Your guide to SaaS metrics 2.0

The case for a next era metrics playbook in the age of product-led growth

We’ve grown accustomed to the traditional set of SaaS metrics as just part of how to operate a SaaS business. It’s hard to conceive of what to do without metrics like CAC payback, LTV:CAC, average ACV, or the magic number.

Here’s the thing: the traditional SaaS metrics playbook can be extremely misleading when it comes to managing a PLG, vertical SaaS, or usage-based software business. (Aka, it’s misleading for the majority of new software businesses being founded today.)

Let’s look at a few examples, shall we?

• Product as a growth driver. CAC payback assumes products grow via sales & marketing. In a PLG model, products drive acquisition, conversion, and expansion. Atlassian, for example, spends 50% (!) of revenue on R&D and only 20% on sales & marketing. How do we contemplate R&D as a revenue-generating function?

• Land-and-expand dynamics. Usage-based companies like Snowflake see smaller ‘lands’ followed by tremendous expansion (NDR of 150%+). Snowflake’s net revenue retention peaked at 177%! How much should we spend on customer acquisition when LTV is essentially limitless?

• Lower margin and re-occurring revenue. SaaS companies are seeing new revenue streams with different margin profiles such as payments, FinTech, and marketplace spend. At Shopify, for example, 76% of revenue comes from merchant solutions and only 24% from subscription software. SaaS companies are also increasingly licensing technology via third party APIs (think: OpenAI), adding further margin pressure. How do we benchmark valuation multiples for non-software revenue?

The reality is that the old SaaS metrics still have a place, especially for companies following the traditional top-down, subscription playbook. But we also need to expand the aperture of how we define success for modern software businesses. I’ll unpack how we got here and what KPIs I recommend from both an executive and operational perspective.

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The case for a next era metrics playbook

The 1.0 SaaS metrics playbook had fundamental flaws, which now look obvious in hindsight.

• It assumed sales and marketing were responsible for customer acquisition rather than the products themselves.

• It assumed that software buyers were the only audience that mattered and ignored the users of software products.

• It assumed that businesses monetized software and monetized on a subscription basis rather than monetizing a breadth of offerings (software, FinTech, payments, marketplace transactions) on the basis of both subscriptions and usage. 

We need a new playbook for modern software businesses. This playbook should center around the user’s journey and treat product usage as a signal of buying intent. 

With this new lens, the growth model isn’t rate-limited by SDR productivity or MQL volume. It’s defined by how many people discover the product, start using it, experience value, and then decide to pay. 

🕵️ Discover: People learn about the product typically by word-of-mouth, a product invitation, or Googling a solution to an everyday problem. Your goal: drive relevant, high-intent traffic to your website while keeping CAC as low as possible.

🏁 Start: Users see potential value in the product and decide to sign up and try it for themselves. Your goal: educate website visitors on the value of the product and convert that traffic to create a free account.

😍 Activate: Users actually realize the value that they were promised. Product usage grows into a habit and they become engaged users. Your goal: shorten time-to-value and guide users to their ‘aha’ moment(s).

🤑 Convert: Users decide to take the relationship to the next level and become paying customers. They’ll usually start small on an entry-level package or pay-as-you-go plan. Your goal: generate revenue by efficiently converting free accounts into paying customers.

📈 Scale: Customers deploy the paid product and decide to deepen their relationship by expanding use cases, inviting their team, or increasing their activity. Your goal: facilitate deeper usage and expand the overall revenue generated by paying customers.

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Operational KPIs