Higgs boson.

Dangerous Data— Revenue

This is the first of a series of posts about using data to run SaaS businesses. It’s an exploratory mission, and I really don’t know where it will end up. What I’m seeking, however, is what I’ve termed “Higgs boson data,” or data that is extremely hard to find and interpret, but provides insights and knowledge beyond our wildest dreams. On the way, I’ll also be on the lookout for data traps, where numbers indicate one thing and become all-consuming, but in the end are either (a) wrong, or (b) a distraction from issues that actually matter.

Some background on why I’m doing this:

We’ve gotten to a point where every company worth its salt relies on data. Commentators generally hail this new era as a revolution.

“Data is the new oil.” — Clive Humby

“Data is the new oil? No: Data is the new soil.” — David McCandless

“Without big data, you are just blind and deaf in the middle of a freeway.” — Geoffrey Moore

“Without data you’re just another person with an opinion.” — Credited to many

“Data really powers everything that we do.” — Jeff Weiner

Some of this sentiment is right. Data has provided the foundation for incredible innovation over the past century: medicine, robotics, transportation, consumer experience, and more.

It has also become one of the biggest distractions to real discussions and decisions. How often have you been in a meeting where the room is abuzz with the latest revenue and customer growth numbers, there are a series of congratulatory comments, and then you leave realizing that nothing was actually accomplished and nothing important discussed? How often have your heard that “this vertical is growing like gangbusters; we need to invest!” only to find out later that nobody in that vertical cares about your product? This is the data danger zone, a place where big, important numbers distract you from taking care of your core. It’s no different than the guy at the gym who can bench 300, but whose legs look like pvc piping. Don’t be that guy.

For this post, we’re going to take a light approach and focus on a common offender: Revenue. While not thought of as “big data” or “new data”, it’s data nonetheless, and very dangerous data at that.

Revenue is big and sexy. It’s the number you want to talk about at the bar to show how well you’re doing (“We just hit a $10m run rate. It’s so crazy right now.”). It’s a convenient baseline for a nice SaaS multiplier that helps you calculate what your options are worth (“We think we’ll get 10x+, so we’re easily worth over $100m at this point; it’s so crazy right now”). Revenue is easily quantifiable, easily transformed into a graphic, naturally includes time as a factor (hockey stick growth!). In short, it creates a damned compelling narrative all on its own.

But whether or not the narrative is true, insightful, or useful is a totally different matter. Revenue in a vacuum, just like all other big, sexy numbers, is not only non-actionable and non-predictive, but it can also blind us from the truth.

For example, you just had your first $1m month, which is 300% better than the preceding year, and 20% better than the preceding month. That’s huge, and you should congratulate yourself. Before taking off to get a drink at the bar, though, take a look at a few other things.

  • Have you noticed that your sales team had 600 marketing qualified leads in its pipeline a year ago, but now only has 250? That’s odd and definitely needs to be investigated. Your pipeline is shrinking. How will you get to $2m without leads?
  • Your customers love you (or so you think), but your CSAT score has been in constant decline since December. It would be easy to say “it’s just a stupid metric that some rando made up” and turn the other way, and you’d be right. But it’s also a metric that’s been proven to work over lots of time and across many businesses. It’s dependable. Figure out what’s going on there, before another frustrated customer starts looking at your competitors.
  • 6 months ago, right after you raised $10m in a Series A with the aim to acquire new customers, you dramatically increased your spend on sales. That strategy could make sense if you have a reliable sales team that delivers predictable growth (and of course you do). But what doesn’t make sense is that you spent $3m on S&M last quarter, but you only have 20 new customers with an ARPA of $2k/month to show for it, and your revenue only grew by $400k total QoQ. Your magic number is .53, which is not very good. It’s not run-screaming-for-the-hills bad, but it’s not good, and it indicates your S&M teams are inefficient. You should look at that.
  • Finally, you pull up your report on customer engagement. It shows that 4 months ago customers we logging into your platform on average once every 3 days. Now it’s once every 7. Maybe this is just seasonality. Maybe it’s a great new notification feature you released. But maybe your customers are getting bored. Or maybe they are trying out another offering. Again, look into it.

Now, remember that CEO that took off for the bar to celebrate nice revenue growth? She may have just missed the fact that her marketing team is potentially failing to deliver qualified leads. Her support team is performing worse as the company grows. The sales team is inefficient, and marketing may be contributing. And the product may not be keeping customers excited and engaged. Well shit.

Of course, all of those may have very reasonable explanations and ultimately be totally unconcerning. But the point is that if you are so focused on revenue that you ignore everything else, you may be hurting yourself and your employees in the long run. Don’t let the big, sexy data distract you; pay attention to the “small” stuff before it’s too late.