Summer’s Top SaaS Frameworks, Shopify Valuation Hack & Perks (lots of perks)
We all know there’s an ocean of content out there — so we thought we’d do something about it and distill the top SaaS frameworks that caught our attention this summer.
Selection criteria for this post were (i) we use this framework daily and (ii) we’ve observed a positive impact where it has been implemented.
1. Growth efficiency
First off, we’ve refocused our efforts towards helping management teams measure growth efficiency. Why? Because efficient growth puts management teams in a position of strength for their next stage of financing — simply put, it is more valuable than absolute growth.
Chatting with our top co-investors, we isolated *two* metrics which we feel are worth internalizing at a deeper level in order to connect burn with growth and see how that equation balances out:
1.2 BVP Efficiency Score (BVPES) reflects the amount of ARR generated by $1 of cash consumed. BVPES a measure of overall capital efficiency connecting the return on OPEX (ie S&M, R&D and G&A). BVPES is most relevant for companies with ARR <$30M, above that threshold BVP Efficiency Rule (BVPER) becomes more relevant:
Definitions for these two measures are:
BVPES (t) = Net New ARR (t) / Net Cash Burn (t)
BVPER (t) = % Rev. Growth (t) + % FCF Margin (t)
This discussion focuses on BVPES and so we have provided a computation example below:
- ARR (2016) = $10M
- ARR (2017) = $25M
- Net New ARR = $25M — $10M = $15M
- Net Cash Burn (2017) = -$10M
- BVPES (2017) = $15M/$10M = 1.5
Top quartile SaaS companies have BVPES > 1 while sustaining top quartile growth (which sub $10M ARR is in the 150%-200% YoY range, with 80–100% YoY persistence).
So far, all of this can be found in BVP’s excellent State of Cloud 2017.
In practice however, we’ve found that the more interesting aspect of this ratio is not necessarily its level, but rather the drivers behind it, ie the why? What we’ve found is that, capital efficiency is mainly driven by product-market fit (as measured by empirically observed user engagement, ARR growth, upsells, logo retention and NPS).
That being said, once product-market fit firms up (typically post $1M ARR), the main driver for capital efficiency then becomes S&M efficiency. In short, developing efficient S&M processes is the most important driver for success for startups as they scale. We’ve found that a compelling way to evaluate returns on S&M spend was through the Magic Number (MN) — and comparing MN to S&M as a % of revenues.
1.2 Magic Number (MN) reflects the amount of ARR generated by $1 of S&M spend. It is defined as:
MN = [Recurring Rev. Run Rate Q(t) — Recurring Rev. Run Rate Q(t-1)] / Q(t-1) S&M Expenses
In Scale VP’s words, “take the change in subscription revenue between two quarters, annualize it (multiply by four), and divide the result by the sales and marketing spend for the earlier of the two quarters”.
What we like about MN is that it is easy to benchmark against public comps given that its inputs are derived from GAAP metrics. We’ve found that MN strengths (ie easy to compute, benchmarkable) offset some of its weaknesses (ie not directly tied to SaaS unit economics, cyclical).
In short, the higher MN the better since it means that investing more S&M (as a % of revenues) will translate into efficient growth. As a guideline, for growth to be deemed “efficient”, MN needs to be above 0.7. Generally speaking, post $1M ARR, if you have reached MN > 0.7, then it becomes compelling to really ramp up S&M as a % of revenues since the return of that spend is attractive.
The table below from the excellent 2016 Pacific Crest Survey describes median cost structure by size:
Note that these S&M as a % of revenues are significantly below those we like to see. Best practice is to shoot for 90%-140% when evidence of efficient growth is established.
Another interesting ratio with a similar philosophy is the CAC:ACV, as illustrated below:
Again here we fall on a similar conclusion: CAC:ACV points to about $1 of CAC to $1 of ACV, which is aligned with MN > 0.7.
Unsurprisingly, below the 0.7 thresholds, digging into the S&M processes and product-market fit will add tremendous value to the business.
For more on product-market fit, we strongly encourage you to review:
The following section is focused on S&M frameworks and benchmarks we’ve found useful to help improve S&M efficiency.
2. State of sales and marketing
2.1 Inbound lead gen: Wondering how to crack the marketing attribution model crystal ball 🔮? Do not worry, you’re not alone :) In fact, I haven’t yet met a CFO that admitted being fully comfortable with return on marketing spend (and I meet a lot of CFOs).
What’s comforting however is that there is a strong positive relationship between marketing performance and the clarity through which management is able to describe its marketing funnel in its reporting.
Best practice is thus for the CFO to own all forecasting activities. So first step is to define how many leads are required to support marketing lead gen targets for next quarter (using CMO input) and track conversion rates across time (Uniques/MQL/SAL/SQL/Opps/Closed Won). Then backing out CAC per lead at each stage becomes more comprehensible. The basic idea here is that by supplying marketing with the right types of templates to fill, discussions become more productive. Please don’t hesitate to reach out to me directly if you’d like to zoom in on that and review best practices for board deck templates.
We will also follow up with a software stack survey to gather feedback on which vendor performs the best for startup marketing attribution and will share learnings. In the meantime, our friends at Google are working on a free product which looks promising and set to launch early 2018 — Google Attribution — worth tracking.
Here are relevant best practices shedding light on marketing attribution:
👉 How to choose MarTech that will actually work for your company, from Michael Litt
👉 Peek inside Slack’s growth strategy, by our friends at OpenView
2.2 Outbound lead gen: We keep agreeing more and more with Aaron Ross’ conclusions: adding sales rep doesn’t increase revenues, lead gen increases revenues. Fact is that adding AEs without being able to feed them enough leads will result in a dry funnel since most AEs don’t have time/skills to prospect efficiently. In other words, unless your average ACV is high (in the $250K range) then it make sense to look at distribution channels as a portfolio strategy and acknowledge that the productivity of these channels change over time (ie some will die). The table below illustrates the type of diversification you want to benchmark against:
Where “Mixed / Other” is defined as respondents who have more than 25% of bookings in two or more distribution channels or channel sales as a primary mode of distribution
We also keep seeing benefits of early specialization between SDRs, AE and CS (see below):
These are the best resources we’ve found that helped our management teams find what works for them:
👉 Specialize your sales team, from Aaron Ross
👉 Bridge Group 2017 SaaS AE Metrics Report, from Bridge Group (for all things AE)
👉 The SaaS Cash Flow Trough, from David Skok (see teaser below, make sure to download the excel model)
(Hint: It takes a long time for a rep to contribute to profitability: getting paid upfront is a HUGE +)
Again here we are happy to assist with any more specific questions you may have.
3. Shopify valuation hack
Shopify revenues were composed of roughly 50/50 of Subscription (SaaS) and Merchant Services (non SaaS, mostly Shopify Payment) as of Q2–2017. Yet, Shopify EV/NTM Revenue multiple is 14.6x.
Question that comes to mind is: *How can non SaaS revenues attract such a high multiple?*
The answer occurred to me talking to some of our portfolio companies who have GMV-derived revenues:
Yes Merchant Services revenues are not recurring and have a much lower GM (35% vs. 70% for SaaS), *BUT* Merchant Service revenues are highly beneficial to Shop *operating margin* (ie below GM) since those revenues are generated at MUCH LOWER CAC and R&D costs than SaaS rev. So while not “contractually” recurring, GMV-derived rev have a recurring feature — no reason to stop processing payments once you’ve shifted to Shop and also scale with volume. I actually see this revenue stream as an organic upsell vector with costs that are mostly captured in GM, and thus adopting a GM-focused view is not reflective of the value these revenues generate for the operating margin of the business and would result in an undervaluation of the revenue base.
4. Other admin perks
👉 We now have 50% off eShares implementation, worth checking out!
👉 Killer ESOP representation: A Template for Visualizing Your Company’s Employee Equity
Keep rocking,
Hugues
