SaaStr Annual Digest: Data Rules Them All
Updated: Aug 17, 2020
SaaStr Annual, one week later.
One week to digest the knowledge and insights I brought back to New Zealand.
It is now time to share.
If you haven’t yet heard of SaaStr Annual, and you’re a kiwi tech company, just know that the team at Callaghan Innovation put together a cohort of 150 tech execs to attend this cutting-edge event.
SaaStr Annual is the no.1 non-vendor B2B cloud software conference where 12,000+ SaaS execs congregate to share best practices, learnings, case studies, network, mentor, meet VCs, etc.
Jason Lemkin and his team are committed to diversity at all levels, with 52% of female speakers, 67% of gender/multiculturally diverse speakers (I even had the pleasure to hear a fellow Frenchman), and attendees coming from 96 countries, with NZ having the biggest contingent!
My main SaaStr takeaways revolve around a few key themes:
the methodology to establish product-market fit thanks to proven frameworks and data to maximise the market opportunity faster;
the necessity to be focussed on a core target segment to learn all about the customer and nail how to best market, sale and service them, and scale upmarket with a phased approach;
the importance of leadership, culture and customer obsession to drive the expected business outcomes and build generational companies.
I’ll explore these key themes in a series of articles to share more than just soundbites.
Today, let’s start with product-market fit.
What is Product-Market Fit?
At the full day workshop Justin Wilcox, Customer Dev Labs, gave to our delegation on immersion day, he defined Product-Market Fit as “being in a good market with a product that can satisfy that market”, where the definition of ‘good’ belongs to you.
The systemic approach to establishing Product-Market Fit defined by Mark Roberge, senior lecturer at Harvard Business Review and former Chief Revenue Officer at Hubspot, in his 'Step by step guide to revenue growth' presentation, was one of the highlight sessions of the conference for many attendees.
Product-Market Fit should be measured by customer value creation, with customer success being the absolute priority during this initial phase. It is easier to scale a business with world class retention than fix retention while maintaining rapid growth.
Therefore it is critical to identify a customer success (or churn) leading indicator to track performance and establish Product-Market Fit.
Go-to-Market Fit is then measured using a speedometer to establish pace once you’ve got customers, as well as a repeatable sales & marketing process. It is as much about customer success metrics (logo retention ratio) than unit economics:
LTV/CAC>3 – is a customer worth more (Lifetime Value) than what it costs to sell to them (Cost to Acquire a Customer)?
payback period<12 – how many months does it take to payback the cost to sell to customers (CAC)?
Josh Stein, partner with VC firm Draper Fisher Jurvetson, reinforced the importance of using payback as a key metric in his presentation ‘How to lie to yourself with SaaS statistics’. If capital access is limited, a longer cash payback will hit your growth. That’s also an easier metric to measure early on.
Your growth phase is all about aligning Sales & Marketing respective SLAs, tracked live on a dashboard.
As 90% of customers start their buying journey online, Marketing should define a lead score (quality of companies vs level of engagement) whereas Sales should define the optimal number of times a sales rep need to call a prospect.
A great case study of applying a growth revenue framework and building a data-driven company culture was offered by Romain Lapeyre, Gorgias CEO, who demonstrated how they closed their first 1,000 customers.
Thanks to a well-structured technology stack, Georgias was able to deeply understand their market opportunity and leverage intent data to laser focus on ready-to-buy prospects. Their tailored sales approach, the constant data input to create a unified view of the customer, and the automation of the sales pipeline enabled them to double down on the most effective marketing channels and triple their close rate.
Leading with a very strong data-driven approach too, Tomasz Tunguz, Managing Director with Redpoint Ventures, presented the results of a quantitative analysis of 600 Freemium SaaS companies. This survey not only provides useful benchmarks for financial planning and goal setting, it also helps identify the right mechanisms to structure and test your free trials.
Here are his Top 10 learnings about free trials:
Stick with annual contracts – for most companies, having an annual contract tied to a free trial is the best opportunity, so stick with annual contracts unless there is a compelling reason.
Strive for a 90% logo retention rate YoY.
Target 100%-140% Net Dollar Retention – start-ups targeting enterprises typically see better NDR than those targeting smaller accounts.
Prefer time and usage-based trials – time-based free trials are most common across all segments. Time and usage-based trials convert twice as effectively as seats or feature-based trials.
Shorten trial length – 14 days free trials are most common but length doesn’t matter as all time-bound free trials convert at the same rate: if you have the point of maximum intent at the beginning, then shorten your free trial length.
Hire salespeople to call leads – salespeople increase conversion by 3.5x. Assisted conversion is more effective across all price points as it reinforces trust and assurance. Depending on whether you have a sales team,
Aim for 4% unassisted conversion rate, or
Shoot for at least 15% of assisted conversion.
Question activity scoring in Enterprise – free trial data has limitations when it comes to Enterprise sales: how people engage with your trial isn’t an accurate indicator of the final outcome and may lead to false conclusion. Considering the number of people involved in the buying decision, you’re unlikely looking at the right people.
Test requiring payment – even though it is not a widely spread practice, the data suggests that requiring payment at the start of your free trial increases the conversion rate by 2.5x.
Finally, Andy Wilson, co-founder & CEO Logikcull, shared his journey in growing Logikull ARR 'from $0-$10M in 19 Months' and the top mistakes he made along the way in 14 years of entrepreneurship.
What resonated most with me were:
the idea to build you SaaS business like a franchise to start nimble and establish a sustainable growth framework – this is something that we too often see with kiwi tech companies trying to address too many segments at once and not focussing on nailing one then moving onto the next with an iterative approach;
the need for a systematic and rigorous hiring and onboarding approach to ensure maximum fit and knowledge transfer – having clear objectives for the role, associated with a methodological screening of candidates (eg culture fit or skill tests) and a closely aligned 90-day plan, all help create efficient, collaborative and committed teams as I’ve seen first-hand in prior roles.
The ultimate realisation is how ill-equipped some kiwi tech companies are to compete with US SaaS machines, that use a proven framework over and over, using an end-to-end tech stack that provide them with ultimate insights into their buyers and users. By adopting a similar approach from the start, the likelihood to nail Product-Market Fit faster would increase as their ability to compete on a global scale.
In the next SaaStr Annual Digest, I’ll discuss market focus and scaling upmarket.
Feel free to reach out to me if you want my notes on any particular session highlighted above.