NPLG 6.8.23: The Decision-Free Sales Process (Guest Blog Post)
NPLG 6.8.23: The Decision-Free Sales Process (Guest Blog Post)
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The Decision-Free Sales Process
“Is your sales process over-emphasizing the need to make a decision?
People hate making decisions, so I set out on a mission to define a decision-free sales process. The result is a product-led growth strategy with more profitable unit economics and a vastly better customer experience. That’s the sales strategy we’ve adopted at my company, Visor.
Visor is the world's most deeply connected spreadsheet. Unlike disconnected spreadsheets and complicated integrations, Visor is a flexible project management platform that can evolve as your needs do, has built-in two-way integrations you can trust, and offers real-time collaboration features to bring everyone together. We support Jira users and agile teams, and we specialize in customizable, plug and play Gantt charts.
At Visor, we’ve doubled our staff in the past 6 months and drawn key investor support despite the current downturn in the tech economy, in part because of how easy we make it for our customers to not have to make a decision, while still supporting our product growth.
Why we hate making decisions
People are so hard-wired to defer and avoid making decisions that we'll often make suboptimal choices just to avoid them. For example, researchers at Cornell University found that sports teams prefer strategies that defer immediate decisions and results, even if they're less likely to win by taking the slower, less decisive option.
Two well-observed psychological phenomena support our decision-avoidance.
Omission bias
Omission bias is our tendency to prefer harmful inactions over harmful actions. Even if it would be better to take some action, people bias towards inaction. Generally, people would rather not have to take responsibility for the side effects and consequences of taking action.
A common thought experiment that shows this is the Trolley Problem. With a runaway trolley approaching a fork in the track, you find yourself with two options:
Do nothing and the trolley will careen into a brick wall, killing all five people aboard
Pull a lever and switch the trolley onto a safer track, killing one person who was standing on it.
Most would agree that Option B is the most morally sound. But many would choose Option A because it involves taking no action, taking less personal responsibility for the consequences.
In software sales, this indecision bias prevents people from trying new things. A new product could be vastly better, but introduces the possibility of new downsides.
A customer might wonder:
What if the product malfunctions and deletes all my data?
What if I get in trouble for using an insecure product?
What if my colleagues don’t adopt the product and I lose social capital?
What if I’m not skilled enough to use this product?
Choice deferral
People also like to defer decisions. We tend to believe that with more time and more research, clarity will come.
This is one of the reasons VC investors rarely say no outright. Even if a company doesn't meet the investor's criteria, they keep options open and defer. After all, things can change.
The same happens with purchase decisions. We want to wait and see.
In fact, our desire to wait-and-see is so strong that we'll work harder on making the decision if we get the opportunity to defer it. Research shows that consumers who can delay making a decision are then more willing to make efforts to make a decision later.
In other words, if you let people defer a decision, they'll more likely become more comfortable making that decision later.
Traditional sales magnify decision stress
Sales training lore holds that the capital-D Decision is the moment in time right after the decision-maker, sitting atop a marble throne of wisdom, carefully weighs their options. They review whitepapers, testimonials, master service agreements, special pricing, and even the charm of the salespeople. They consider the opinions of all the various internal stakeholders. And at one precise moment in time, with a few digital scribbles on a virtual paper, the esteemed decision maker does what they've been entrusted to do: They decide.
Docusigns fly like Nike, the goddess of victory, down from craggy Mount Olympus. Money transfers electronically. Congratulations all around. The sales process is done. The future is certain. A decision has been reached!
Some complicated products and services, like SaaS products serving enterprise-wide global teams, need a process like this with a definitive decision. But many products have the power to deliver value without scaling Olympus. When such products over-rotate on decision making, they create an unnecessarily stressful buying experience.
Product-led growth strategies eliminate decisions
Eliminating the most dreaded part of a new software purchase is a great way to improve customer experience.
But how exactly can you eliminate a decision from a purchase?
The key lies in creating micro-decisions that are so small — and have a reward associated with them — that they cease to become decisions at all. They become more like tiny investments, each with some return. A giant cliff of decision becomes a sweeping, gradual incline of investment. It feels more like playing a game than buying a product.
At Visor, one of our main onboarding goals is to keep driving the user deeper into the product to achieve greater-and-greater value. In fact, we take advantage of an arbitrage opportunity in how people value time vs. money.
People tend to over-value their money and under-value their time. We see that people will gladly spend hours exploring a free solution, even if they're unwilling to pay even a few dollars.
Freemium strategies make the most of this, replacing an upfront commitment of money with a less costly commitment of time. As you spend more time with the product, ideally you're getting more value.
Not all product-led growth strategies do this. Products with a free-trial inevitably force some decision; you either pay and continue or you don't and you lose access. It's a perfectly valid strategy for some products, but it puts emphasis on making a decision at the end.
At Visor, we've implemented a freemium strategy, and obliterated the decision-making. Yes, we do charge users. But we've refined our billing plans to only ask users to pay when they're getting value from the product. When the product prompts them to begin paying, there really is no decision to make anymore; Visor is their product.
Success relies on confidence in your product. You need to be confident that users will use the product enough that when the time comes to pay, it's not a decision at all. It's just a little more investment.
Myth: Product-led growth means ignoring customers
A strong product-led growth strategy still requires extensive direct user engagement. Rather than having a sales team helping users to make a decision, Visor, for example, has a success team that helps users get value.
Our success function has two crucial objectives:
The success team's first goal is to engage with users and help them get value. This strategy thrives on the belief that we have to give value before we get value. Our success team doesn’t discuss decisions or payment. Our product's freemium limits ask users to pay. This creates a more trusting relationship between our success team and the customers they serve.
The success team's secondary goal is to surface customer learnings to the team. By spending time helping users get value, they establish an understanding of where the product can improve. Then, they funnel these ideas directly to the product team. Combined with quantitative analysis, this directs the product team and overall strategy.
Many companies that start out with a product-led growth strategy do hire effective sales teams eventually, as products get more complicated and deals get larger. But they only gain the privilege of growing that large after they’ve built a product that has gained sizable market traction — and they achieved that via product-led growth.
The question is then: what strategy will you decide on for your business, now?
Or would you rather defer that decision?”
I would love feedback. Please hit me up on twitter @zacharydewitt or email me at zach@wing.vc. If you were forwarded this email and are interested in getting a weekly update on the best PLG companies, please join our growing community by subscribing.
PLG Benchmarking (Startups):
This is a new section! I will continue to update these metrics and add new metrics. I would love your feedback on what else I should track.
Conversion rate (website → free user):
Best: 10%
Good: 5%
Activation rate (free user → activated user):
Best: 60%
Good: 30%
Paid conversion rate (free user → paid user):
Best: 8%
Good: 4%
Enterprise conversion rate (free user → enterprise plan):
Best: 4%
Good: 2%
3-month user retention (% of all users still using product after 3 months):
Best: 30%
Good: 15%
Conversion from waitlist to free user:
<1 month on waitlist: ~50%
>3 months on waitlist: 20%
For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior NPLG.
PLG Financial Benchmarking (Public PLG Companies):
Financial data as of previous business day market close.
Best-in-Class PLG Benchmarking:
15 Highest PLG EV / NTM Multiples:
15 Biggest PLG Stock Gainers (1 month):
Complete Notorious PLG Dataset (click to zoom):
Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.
Recent PLG Financings (Private Companies):
Seed:
Dumme, a developer of a content automation platform intended to search information through video, has raised $3.4M. The round was funded by Y Combinator, Caffeinated Capital, SciFi VC and Protocol Labs.
MindsDB, a developer of predictive tools designed to help organizations apply machine learning to their data, has raised $41.5M at a $81.5M valuation. The round was led by Mayfield, with participation from Benchmark and TQ Ventures.
Vectera, a developer of an AI-powered text search platform designed to reliably bring sophisticated semantic search capabilities to any organization, has raised $28.5M at a $128.5M valuation. The round was led by Race Capital, with participation from OODA Ventures, Brighter Capital, Feld Ventures, Green Sands Equity, NKM Capital, MDSV Capital, Vertex Ventures US, BECO Capital, Sparq Capital, Raed Ventures, Essence Venture Capital, GTM Capital, Transform VC, Page One Ventures, Top Harvest Capital, Fusion Fund and Spark Labs.
Zeliq, a B2B sales platform intended to power up conversations and pipelines, has raised $5.4M. The round was led by Resonance VC, with participation from Groupe Duval and OBRATORI.
Series A:
Korbit, a developer of an AI tool that does code reviews, detects and assigns issues, and teaches engineers how-to fix the issues, all within their workflow, has raised $8.34M. The round was led by Khosla Ventures, with participation from Desjardins Capital, Global Brain, Alumni Ventures, Graphite Ventures, True Equity, ETF@JFFLabs, and Merus Capital.
Predibase, a machine learning platform designed to make writing high-performance, low-code machine learning algorithms easy, has raised $28.4M. The round was led by Felicis with participation from Greylock Partners and The Factory.
Series B:
CoreWeave, a cloud infrastructure platform intended to provide computing resources for blockchain and other projects, has raised $421M at a $2.43B valuation. The round was led by Magnetar Capital, with participation from Nvidia.