SaaS Metrics 2.0: The Case For Next Era Metrics Playbook
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 reoccurring revenue. SaaS companies are seeing new revenue streams with different margin profiles such 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. Here I’ll unpack how we got here and what KPIs I recommend from both an executive and operational perspective.
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, growth isn’t defined solely 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 as much of that traffic as possible 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.
You’ll want to track the most important KPIs for each step in the user journey. This will allow you to benchmark your performance against peers, diagnose where there’s friction, and spot opportunities to accelerate growth.
- Unique website visitors excluding customers (UVECs)
- Lead generation by source (ex: paid versus non-paid channels)
Successful product-led businesses generate a disproportionate share of their new users through low-cost channels such as organic search/SEO, word of mouth, product invites, referrals, and third-party marketplaces. (For more, check out my guide to product-led marketing with Lenny Rachitsky.)
Track lead generation both in terms of free product sign-ups and traditional lead generation (demo requests, MQLs), along with the outcomes for each type of lead. Traditional top-down companies who add a “Try free” CTA often find that it not only grows the overall number of leads, but that “Try free” leads convert at higher rates because they’re product-qualified.
- Conversion from website visitor to lead
- Volume of activated sign-ups
- Cost per activated sign-up
Sign-ups are meaningless if they don’t take any action in the product. Measuring activated sign-ups allows you to better understand the quality of your leads and their propensity to buy. This acts as a great filter to determine whether your marketing campaigns are targeted at users who will actually convert when given enough time. And you’ll know this as soon as a few days after running a campaign, allowing for faster decision making to ramp up or down spend.
The metric also facilitates shared ownership between marketing and product to help more users experience value with your product.
- Activation within (7) days
- Activation rate by source and by persona
- Conversion from first-order activation (ex: activation in single-player mode) to second-order activation (ex: activation in multi-player mode)
Each company will need to create their own definition of activation that fits with their specific product. In my experience it should be something that: (1) is easily achievable by somewhat committed users, (2) can be completed within the first week from sign-up, (3) is predictive of future conversion/retention, and (4) is correlated to business performance. 20-40% activation rates are common.
- Cohorted free-to-paid conversion within (30) days from sign-up
- Product-influenced or product-driven revenue
PLG companies can look to product-influenced or product-driven revenue as an indicator of the effectiveness of their PLG motion. This refers to revenue from customers where meaningful activity was observed and recorded in the product before any sales interaction. It’s a better indicator of the PLG team’s pipeline contribution than self-service revenue on its own. (For more, check out my interview with Ben Williams.)
- Cohorted gross and net retention rates
- North Star usage metric(s)
- Product Qualified Accounts (PQAs)
Product Qualified Accounts are usually calculated as a score rather than a binary qualified or not. They’re a signal of strength based on a combination of fit with your ideal customer profile (ICP) and product usage behavior. You’ll want reps to prioritize based on the best fit and highest signals, then go down from there. (For more, check out my interview with Jesus Requena on Figma’s approach to product-led sales.)
Executive and investor KPIs
Operational KPIs help you identify where to focus. Executive and investor KPIs, on the other hand, help you communicate the health of your overall business model. Your goal is to convince others that you have a predictable way of generating revenue and a path to profitability at scale.
- Annual revenue run-rate (“ARR”). This is an extension of annual recurring revenue (ARR) that incorporates non-subscription re-occurring revenue. My rule of thumb: if the revenue is high-margin and acts recurring, it should be valued accordingly.
- Quarter-on-quarter change in net new “ARR.” This metric indicates to what extent a business is growing linearly versus exponentially. Hyper-growth companies will see the change in net new “ARR” getting larger and larger each quarter.
- Quarterly net new “ARR” versus cash burned. This ratio provides visibility into the efficiency of the business model. Unlike CAC payback or the Magic Number, it incorporates all areas of investment that drive customer acquisition, conversion, retention, and expansion. The more incremental ARR you generate for every $1 you burn, the better.
- “ARR” per FTE. SaaS seems to love complicated metrics. I’d be lying if I said I didn’t love a few of them, too. An increasingly important one is shockingly simple: ARR per FTE. This is a metric you can’t hide from. In theory, PLG companies should have a higher ARR per FTE at scale as they’re able to take work that would normally be done by people and turn that into product experiences instead.
- Natural rate of growth. PLG companies tend to have a baseline of hyper-efficient growth from organic acquisition (SEO, word of mouth, etc.) and organic expansion (more usage, more seats, etc.). From there, they layer on paid marketing channels, SDRs/BDRs, and other investments to accelerate growth. The goal of this metric is to help you unpack the incremental ROI of your paid investments above and beyond the baseline. This helps you prove to what extent you can spend money to make money.
- Cohort-based retention by customer type. Cohort-based metrics, where you track the progression of behavior among a group of sign-ups that start at the same time, are by no means new. But these metrics are increasingly important versus looking at average values, which can be highly misleading in a PLG or usage-based business. You’ll want to track cohort-based spend and retention, and get granular around behavior by go-to-market channel, number of users, country, and other factors.
The TL;DR – Time for SaaS metrics 2.0?
I hope this post helps start a conversation about which metrics matter most for your business. While many of the OG SaaS metrics have a place, forward-thinking companies need to look to new ones in order to make the best decisions.