Testing SaaS Compass

I’ve been testing SaaS Compass this week. It’s my upcoming tool that makes improvements to metrics comparable.

I created some test companies and let SaaS Compass calculate their metrics. Then I made realistic improvement plans for them and viewed the revenue and customer base life-time value forecasts. These were all companies with annual revenue < $1,000,000 and most of them were under $500,000.

If you are one of those SaaS owners who have been generous enough to publish your company stats in your blog or twitter, thank you! Without your help, I wouldn’t have been able to create realistic test profiles.

So, let’s look at the results.

The happy scenario

No prominent key metric

The difference between the best and the worst improvement option is several thousand dollars in total customer base life-time value. The difference between the top 3 metrics is not huge.

In the big picture, the value of this forecast is “nice to know”.

Of course, this is a snapshot and we are talking about recurring revenue here so the difference accumulates over time. And… I’m using really small, realistic improvements here.

Still, in this scenario, it’s not going to ruin your business if you don’t hit the key metric. But every now and then I run a scenario that has a profit bottleneck…

The bottleneck scenario

Prominent key metric

This is a mild case of a revenue bottleneck. When I saw this pattern first time, I thought I had run into a bug in the spreadsheet. But after re-checking the projections several times I had to admit that the calculations were right. I had found a test company with a bottleneck.

I played with it a little, as I wanted to know how much I would need to improve the other metrics to gain the same increase. I soon found out that the changes needed were ridiculous.

Then I tried decreasing the churn targets, but the chart bar refused to shrink easily.

For a bottlenecked company like this, even a feeble attempt to make the customers stay longer is the winner’s choice. Doing anything else is waste of money until the bottleneck gets fixed.

As I continued testing, I saw how the bottlenecks moved around when I used different company profiles. I was fascinated! There are other systems for finding the key metric that compare to averages and/or try to find your “stage”. What I saw while testing is a proof that those methods work. But then again… there are lots of posts about how companies have trouble recognizing their correct stage.

Bottlenecks and prominent key metrics

While testing, I found both bottleneck metrics and prominent key metrics.

Some of the bottlenecks and relationships that create a prominent key metric are easy to understand. Like the relationship between metrics that affect only new users and metrics that affect only old users. E.g. conversion rate vs. churn rate.

If your customer base is small, it’s often much easier to get 100 more signups than implementing something that makes 100 more old customers to stay. At that point you may not even have 100 customers! But as the company grows, the amount of old customers in relation to the new customers grow, and churn becomes more and more important.

There is a nice post about this by Joel, where he tells you how to find your SaaS Growth Ceiling . If a company finds itself stuck in the ceiling, their prominent key metric is churn.

Are the bottlenecks common?

This is still test data, so I have no idea. In my tests, about 1/4 of my customer profiles have a bottleneck or a very prominent key metric.

I hope that we’ll find that out how commonly they appear for real when I start to get customer feedback from the SaaS Compass. The launch day is 17th of July.

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