“I’m into distribution, I’m like Atlantic
I got them mutherfuckers flying’ cross the Atlantic”
–Rick Ross, “Hustlin’“
When I ask new entrepreneurs what their distribution model will be, I often get answers like: “I don’t want to hire any of those Rolex-wearing, BMW-driving, overly aggressive enterprise sales slimeballs, so we are going to distribute our product like Dropbox did.” In addition to taking stereotyping to a whole new level, this answer demonstrates a deep misunderstanding of how sales channels should be designed.
What is a sales channel? It’s a route to market for a product or set of products. It can range from your website to a sophisticated sales force. The sale itself must be supported with the right marketing, process, and optimization strategy. Selecting the right channel is critical for any business — and products often fail because the company chose the wrong route to market.
When designing a distribution strategy, one should never begin with the sales channel itself. A properly designed sales channel is a function of the product that you have built and the target — i.e., customers or market — that you wish to pursue. In mathematical notation, think of your channel (c) as the output of your distribution design (f) with product (p) and your target (t) as inputs, or:
f(p,t) = c
Note that this function accepts only one product and one target as input, so if you have multiple products and/or targets, you might need multiple sales channels.
So what does a channel function design look like? What does (f) do? Let’s explore a basic version. First we will consider the different kinds of product designs and how they might impact your channel (c) decision. The first dimension that we’ll look at is how the product (p) might be delivered to the customer or target (t). There are two high-level possibilities:
A. It can be delivered online (examples: Box, Dropbox, Okta, Salesforce, Workday)
B. It can be delivered only via a delivery service, a sales person, or in a store (examples: a smart watch, a robot toy, a smart security camera)
The second dimension that we’ll consider is the amount of assistance that the product requires to begin using it, if any. These vary across a spectrum:
A. No assistance required (examples: Github, Slack)
B. Minor assistance required (example: Okta)
C. Major assistance and consulting/ professional services required (examples: Palantir, Pivotal)
Note that the amount of assistance may change based on the profile of the customer. For a very small business, “self-serve” companies like Dropbox, Salesforce.com, and Slack might not require much assistance and so fit into category B. But for a large enterprise that expects major support especially given the size of their contract — or where the product needs to be integrated with other technology they have (e.g., migrating data off legacy servers, or connecting to other tools) — even a seemingly self-serve product will require major assistance and thus be in category C. This is also a typical trajectory for products that start off with viral, bottoms-up (e.g., departmental-level) adoption in the company but then end up being adopted company-wide.
We can now classify various products by their distribution characteristics:
[A,A] can be delivered online, no assistance required: Github; Dropbox, Slack (for small companies)
[A,B] can be delivered online, minor assistance required: Okta, Saleforce (for small companies)
[A,C] can be delivered online, major assistance required: Oracle Financials, Palantir; Dropbox, Salesforce, Slack (for large companies)
[B,A] not delivered directly, no assistance required: Anki Overdrive, Apple Watch
[B,B] not delivered directly, some assistance required: Nest Thermostat
[B,C] not delivered directly, major assistance required: EMC Symmetrix
Next, we look at target decision makers; this matters because different decision making processes require different sales strategies. The key here is not so much the size of the organization, but the manner in which they make a decision. This is a subtle, but critically important point: If a business makes a decision on a product in the exact way that a consumer makes a decision, then it’s more like a consumer. If a business has a complex purchasing process with dozens of constituents that must sign off, it starts to look more like the U.S. government. Note that no matter how hard you may try, you will NOT be able to change your target’s decision making process, so you need to design your sales channel to meet their needs not yours. In this context, we can think about some example targets:
I. Individual — a direct consumer or a single decision maker in a company
II. Small group — a small engineering team deciding, such as with Trello or job ATSs
III. Entire small company (<1000 employees) — for example, deciding on HR software like Zenefits
IV. Large group — multiple decision makers, with different economic and technical motivations for deciding on the product
V. Multiple groups simultaneously — for example, sales and marketing both needing to agree on the right marketing automation solution
VI. An entire large company — for example, deciding on an HR system like Workday
Next, we will consider some rules of thumb for designing a channel to reach these types of targets depending on the product characteristics discussed earlier.
Targets I and II involve the same simple decision making process: The customer asks herself, is this something that can help me and is worth the money and effort? These targets therefore can often be sold entirely via marketing; viral distribution (if you have a product that inherently travels by word of mouth or other organic spread); and optionally telesales (particularly if you have an [A,B] product).
If you are going after targets I and II and you have an [A, C] or a [B,C] product, God help you as you will surely go bankrupt.
Target III decisions generally involve multiple people so are more complex, but there are clear decision makers there who can act quickly for that type of product. Still, these targets generally require a human in the loop to help navigate the decision-making process and explain the economic and technical benefits of the product in greater depth. Sometimes, this involves setting the buying criteria and upleveling the sell beyond features and benefits. This is where a salesperson can help — also positioning the product against competitors’ products or previous conflicting decisions — more effectively than a website or a product that speaks for itself.
For this size of company, [A,C] and [B,C] products are typically too expensive to sell because the cost of sale typically outstrips the profit margin on the product.
Targets IV-VI not only represent complex decision-making processes, but nobody inside the customer actually knows how the decision will get made. This isn’t because the companies are stupid, it’s because they are doing something they almost never do. How often does any company buy an HR system? Once a decade? If a large organization does something once a decade or the first time ever, they likely will not have a process for doing it. In particular, who gets to weigh in on the new HR System? The CISO? The CIO? The VP of Engineering? Chances are, the customer does not know yet. As a result, these targets almost always require a human in the loop and often require an in-person or field sales representative who can walk the hallways of the company to help the customer figure out how to make the purchase.
If you have an [A,A] product, you might not need as much human assistance initially because the product can spread at a department level and won’t require a complex decision-making process. Note if you have a type [A,C] product you will almost certainly require an expensive in-person sales representative to help execute the now even more complex technical decision. The customer will expect it.
Recently, we have seen these strategies play out in the market. Dropbox was able to reach targets I and II with a brilliant [A,A] product and primarily viral distribution, but they had less success with type VI targets with that same channel. This opened the door for Box.net, which built a direct sales channel (some of whom own Rolex watches) to very effectively reach target types IV through VI. In order to reach those targets, Box fulfilled many high-end requirements that moved their product from a strictly [A,A] product to a sometimes [A,B] product. Dropbox has now built an impressive direct sales force and is targeting more complex customers again; while most of their revenue is [A,A] they also ended up with sales and a sales engineering team for their larger [A,C] customers. Meanwhile, Workday’s product may have been able to be sold entirely over the phone, but to reach their primary target (VI), they had to build a high-end sales force. Zenefits went after type III customers and was able to reach them efficiently using telesales.
Once you’ve got the basic design down, you’ll want to consider more target parameters such as verticals — how does the Financial Services decision-making process differ from the Defense and Intelligence decision-making process? — as well as international — do we sell the same way in France as we do in Japan?
Finally, each of these channel profiles suggests a different profile for the type of sales force you build out for it. There is a difference between viral marketing (e.g., product design to enhance forwarding and so on); inside sales (e.g., telesales); and direct sales (people directly in the field or on sites meeting with customers). Certain products might be able to rely on the product’s inherent virality for marketing, but that is not a complete channel strategy as the company might be missing an opportunity to go after bigger customers with the same product.
If you want to build a successful company, your distribution strategy must be a function of your product and your target market. If you insist on designing your channel based on your personality, inability to handle the diversity required to mix sales people and engineers, or a lust for Drew Houston’s business model, then please give my condolences to your employees.