B2B SaaS Metrics Decoded! 🚀

Part I: Essential Guide for ANY Interview!

Everyone knows that,

With better metrics, we make better decisions.

Metrics act as gateways to critical information about your business operations.

Today, we'll introduce key metrics tailored for B2B SaaS. Whether you're a founder or preparing for interviews in roles such as product manager, data scientist, engineer, or other senior positions, a solid grasp of product and metrics will make you stand out from the crowd!🦄

Build basic metrics in before launch?

This is probably counter-intuitive.

From an investor's perspective, it's a significant differentiator when a founder can fluently discuss key metrics.

This doesn't mean overloading a dashboard with hundreds of metrics for a small volume of users.

So, everything in moderation.

Now, with your planned product launch next week, what should you do?

Getting started with metrics

First, choose 4-5 key metrics; you don't need more at this stage—they will grow over time.

Second, utilize a convenient analytics solution, like SQL querying your database.

Third, define and agree on metric definitions, ensuring your entire team adopts a centralized definition, whether it's one day or five days per week for an active user.

Post launch

After launching the product, if the defined metrics aren't performing as expected, founders may be tempted to tweak definitions or change metrics to paint a better picture.

But you are only fooling yourself at that point.

Keeping metric definitions consistent over time is crucial.

This ensures meaningful comparisons with your own product's progress, rather than meaningless comparisons with other companies.

You’ll need to keep the definition internally consistent to keep track of your own progress.

Key metrics to track

In the old days, people liked to report metrics like "page views" or "unique visitors" because they boasted large, impressive numbers. However, these are often referred to as "vanity metrics." While they may appear successful, they aren't genuinely tied to the success of your company.

The most recent addition to vanity metrics is "gross merchandise value (GMV)," indicating the total dollar value of goods sold on platforms like eBay, but not reflecting eBay's revenue directly. The same applies to "gross transaction value (GTV)" in the fintech industry. You can say that we are transacting billions of dollars, but the revenue is a completely different story.

For B2B companies, top 3 metrics for investor updates

Metrics #1 Revenue

Your primary metric should be "revenue." Even if metrics like GTV show fascinating growth, if your revenue isn't increasing, you might be deceiving yourself about your company's success.

A story I’ve heard was a founder sent “zero revenue” titled investment update emails for 10 months before things got better. And because she kept herself and the investors honest, they were able to find where to focus on and eventually fix the situation.

As early stage founders, a lot of us probably don’t have any revenue.

It’s okay to tell the truth.

Metrics #2, #3 Burn Rate and Runway

#2 - Burn rate: Monthly cost minus your revenue.

For early-stage startups incurring losses, it's the amount your bank balance decreases each month.

Understanding your burn rate leads to #3 Metric - "Runway."

For instance, with $1 million in the bank and a $100k per month burn, you have 10 months of runway.

Metrics #4 Retention

Besides the above three, one of the most critical metrics is "retention." If you sign up 100 customers in January, how many continue to pay in subsequent months? This indicates customer satisfaction and loyalty.

It’s a sign that your customers love your product and they keep coming back.

A traditional way of measuring retention is using the cohort method, ie., measuring the same for the January signups, then the February signups and so on.

Common retention graphs for B2B:

1. Cohorts retention in percentages:

This is similar to what we’ve previously discussed around metrics for consumer products:

2. Cohorts retention in curves:

3. Cohort stacking through layering:

The following is a well performing layer cake: For sticky products, layers build up over time, becoming highly profitable. A well-performing layer cake features a flattening retention curve, ie., the retention curve doesn’t go all the way to zero.

If your product loses users without sustained retention, then your layer cake would look like the following: