I want to continue my post from Tuesday about the importance and value of instrumentation. Today, I want to share SaaS metrics that can be answered with proper instrumentation (operational and business).
  1. Cost of acquisition. This is cost to capture an unaffiliated buyer. Need to know the costs associated with closing this opportunity including marketing costs, engineering support, etc. For this metric, it’s important to track the flow and behaviors of a customer through websites, sales touches, etc.
  2. D1, D7, D14, D30 retention metrics. Here, D stands for “day” and the number refers to the number of days since a user first enters the system. This metric tracks the percentage of returning users to the service in D days –gauge “stickiness”.
  3. Open and Click-Through Rates of Emails. Many products these days have email engagement and nurture campaigns. Here, companies measure if users are opening these emails and, if applicable, are they clicking into a destination the company is looking for.
  4. Drop-off During Sign-up Process. Many products have multi-stage sign-ups which can deter and annoy users from completing sign-up. By measuring here, the company can quickly ascertain if the sign-up process needs to be simplified or be very valuable to motivate complete sign-up. If they never enter, they’ll never see the great product! (This, by the way, is why so many apps use Facebook, Twitter, Google login… plus, companies get personal data shared from those platforms.)
  5. In-App Engagement.This is a big bucket including what pages, tabs, profiles, features are viewed and used. You want to understand how users interact with the product – are they finding pages useful? Are features cumbersome?
  6. Customer Lifetime Value. Same concept of the revenue of a customer (or net profit) but extrapolated against the number of times a customer buys (subscription, multiple products, etc.).
  7. Churn.That is, what percentage of customers stop buying annually? Good annual churn for SaaS businesses according to Sixteen Ventures is 5-7%. High churn may point to poor value, mismanaged expectations, or an inherent problem in the product.
  8. Average Revenue per Customer. To be explicit, it’s total revenue divided by customer. In this case, revenue would naturally be weighted by where most of revenue comes from.

I get excited when a company properly instruments their products and services. It demonstrates tremendous maturity and understanding to recognize engagement data will drive confirmation (or rejection) of hypotheses, and thus, enables smarter business decisions.

What are some other metrics you find useful? How would you measure success in your company?
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