4 Lessons Learned: The Atlassian F-1 and Predictable Revenue Vs. The Flywheel Sales Model
I talk to a lot of startup sales VPs.
In the last year, I’ve begun advising 3 more startups than I previously had. My “day job” is as a VP of Sales at a ag-tech company, and I run a sales conference and emcee a marketing conference.
For the last 10 years, Aaron “Air” Ross’ book Predictable Revenue, has been the boilerplate sales model for practically every SaaS company that I’ve come across. When the RingCentral S-1 came out about three years ago, I pored over the entire document for hours, trying to suss out every single customer metric I could — average revenue per user, account size, churn, etc. (There’s actually very little churn data for VoIP phone systems, so this was a particularly revealing document around that).
When I read Tom Tunguz’s post on Atlassian, I was pretty surprised, because it refuted a lot of what I thought I knew about building SaaS sales, quickly. Atlassian largely used the Flywheel model, rather than the Predictable Revenue model. Before getting into the metrics, let’s look at the difference between the two.
Predictable Revenue Method
- Users you’ve heard of: Salesforce, Echosign (now Adobe)
- Biggest differences between this and Traditional SaaS Sales Model: None, this has become the model. Sales development reps get meetings for inside sales reps. (illustration here). Inside sales reps nail an SMB sales niche, scale up to midmarket, scale up to enterprise. Marketing leads from the front, managing the next quarter, while sales manages the current quarter.
- Why people use it: Dozens of success stories, reasonably easy to justify to any CEO or Board.
- Users you’ve heard of: Atlassian, Asana
- Biggest differences between this and Traditional SaaS Sales Model: Enterprise sales team is 100% inbound.
- Why people use it: Highly efficient customer acquisition, grows revenues exceptionally.
Lesson 1: The part of the Atlassian S-1 that really blew my mind was Atlassian’s net income, compared to the typical SaaS revenue media. Doesn’t necessarily prove that using Flywheel is a cure-all, but it makes you sit up and take notice.
Lesson 2: Atlassian is profitable. That’s not too common in SaaS today. Last time I checked, only about 11% of all tech IPOs were from profitable companies.
Lesson 3: High Average Revenue Per Customer (ARPC) with “no whales.” What this means is that Atlassian was able to sustain ARPC of about $6k, as high as big dogs like ZenDesk, Xero and LogMeIn. This is with no customer making up no more than 1% of all total revenues (no more than $3.5M, and only 854 customers pay more than $50k/year each).
Lesson 4: Sales Efficiencies of Using Flywheel: Sales Efficiency (full post on that here) is an incredibly handy SaaS sales benchmark. It tells you what the payout is on all sales and marketing numbers — so, if your startup invests $180k in sales salaries, $60k in sales travel and $50k in marketing spend this year ($290k) and generates $780k worth of incremental revenue, then, net of cost to provide service, your sales efficiency is 2.68. This number is normally between .8 and 1.2. If you get it between 2.5 and 3.2, that’s just kick-ass. And that’s what Atlassian did. (Comparison of them versus SaaS median is here.)
I don’t know enough about this stuff to establish causality between Flywheel method and crazy-high Sales Efficiency, but I do know enough to promise that my next few posts here will be about optimizing Sales Efficiency, whichever revenue-building methodology you’re going after.
For a far deeper dive into SaaS metrics, especially in the first two years of your SaaS company’s life, read this post on Bookings, MRR, Revenue and cash.