Grabowski’s Who Is Going To Buy The Darn Thing? isn’t nearly as popular as Steve Blank’s various works, but both share a similar underlying sentiment: that a startup’s marketing functions are as important if not more important than product development.

Grabowski’s contribution is a simple quantitative metric, the Marketing/Engineering ratio, and the claim that successful startups spend more on marketing than engineering (an M/E ratio greater than 1).

Defining the M/E ratio

To start, it’s important to clarify what “marketing” is in this context. Although the term is often used to describe a broad range of activities including sales and advertising, Grabowski takes a much narrower view:

Marketing is defined as the up-front process that comes before the product is ready. (Promoting and selling come after the product is ready.)

Grabowski’s writing pre-dates the Lean Startup Movement, so his definition unfortunately implies a hard separation between pre-launch and post-launch activities. Viewed from a Lean perspective, he is essentially arguing that “learning” have its own line item on a budget and that startups should spend more time/effort/money on learning instead of building. Arguing for an M/E ratio greater than 1 is just another way of saying we should spend more time learning about what to build than actually building. That’s a fairly obvious statement when put plainly, but it’s still surprising how many entrepreneurs get mired down in product development before actually confirming that their target market exists.

Distinguishing marketing from sales makes the M/E ratio a particularly strong statement. Many startups implicitly group marketing, advertising, and sales into one “customer acquisition” category. While advertising and sales are important (I think many startups would benefit from increasing their advertising budgets), they are not a substitute for true marketing efforts, which should be focused on discovering customer needs. Just spending equal amounts on engineering and customer acquisition is not enough. Startups need to invest in learning before and while building a product and then again invest in sales once a product begins to find market fit. I agree with David Cummings’ claim that startups should budget for a 3:1 customer acquisition to engineering ratio, but would go one step further and argue that a significant part (more than half) of that customer acquisition spend should go to upfront marketing.

In fact, many sales teams don’t understand marketing. Although sales and marketing are often seen as complementary skill sets, Grabowski cites an example of a firm where: “Many engineering efforts had been urged by the sales force, which had hoped to exhibit technology that would make customers’ jaws drop.” He goes on to describe this as a common pitfall: “Mistaking selling for marketing”. Sales teams are well positioned to communicate with customers, but there is a fundamental difference between pitching your wares and listening to what the customer wants. The best salesmen already know to listen to their customers, but not everyone has the patience and charm of Dale Carnegie.

Minimizing risk

Technology-based startups present two types of technical risk. First, there is the risk that the startup cannot make the technology work. The second risk […] is that the startup does make the technology work, but that they are developing the wrong technology. Up-front marketing can guide engineering to the right technology.

The embarrassing truth for most developers is that software engineering is relatively easy: few software companies have failed because they couldn’t get their technology to work. Pharmaceutical companies have real technology risk: you could easily spend millions trying to develop a cure that never works. Aerospace companies have real technology risk: a single unchecked failure would not only destroy the company, it could literally kill.

For most software companies, the worst case scenario is that the product needs to be shelved for 6 months while the engineering team re-architects from scratch. Twitter and Tumbler both went those phases of significant instability when their user base outgrew the capacity of their early prototypes, but both were able to overhaul their software with minimal business impact. Spending 6 months building something that no one wants is much worse than spending 1 month building something desirable that doesn’t work.

Budgeting for marketing

The Marketing/Engineering ratio’s iron-clad simplicity is its main appeal. It’s easy to read Steve Blank, decide to “get out of the building”, and then completely shirk any meaningful change in activity. If a single founder worked 4 days a week writing software and spent the fifth talking to customers, he might feel like he’s following Steve Blank’s advice, but an M/E ratio of .25 is clearly substandard according to Grabowski.

That simplicity is wonderful for planning. I have woefully little experience crafting marketing plans for new products, but have been preparing engineering estimates for most of my career. Targeting an M/E ratio (or more), makes it easy to infer the marketing budget from engineering estimates:

Engineers know how to develop an engineering budget. Simply use the engineering budget to establish the size and timing of the up-front marketing budget.

Committing to this ratio and maintaining it for the life of a project is a natural check on feature sprawl and cost-overruns. If someone wants to add a pet feature that “only” requires one-engineering-week of effort, he’d best invest one-marketing-week upfront to verify the feature is actually desirable. If the initial engineering estimates were low and it’s now clear that the project will require 3 times as much development time, then the company should increase its marketing efforts 3-fold.

Conversely, cheap engineering efforts can be pursued with minimal marketing. If the concept for a new feature can accurately be expressed as a 1-day MVP, then the team only needs to spend 1 day interviewing customers before proceeding.

By establishing a firm M/E ratio, startups can align the interests of their marketing and engineering teams. Instead of throwing new feature requests over the wall, marketers are incentivised to justify their requests with firm data, since additional engineering commitments will also place additional demands on the marketing team.