Ryan Donovan

Many of the organizations I have spoken to define their product metrics entirely within the realm of user activity and adoption. Yet, at the same time, there is an inherent desire for product leaders to act as General Managers or CEOs of their product lines. In the current market/economy the best path forward is no doubt for product leaders to care about business metrics end-to-end. At minimum:

• Pipeline – covering all stages of the business from marketing demand-generation to sales to product. Dive deeply into moving from one pipeline stage to another as well as points of abandonment. These represent opportunities to not only improve GTM efficiency, but better position product or address gaps in the offering. Because there are so many ways to manage pipeline, there is no set
• Win Rate – adjustments here are a not only a signal of GTM efficacy, but also early indicators of gaining or losing product-market fit or competitive headwinds. Previous comments around product positioning and offering from pipeline also apply.
• Long-Term Value: Customer Acquisition Cost (LTV:CAC) – evaluate current state vs. best-in-SaaS and partner with the GTM organization to carve a path to best-in-SaaS.
• Gross Margin – evaluate current state vs. best-in-SaaS and partner with the GTM and finance organizations to carve a path to best-in-SaaS.
• Research & Development + Sales & Marketing as a % of Revenue – although these metrics vary widely from industry and product category, publicly traded competitors and private comparators (usually available from one’s venture or private equity investors) provide guidance on what good looks like for a given category. Evaluate current state vs. category benchmarks and formulate plans with the engineering and GTM organizations to adjust.
• Growth – previous benchmarks had sustained growth between 20-40%+ as being a table-stake for a healthy company, depending upon stage. This is revising with a coupling with profitability, as profitable growth is the proverbial new black – making Rule of 40, Rule of X, etc. more relevant metrics to track.
• Gross and Net Retention – for single product companies gross and net retention’s gold standard should be ~95% (or whatever is appropriate for the category, given available benchmark data). For multi-product companies, ~120% net recurring revenue is the gold standard benchmark.
• Influenced ARR – for multi-product companies, look at the ARR impacted by the adoption of advanced capabilities even if they are bundled into higher tier price plans of the core product. For example, consider a Premium Analytics feature in the most expensive price plan. A product leader should look at the total ARR of all customers on that price plan and exclude all other price plans as the first number. Then look at adoption of the Premium Analytics feature within the total cohort of customers on that price plan. If 50% of the customers are using Premium Analytics, 50% of the ARR of the most expensive price plan would be the influenced ARR for Premium Analytics.
• Rule of 40 – this is defined as the combined growth and profitability rate should equal 40% or greater. In recent times, it was acceptable to be growth at any cost. And the Rule of 40 typically applied only to later stage investments that had the ability to be profitable. Now, growth needs to occur with positive profitability requiring a different mix than before, making the Rule of 40 relevant to virtually all SaaS companies. A good example would be 30% growth plus 15% profitability for a Rule of 40 value of 45%. For reference, the Bessemer Venture Partners Cloud Index has a rule of 40 of 48% for their top decile of SaaS businesses. Again, product needs to partner with engineering plus the GTM teams with support from finance to help plot a trajectory for profitable growth in this market and economy.
• Rule of X – Bessemer Venture Partners has introduced a new take on the Rule of 40 equation that they call the Rule of X. This applies to later stage companies that have reached the ability to be profitable. Their equation is Rule of X = (Growth Rate X Multiplier) + Free Cash Flow Margin. In this case, the Multiplier would be 2X for later stage private companies and 2-3X for public companies with reasonable costs of capital. In the same example from the Rule of 40, the Rule of X would be 75% ((30% X 2) + 15%). The Bessemer Venture Partners Cloud Index has a Rule of X benchmark of 80% for the top decile of cloud investments. Product should once again partner with engineering + GTM teams with finance support to help plot the right course here.
• ARR / Employee – in today’s economy this metric is being looked at with increasing scrutiny and should be considered as a key metric product leaders study and see how their business compares against benchmarks.
  • Median ARR for bootstrapped businesses broke down as follows:
    • Less than $1M Revenue – ~$56K ARR/Employee$1-$3M Revenue – ~$104K ARR/Employee$3-$5M Revenue – ~$166K ARR/Employee$5-$10M Revenue – ~$160K ARR/Employee$10-$20M Revenue – ~$184K ARR/Employee>$20M Revenue – ~$180K ARR/Employee
    Conversely, equity-backed companies typically have lower metrics UNTIl greater than $20M in revenue is reached, at which point it catches up:
    • Less than $1M Revenue – ~$29K ARR/Employee$1-$3M Revenue – ~$64K ARR/Employee$3-$5M Revenue – ~$86K ARR/Employee$5-10M Revenue – ~$104K ARR/Employee$10-$20M Revenue – ~$128K ARR/Employee>$20M Revenue – ~$186K ARR/Employee
  • During my tenure at Microsoft as a public company, a healthy business was considered to have ~$1M in revenue per R&D employee working on that product
• Burn Multiple – For earlier stage businesses that have yet to reach profitability, this is now one of the absolutely most important metrics. Burn Multiple is defined as Net New ARR (annualized) / Net Burn (annualized). The previous benchmarks for Burn Multiple were:
  • Under 1x = Amazing1-1.5x = Great1.5-2x = Good2-3x = Suspect
  • Over 3x = Bad
  • With current macroeconomic conditions, keeping this at or under 1.5x is prudent and should be a shared goal between product, engineering and GTM with finance support.
• Magic Number is defined as (Current Quarter Revenue – Previous Quarter Revenue) * 4 / Previous Quarter Sales & Marketing Spend. This is now being looked at as a key SaaS metric. Customers that are less than 0.75 are considered Inefficient; between 0.75 and 1.0 as getting there; and above 1.0 as doing well. For a company with multiple product lines, it may be possible with the right level of data fidelity to break this out by product as well.
• Cost to Serve is defined as Total Cost of Service / Number of Customers. The Total Cost of Service should include all direct costs such as customer success headcount, customer support headcount, the portion of R&D that is allocated towards maintenance and upgrades, and all cloud/hosting costs. This metric should be benchmarked against comparable competitors and be at or above or trending in the right direction.

For single product and segment companies, looking at these metrics is easy – because they can be looked at on an overall basis based on what is likely already in place. For multiple product, single segment companies, this becomes more challenging. Not only should they be looked at on an overall basis, but they should be broken down to individual products. Likewise, if a company has multiple discrete user segments (e.g. Small Business, Mid-Market, and Enterprise), these metrics need to also be broken down on a per segment and/or per segment, per product basis.

Product is at least half of the equation of Go-to-Market Efficiency. One can have the most efficient GTM organization in the world, but if the product sucks – GTM metrics are going to suck. Conversely, an awesome product can cover up a ton of GTM inefficiency. Given this significant leverage, in today’s market and economy it is an imperative that product care about and help shepherd GTM metrics in partnership with their respective counterparts.

Research and Development is typically the biggest or second biggest cost in any SaaS organization. And, if things are working ideally, product is the principal driver of how engineering dollars are spent. Product needs to partner closely with engineering and finance to ensure that the R&D dollars are being spent appropriately and having the requisite impact upon corporate and GTM metrics. And work together with engineering to manage R&D costs. If, for example, the true manpower required to sustain and evolve the product is too expensive, look at ways to lower R&D costs to an acceptable level by exploring things like lower cost labor markets, etc.