At SaaStr 2019 Tomasz Tunguz, Partner at Redpoint Ventures, presented survey results on B2B SaaS free trials. The survey revealed valuable learnings and we wanted to share and take a deeper dive on on some of the more surprising results.
But first, we want to thank Tom for sharing these valuable insights and encourage our readers to check out his blog post, Top 10 Learnings From The Redpoint Free Trial Survey. You can also listen to Tom discuss the survey results with Harry Stebbings on the official SaaStr Podcast episode 213.
For your convenience, we’ve attached Tom’s slide deck and Harry’s podcast episode at the bottom of this article.
The survey was born from Tom finding that many of their startups were running free trials as part of their marketing campaigns, yet the disciplines around free trial best practices aren’t well known. We at Productlift relate directly with this issue as it’s at the core of why we started this company.
To shine light on what the landscape looks like, they conducted a survey obtaining 600 responses across SaaS price points and buyer persona’s. The survey results provide excellent insight into questions that many B2B SaaS organizations are asking.
Questions to ask when launching free trial campaigns.
The hypothesis of offering free trials is that when someone signs up, it’s the point of maximum intent (the point in a buyer journey when they are most likely to buy). We’re going to focus on these three emboldened points.
- What impact do free trials have on conversion rates for monthly, annual, or multi-year contracts?
- What are the optimal free trial structures?
- How do free trial behaviors differ across personas?
- How does the ACV price point affect free trial conversions?
- How do conversion rates differ between assisted and unassisted trial account leads?
- What impact do salespeople have on conversion rates when contacting leads during their free trial?
- How does lead scoring affect conversion rates?
How do conversion rates differ between assisted and unassisted trial accounts leads?
Unassisted conversions happen when the sales person does not touch the lead. From the survey data, the optimal unassisted conversion rates ranged between 4-5%. This is considered good, but only when when you consider a large enough sample size. As Tom mentions, great conversion rates on a small number of people isn’t nearly as meaningful.
“If you are seeing 6-7% unassisted conversion rates, growing 15% or more a month on a super capital efficient base, I’ll be falling over myself to invest.”
– Tomasz Tunguz
Assisted conversion rates are more nuanced since SaaS companies differ in where they measure conversion points in the sale cycle (Stage 1 vs Stage 2, MQL vs SQL, etc.) The survey data revealed that optimal conversion rates for assisted leads an impressive 15%.
What impact do salespeople have on conversion rates when contacting leads during their free trial?
When comparing the 50th percentile of assisted and unassisted conversion rates, salespeople are achieving a 3x higher conversion rate.
An interesting note that Tom mentions is that when they look at the distribution of different respondents, assisted conversion rates have a uniform distribution whereas unassisted follow a power law relationship.
What this means is that when a company can obtain high unassisted conversion rates (10-15%) they’ve have achieved exceptional product market fit combined with a very honed funnel. Very strong signs of growth, but few companies are able to achieve this.
For companies that are not hitting those numbers, having salespeople interact with free trial leads will actually help get better conversion rates.
“One of the conclusions from the survey was that if your price point allows for it, which is typically something like a $10 or a $12K ACV, you really should be hiring it AEs to call your leads.”
– Tomasz Tunguz
How does lead scoring affect conversion rates?
Here is where things get really interesting. It’s a lot to piece together but we’ll try to lay it out as best we can.
The survey results revealed that lead scoring for mid-market/enterprise price points ($15k ACV and above) resulted in a negative signal. This means that when salespeople used lead scoring they achieved lower conversion rates.
Tom has machine learning background from his time at Google where they used an in-house tool called Glengarry (possibly an ode to the dialogue heavy salesperson movie Glengarry Glen Ross). They scored Google Ads users based on their engagement to come up with an Activity score. In Tom’s experience, they found the data to be “super impactful” but the results of this survey run counter to this experience.
The hypothesis is that mid-market/enterprise trial account user experiences greatly differ than SMB. The person reviewing the product and the consumer of the would have very different engagement activity.
For example, during the free trial period the champion may dabble in the product for 5-10 minutes, then go talk internally to build consensus and work with procurement teams and finance to get budget.
If you disqualify them out purely based on their engagement activity, especially at higher ACV ($50-$150k ACV) then you’re missing out on material revenue opportunity. The survey showed that conversion rates of salespeople not using activity lead scoring was 4x higher.
About Tomasz Tunguz
Tom began his career working with his dad at a startup when he was just seventeen years old in South America. Upon finishing college and grad school, he went on to work at Appian. From there he went to Google as a Product Manager in Ads, where he got to work closely with Machine Learning. Tom Currently is the General Partner at Redpoint Ventures.