The Sales Learning Curve Part I: Introduction
The piece of writing that has most shaped my thinking about startup sales
The Sales Learning Curve1 is one of the few genuinely useful things I’ve ever read about sales; it’s particularly important to startup sales. Fun bit of background: I got this piece of writing from the worst boss I’ve ever had. Turns out everyone has something to teach us.
The article is chock full of insight. The authors, Mark Leslie and Charles Holloway, introduce the concept of the sales learning curve by distinguishing it from the learning curve an individual sales rep must climb after he is hired. The sales learning curve is about organizational learning.
Progress along the sales learning curve is measured in an analogous way: The more a company learns about its product, market, and sales process, the more efficient it becomes at selling, and the higher the sales yield. “Sales yield” is defined as the average annual sales revenue per full-time, fully trained and effective sales representative. Typically, sales yield for a new product starts out slowly, accelerates for a while, and then flattens out as the product matures, in a classic S-shape curve. The steepness of the curve—a measure of how rapidly product revenues reach the break-even point and then achieve targeted levels—varies substantially from product to product.2
This curve serves as the foundational framework for thinking about sales for new products, new markets, and in our case, new companies. Notice that much of the learning comes to life outside of the sales department.
The authors are careful to note that you cannot hire an army of people to gather this knowledge in some parallelized fashion so you can learn it all at once. A great deal of the process unfolds sequentially, or as we in the startup world like to say, iteratively.
Leslie and Holloway break the curve into three phases: initiation, transition and execution. Since the initiation phase usually encompasses everything that happens until just about Series B, I’m going to quote liberally from this section:
This phase begins when the product is ready to hit the market, that is, when it has been beta tested, and lasts until the break-even point—that is, when sales yield reaches a point where revenue per sales rep equals the fully loaded cost per sales rep. Typically, during this time, few customers will be willing to consider buying the product, and those that do will require significant incentives.
It’s both unrealistic and potentially dysfunctional to assign large sales quotas in the initiation phase. The members of the sales team should be encouraged to focus instead on learning as much as they can about how customers will use the product so they can support engineering, product marketing, and marketing communications in perfecting both the offering itself and the go-to-market strategy and programs. A heavily commission-based pay plan is not only unlikely to achieve sales objectives but can inhibit learning.
It’s also inefficient to hire too many sales reps in this phase. A small sales force not only keeps costs down but is more effective in supporting other parts of the company. Typically, three to four salespeople are enough to start the learning process and to make sure that the problems encountered aren’t just the result of a bad hire.
The types of skills needed during this phase differ from those needed to sell more mature products. They include a facility for communicating with many parts of the organization, a tolerance of ambiguity, a deep interest in the product technology, and a talent for bringing customers together with various functional teams within the company. Salespeople must be resourceful, able to develop their own sales models and collateral materials as needed. We think of this kind of person as the “renaissance rep.”3
Note here that Leslie and Holloway aren’t really talking about startups per se. Their audience is post-beta executives at big companies breaking into new geographies, or offering adjacent products to familiar markets. Unless your startup is selling a small tweak on a familiar product to a known market, you have to assume you start even farther behind on this learning curve. And insofar as their analysis is right, you should, a fortiori4, figure their tactics apply to you and perhaps take them a step further.
The key takeaways for startups then are:
Don’t assume that hiring more sales staff will make you grow faster
Learning is paramount for your sales function
Plan to lose money on reps
Heavily commission-based plans won’t help, and will likely hurt, learning
Quotas are a guessing game and should usually be avoided
You need very specific types of sales reps (“renaissance reps”), and often these are not the same ones that are successful at later stages
In Part II of this Series, I’ll address the the first three insights and how this should affect your hiring strategy. In Part III, I’ll discuss commissions and quota and how these should look and evolve in different contexts. Part IV will focus on the renaissance rep profile and its interaction with the rest of the company, which is a necessary and poorly understood part of the early learning curve. Finally, since renaissance reps are in short supply, part V will help you think tactically about staffing workarounds.
Addendum: wondering if you are the exception
Like every rule, there are exceptions. I recently met an entrepreneur whose company, two months after pre-seed, started selling software like hotcakes and has grown to nine salespeople. But his situation is vanishingly rare. The company stumbled into product/market fit at a rate we can only be assume was luck, despite the fact that he’s a top notch, super smart guy. Also, their sale turns out to be unusually straightforward, so much so that they are already thinking about how to migrate most transactions toward a self-serve model. In fact they are already able to hire directly from other vendors in the industry. This means they are probably mostly “coin-operated reps,” which are usually only effective in the later stages of learning. All signs suggest that this company is much farther ahead on the sales learning curve than what its funding stage implies. And as you can imagine, the VCs are circling, trying to convince this guy to take more money than he can come up with ideas to spend it on.
But his example is the rare exception that proves the rule. He may be the first entrepreneur I’ve met in such a spot. Sure, you might hear rumblings about others, but there is serious selection bias behind such rumors. Don’t let the availability heuristic distort your thinking here. Also, geniuses who find product/market fit because of their maverick prescience make for great Aaron Sorkin screenwriting, but don’t have much to do with the reality behind the storytelling. Most big winners really just turned over the entrepreneurial equivalent of a Royal Flush5 and rode that luck to the bank. Assume you should play by the rules here. I’m sure you are a very special snowflake. But if in this case you are the exception, it will become patently obvious.
The Sales Learning Curve, Mark Leslie and Charles Holloway, Harvard Business Review, Jul.-Aug., 2006.
Dude, I’m a renaissance rep; expect some Latin.
If you aren’t convinced about the role of luck in these kind of outcomes, I suggest you review some of the social science writing on the topic. Success and Luck, by the Economist Robert Frank, is a good introduction. It turns out that small variations that we can all accept exist in the luck lottery are more than enough to explain massive disparities in outcomes.