In Defense of Troublemakers. I love the title. Who doesn’t want to be a troublemaker? Charlan Nemeth is a professor at Berkeley of Psychology. She’s studied the role of dissent in group decision-making and written this book on the topic. It’s a critical part of a functioning team.
Here’s what I learned from the book:
The minority, dissenting opinion in an argument is essential to ensure we make the best decisions.
When we are exposed to dissent, our thinking does not narrow as it does when we are exposed to consensus. In fact, dissent broadens our thinking.
This is because dissenters often share a critical perspective or data point that the majority didn’t know or hasn’t considered. That “one piece of unique information could change the whole picture and the final decision”
Importantly, dissenting opinions don’t have to be correct to improve the decision. Dissent breaks the blind following of the consensus and dissent stimulates thought that is more divergent. By exploring a problem space more broadly, a group makes a better decision.
But dissent in a room must be genuine. Tools like playing Devil’s Advocate work only if the person playing Satan’s lawyer genuinely believes in the dissenting view or genuinely wants to explore the other argument.
Creating a culture that actively encourages dissent is one of the hardest managerial challenges. Teammates must trust each other to be able to argue a minority position, and to feel confident enough to explore new angles, share new data points, and take the time to debate an issue, rather than simply agreeing with the majority.
If you’re curious about the research and findings on dissent, and the techniques to foster more dissent within your team, this is a good book.
After publishing the survey last week, I received many questions. I’ve answered a few here. I’m happy the data has garnered so much interest and I hope it’s helping with our two goals of sharing benchmarks and sparking conversations about how to optimize trial. If you have stories or data that buttresses or contradicts any of these findings, please share them. I’d love to publish them here. Also, if you have ideas for future surveys like this, send them my way.
Matt asked: Is there any meaningful difference in conversion or other metrics for companies in different ARR buckets?
Not substantially. Chart below.
There are some variances across ARR buckets. I would have expected companies in the $1M or less in ARR to observe lower conversion rates because they are earlier in their go-to-market development. Consequently, earlier startups might have a lower conversion baseline, whereas a business at $20M in ARR has spent several years optimizing trial.
But statistical tests indicate that the differences in conversion rates aren’t meaningful.
Jonathan asked: Can you share trial length by market segment?
This was a good intuition. Enterprises tend to use longer free trials than their SMB counterparts. This may be due a perception that enterprise buyers navigate longer and more complex decision-making process. But the conversion rates across different trial lengths aren’t different to statistical significance.
And can you show payment collected by ARR?
The popularity of requiring payment is constant across ARR buckets. The only one that stands out is the $150M ARR bucket, but there weren’t many of those in the respondent set, so the result is skewed by a small sample set.
Jason asked: when you wrote “require payment to start trial,” does that mean collecting payment information or actually charging the card?
I suspect the effect on the top of the funnel and the ultimate conversion rate is the same. But charging the card immediately would mean the trial wasn’t free! And if they did cancel the trial, you would have to credit accounts which could get tricky.
Andrew asked: Does requiring payment have an impact on retention? And when is that conversion counted… is that on payment capture?
Good question. We don’t have the data to answer it.
Dustin asked: Was there any meaningful impact in combining free trial limiters? ie. a usage + time bound free trial model converting better than usage or time alone?
We didn’t ask this in the survey, so I don’t have a good answer for this. Perhaps a useful question to ask in the future.
As you build out your startup’s financial model for 2019, a key component will be the hiring plan. You’ll need to calculate the number of managers and individual contributors to achieve your goals. But don’t forget to plan for mishires.
You will make mistakes hiring people. We all do and it’s part of the process of building a company. Someone looks great on paper but isn’t a culture fit. Another doesn’t ramp quickly enough. A third might not have the work ethic. Whatever the reason, it will happen.
In the hiring plan, you should anticipate this. Many startups plan to over-hire in sales, but not in other departments. Why is this? It’s because AE hiring is directly tied to bookings capacity and consequently growth. A mis-hire might cost the business $500k in ARR, which can be the difference between growing 2x and 2.5x at the early stages. So it matters.
Overhiring in other GTM teams like customer support, customer success, sales engineering should be considered, especially if the company is on a steep ramp and hiring quickly; and the business has the balance sheet to support this hedging strategy.
There’s no way to know exactly what fraction of hires won’t work out. Many businesses project 20% mis-hire rate, which is a good initial estimate.
Whatever your estimate, take the time to think through over-hiring in the key GTM and support teams to ensure you’ll have the right capacity to support your growing customer base.
Before we’d leave campus - Christmas vacation or spring break or summer vacation - our rowing coach would tell us, “You’re either getting faster or you’re getting slower. There’s no such thing as staying the same.” It was his way of inspiring us to train hard during those times. I’ve never forgotten it.
More recently I came across two math equations that confers the same idea, with a twist. The compounding effect of improving every day.
What if you could improve how you do something by 1% each day for a year? You’d be 37x better. What if your performance declined by 1% every day for a year. You’d lose 97% of your performance.
It’s a reminder that getting just a little bit better every day has dramatic effects in relatively short periods of time. To bastardize Einstein: Compounding improvement is the most powerful force in the universe.
When we distributed the survey, we never would have expected the response. About 600 companies submitted data. They span single digit ARR businesses to publicly traded SaaS companies. These businesses sell at every price point and sell to every operational buyer. From product to sales, from legal to marketing.
We processed the data with 1000+ lines of R code to parse the insights from the data and test for statistical significance.
In sharing the results, we have two goals
Share benchmarks to calibrate your startup’s free trials
Spark conversations about new free trial tests to run for your startup.
Let’s jump into the list.
Annual Contracts Dominate. Between 60-80% of respondents tie annual contracts to free trials. Annual contracts dominate in the mid-market. In the SMB, month to month is more common. In the enterprise, multi-year contracts emerge. As we dug into the data, we couldn’t find any meaningful difference in free trial conversion based on contract length. So, stick to annual contracts unless you have a good reason to diverge.
Aim for 90%+ Logo Retention. More than one-third of respondents retain 90% or more of their customers by count one year after acquiring them. Higher rates of customer retention are more common in the mid-market and enterprise.
Target 100-140% Net Dollar Retention. The top quartile of respondents observe net dollar retention of 120%+. The top decile grow at 140%. Startups targeting enterprises typically see better NDR than those targeting smaller accounts.
Time and Usage Based Free Trials Convert Better. There are four ways to limit trial. Usage: 500 of API calls, then upgrade. Seats: first two seats free. Time: 30 day trial. Feature: upgrade for better security. Time and Usage based trials have at least 2x the conversion rates.
Conversion Rates Aren’t Impacted by Trial Length. Shorten Trial Length. Most companies employ 14 day trial. But all time-bound free trials convert at the same rate.
Salespeople Increase Conversion by 3.5x+. 75% of respondents employ salespeople to call upon prospects. This is true across every price point.
Target 4%+ Unassisted Conversion. The 50th percentile of respondents convert 4% of leads to paying customers, when the conversion is unassisted (doesn’t involve a salesperson).
Target 15%+ Assisted Conversion. The 50th percentile convert 15.5% of free trial leads to paying customers when assisted by a salesperson.
Scoring Leads by Activity May Lead to False Conclusions. Many companies use activity data to score leads. How frequently someone uses the product, how many people were invited etc. The data suggests activity scoring may be disqualifying good leads because bigger buyers exhibit different usage patterns before buying.
Requiring payment Increases Conversion Rate by 2.5x. Only 12% of respondents require payment to start trial. The others bet that by filling the top of the funnel with more leads and getting data on prospective leads is a better trade. The data suggests it’s worth testing payment requirement for mid-market and SMB price points.
Thank you to everyone who participated in the survey, and in particular to my colleague Patrick Chase. If you have questions or observations about this data, please email me or send me a tweet.
The first wave of SaaS is 20 years old. Today, the SaaS model dominates. But we’re seeing the emergence of a different type of next-generation software company. A new wave of companies that is responding to the changing needs of customers by innovating their architecture. Very simply, they liberate the database from the application.
In license software, the database ran alongside the application on-prem. In SaaS, the database runs next to the application in the cloud. But what if you freed customers from this constraint, and gave the customer the choice of where to run each? Suddenly, the customer is in control of their data in a way they never can be with SaaS.
Customers can choose where to host the database, how to secure it, monitor it, ensure it complies with new data privacy regulations, limit access, and service it. They can run it in their cloud, in a VPC or on premises.
Meanwhile, the application is delivered as any other SaaS app. It’s updated just as quickly. Even better when the app is open source. Customers can audit the code, fork it to customize it, and embed it wherever.
We’ve been looking for companies building software this way. Today, I’m thrilled to announce our investment in and partnership with Mattermost.
Mattermost embodies this new wave of software companies. They deliver open source messaging to secure enterprises and DevOps teams. They work with Uber, USAA, Department of Defense, ING, Bristol Meyers, Virgin, Samsung and many others.
We’ve spent a long time getting to know Ian and the terrific team at Mattermost. In that time, we’ve been impressed by three things. First, the recognition by the most demanding teams that this new data architecture satisfies their requirements. Second, how this model has propelled the business to far larger revenue than typical at a Series A. Third, the explosive distribution of open source also applies at the application tier, not just infrastructure.
If you’re a developer looking for a high performance, secure messenger, or you work in an enterprise that values control over data, give it a whirl.
As you start to go to market, there are two things to prioritize from early customers that matter more than cash. Feedback and marketing rights.
The feedback matters for obvious reasons. The product is early; customer feedback will help you hew the raw granite of your initial product into shape.
The second may not be so obvious. Every prospect championing a software purchase will be asked by the opponents of the sale and decision-makers: “Who else is using the software?” The more impressive your customer list, the stronger the case your champion can extol. Logos confer credibility.
That’s why logos are worth more than cash. If you negotiate the rights to market some great customer brands, you’ll be able to use them in every sales process, in every press release, in every recruiting conversation. That’s worth much more than cash and larger bookings in the early days.
A great customer logo slide is like a bank account. It compounds its value with time. Great brands attract other great brands. Be sure to invest early in those logos, even at the material expense of bookings.
Late last year, my colleague Pat Chase and I announced the Redpoint Free Trial SaaS Survey. Over the course of a few weeks, we received roughly 600 responses from SaaS startups who use these marketing techniques. They span companies from $1M in ARR to more than $100M. The respondents sold into every key function of a business and at all different price points. On February 5 at 10am, I’ll be sharing the top 10 learnings from the survey at [Saastr](). After the conference, I’ll post the slides with the conclusions here.
This is the first time we’ve run a large scale survey. We were surprised in three ways.
The first is the amount of responses; we were stunned by the volume of data and willingness to share. Thank you to everyone who contributed.
Second, it takes quite a bit of work to analyze the data, far more than I expected. We wrote more than 1000 lines of code to identify the ways startups use free trials. We cut the data by contract size, target buyer, free trial structure, and many other dimensions. Then we tested the results for statistical significance to ensure we’re pointing startups in the right direction.
Third, the data suggests that some of the common knowledge about free trials is correct. And some of it deserves more testing. But that most of the conclusions apply across a broad base of startups. I’m excited to share more soon.
It’s very difficult question to answer. How do you judge a leader? Is it financial success? The loyalty they engender? Their ability to inspire? There are war-time leaders and peace-time leaders. Leaders may be understated or zealous. I’m not sure we’ll ever be able to say definitively what constitutes a great leader. Regardless, we all want to improve our ability to lead, whether it’s a small team or a Fortune 500. But how?
One way of looking at leadership development is through Adult Development Theory, an idea pioneered by Dr. Robert Kegan, a developmental psychologist at Harvard that borrows from others in the field.
Adult development theory has five stages. The first two we develop in childhood: impulsive mind and imperial mind. The next three we learn in adulthood. I’ve put together a quick summary below. For greater depth, there’s a good overview here.
Socialized Mind (most adults): we have built relationships with our team and those social connections influence our ideas the most. We see ourselves the way others see us and look for external validation from others about how we’re doing as leaders.
Self-Authoring Mind (some adults): we shift from validating ourselves in the eyes of others to establishing an internal sense of self, and begin to direct ourselves independently. We have limits, values, goals and drive that comes from within, and those govern our leadership.
Self-Transforming Mind (very few adults): we’re able to balance both the perspectives of others with our our sense of self-direction. Tricky business!
If I think about the style of management epitomized by Steve Jobs (or at the least the public perception of his management style), he would be in the self-authoring mind, caring very little for others’ perspectives. Reading some books including Creative Selection, I’m sure Jobs’ style was more nuanced.
Both believe the core of leadership starts with listening and then being able to balance the external points of view with a strong sense of self (values, direction, belief).
Maybe that’s why leadership is so hard to evaluate. It all comes down to judging many opinions including our own and managing relationships well after the decisions are made.
This framework got me thinking about where I am in the Adult Development Theory. Kegan said that we all see ourselves one step ahead in development of where we actually are. Where are you? Where do you want to get to?
Over the weekend, the [NY Times interviewed a classmate]() of mine from Dartmouth and fellow oarsman on the freshman crew team, Cal Newport, about his book and his idea, Deep Work. Here’s the crux of the idea:
Deep work is my term for the activity of focusing without distraction on a cognitively demanding task. It describes, in other words, when you’re really locked into doing something hard with your mind…In order for a session to count as deep work there must be zero distractions. Even a quick glance at your phone or email inbox can significantly reduce your performance due to the cost of context switching.
The longer I work in technology, the more I value long blocks of uninterrupted time. It’s probably the scarcest resource at work. When is the last time you had 90 minutes to work on a project without an interruption: a phone call, a text message, an email, a buzz or a ring or a knock?
In a different book Make Time by two Googlers, Jake Knapp and John Zeratsky introduce the infinity pool. The infinity pool is technology that deliberately devours as much of your time as possible. We all have these insatiable monsters in our pockets. They are boredom cures, fixes for dopamine desire, triggered by a two minute YouTube video, a quick Fortnight campaign, a voyeur’s social media blitz.
In Make Time, the authors advise you not to wait for technology to give you back your time. Because it won’t. There are PhDs in every discipline learning how to take it from you.
The authors advocate extreme measures to combat the algorithms using our predilections for newness against us. Delete all infinity pools from your phone. It’s an interesting experiment, but I’m not ready to go that far.
Instead, I installed an app that recorded each time I activated my phone, and challenged myself to reduce it touches from about 40 to about 20 times per day, which I thought was great. But then I realized, that’s still more than once per hour. A long way to go. They also push for checking email once per day, which might be possible in some work environments, but definitely not for me.
Deep work is the most satisfying work. I like to write early in the morning because then I have the luxury of uninterruptedness. I’m sure we all know that feeling. We can make real progress in short periods of time; we’re at our intellectual peak. We have to defend it, first by being aware of the challenges impeding our focus.