Sachin Rekhi

For years now in the valley we've been shunning the traditional approach to launching a startup: writing a formal business plan, pitching investors, assembling a team, launching a product, and selling it like hell because we've learned the hard way that more than 75% of all startups fail and we needed a more iterative approach that allowed us to learn from our failures and refine along the way.

The customer development and lean startup methodologies evangelized by Steve Blank and Eric Ries brought us a better approach that favored experimentation over elaborate planning, customer feedback over intuition, and iterative design over traditional “big design up front” development. It championed the creation of minimal viable products (MVPs) as well as pivots when necessary to quickly adjust directions.

However I've seen too many startups use the lean startup methodology as an excuse to fly by the seat of their pants and shun almost any structure to their approach to iterating, validating, and finding product/market fit.

Personally I find the most efficient way to operate during the earliest phases of a startup lies in between a formal business plan and unstructured iteration. The process I've used involves documenting your initial product/market fit hypotheses, systematically validating each of the most uncertain hypotheses, and continually iterating on and updating those hypotheses as your team learns through customer validation, MVP launches, and future product iterations.

Here is what I typically capture when initially documenting a startup's product/market fit hypotheses:

1. Target Audience
It all starts with a clear hypothesis on who the target audience is for your product or service. It's important to be as specific as possible. For a marketing automation solution, for example, "marketing professionals" is too broad but instead "demand generation professionals" and "marketing operations" is far more specific. To better focus, it's helpful to determine this in terms of the "core" audience to whom your product is best suited, as opposed to the "total addressable market" for folks who might get value out of it.

In B2B products, it's important to divide the target audience in terms of end users of the product as well as business decision makers who have the budget and will ultimately make the call on whether to rollout the solution in their company, because you'll often find that these are two completely different audiences with different desires and needs. In addition to looking at the specific individual, it's often helpful to assess are there specific industries where your product is most valuable? Is there a certain company size for which your solution works best? Are there psychographic aspects of the target audience that will make them ideal users?

The challenge I find most people have with coming up with a crisp target audience definition is that they've been trained by venture capitals to find the biggest total addressable market they can justify to make their startup seem like it's attacking a massive opportunity. While that may be fine for your pitch deck, it doesn't help you refine your solution in the earliest stages of your business. To address this, I tell folks to think of their target audience not in terms of who they could eventually serve, but who specifically their current MVP is targeted towards today.

2. Problem You're Solving
Before getting into the specific solution your product or service provides, it's important to have a clear understanding of the specific problem or pain point that your solution solves for. There is no substitute in product development for developing an incredibly strong understanding of the problem space of your target audience. This means not only deeply understand your solution, but understanding all the previous solutions that have ever been tried to address the problem you're going after.

It's equally important to understand how much of a priority is addressing this problem to your target audience. This is what will help differentiate your solution from just a "vitamin" to being a "pain killer" if you are addressing problems so painful that any improvement to the problem space would be a welcome addition to your target audience. In contrast, nice-to-have solutions that solve not-so-pressing problems tend to struggle with customer inertia, where while your solution may in fact be better than their existing solution, the cost of switching makes it not a priority.

3. Value Propositions
Next you should define the specific value propositions that your solution provides. Value propositions shouldn't be the features that you are building, but instead the "promise of value" that you are giving your customer. This should be phrased in the customer's terms in how it will address the problem you're solving as well as improve their lives or business.

Products can have multiple value propositions, but too many can become a distraction. It's helpful to limit yourself in the early days to at max three value propositions that you are focused on. You can always add more later, but very difficult in the early stages to validate so many and to iterate to a great solution for each of those value propositions.

4. Strategic Differentiation
While the value proposition states the value your solution will provide to the end customer, your strategic differentiation is more company focused on describing what unique assets or capabilities your solution will have or take advantage of to make it a superior offering.

Strategic differentiation could be better data that you have access to, a simpler user experience, more sophisticated functionality, a cost advantage, or so many other elements of differentiate too numerous to list. But it's important to document why specifically you think you'll be able to create a solution that is ideally 10x better than the existing solutions on the market.

5. Competition
Speaking of other solutions on the market, it's helpful to document who the competition is and how they're doing in terms of addressing their customer needs. For nascent markets its important to take a very broad view of competition, including alternatives and substitutes to your solution. The status quo may in fact be no streamlined solution and instead a manual process which is equally important to understand and that status quo is the real competition you'll be fighting against in the market.

While obsessing over competition is never a winning strategy, not having clear differentiation from them will also make it impossible for you to win in the market.

6. Acquisition Strategy
Acquisition strategy documents the primary ways you expect to drive awareness, interest, desire, and adoption of your solution. Do you expect to provide your solution self-serve online? Or to sell it through an outbound sales team? Do expect your product to be viral and drive significant marketing through end user usage of the solution? Do you plan on taking advantage of traditional advertising or web advertising methods? Are you going to leverage channel partnerships to bring the product to market?

As you iterate, developing a more detailed understanding of your acquisition strategy involves understanding the cost of acquisition of customers for each of your primary acquisition channels and becomes a very important set of hypotheses to test.

7. Monetization Strategy
Equally important is understanding how you generate revenue from your product or service. Do you plan on implementing direct means through transactions or subscriptions? Or indirect means like advertising or selling derived data?

A more detailed understanding would also cover price points and an understanding of willingness to pay in the market, often based on understanding the value you are creating for the customer or based on comps to existing solutions in the market.

8. Key Performance Indicators (KPIs)
Finally, it's important for you to document the key performance indicators which you plan on leveraging to gauge how well you're business is doing. Defining these are early as possible is critical. First, it prevents you from "seeing what you want to see": you can always find a metric that looks good or a metric that looks bad. But if you have defined early on what success looks like, you're able to have an objective view into what really matters to your business and how you are performing.

When it comes to picking metrics, I like to have a suite of acquisition, engagement, monetization, and customer satisfaction metrics. It's important to customize these specifically for your business. For example, for productivity and other business solutions, oftentimes you're trying to improve the efficiency of the team, which may mean minimal actual engagement with your product or service, but significant value generated for the company. If that's the case, it's important to substitute engagement metrics for metrics that capture the value that you're creating. You may find over time that the metrics you're currently using don't do a good job of capturing customer value, so expect to iterate on your KPI hypotheses as much as any other.

Once you've defined the metrics, it's important to develop benchmarks for them. This is usually a highly iterative process because benchmarks are often difficult to get and also vary widely by stage of business. But without appropriate benchmarks, it's impossible to tell how you are doing in anything other than a directional sense.

I hope this helps identify the key product/market fit hypotheses that most startups need to determine in the earliest stages of their business. After documenting these comes the even more crucial task of validating them. I saved how best to validate them for my next post :)