Software Product/Market Fit

Finding the right Product/Market fit is probably the most important differentiator between success and failure of a new software company or product. Yet even though this software product/market fit should be obvious, it is often glossed over in the excitement of a new enterprise. Why is this? In some cases, people don’t really want to know that they don’t really have it nailed!

That may sound ridiculous. But think about it for a second. You’ve come up with this idea that YOU think is great! And have become very excited about the possibility of creating an all-new product. And maybe even a new company. The beginning of this journey is VERY exciting. Whether you want to admit it or not, the thought of major $$$$ signs may be flowing through your mind. This can cloud anyone’s objectivity.

Many founders lack marketing skills

In addition, many founders may not be product marketers by profession. Often, they are more excited about working on the technical aspects of the new software product. Digging into a market segment to verify there is great product/market fit may not be nearly as appealing. These two scenarios, along with many others, can unfortunately serve as “blinders” to the misalignment between the product and the target market.

I’ve seen many companies plan SaaS, mobile, and traditional on-premises software products in great detail up front, with very little market input. Technically-driven organizations are often prone to this approach. This can work fine if these companies are essentially “the customer” themselves. We call this ” next bench marketing”. But in virtually every other case, this approach dramatically increases the chance of failure.

The truth is, it’s very hard to plan a product properly from a “clean sheet of paper”. You’re going to get a lot wrong. Even if you wisely solicit early customer input. Customers usually aren’t great at telling you what they need. That’s true until they actually see it! So even a good effort at pre-product market research can often yield misleading results. But this isn’t an excuse not to do it at all! Pre-product research will generally get you closer to the right answer. If you’re skilled at it, you can at least uncover customer problems you weren’t aware of. Even if you aren’t able to fully ascertain the perfect solution at this early stage.

Focus on discovering and solving real problems

So the most realistic path to success, imo, is to spend your early time uncovering PROBLEMS. Those that have been left unaddressed by other vendors in the market segment. Then try to solve one of these problems with a minimum viable product (MVP). The goal is to get “in the door” of your market segment as quickly as possible. Then listen to those early-adopter prospects and customers. They will inform you on the perfect software product/market fit, which you can use to polish product releases v2, v3, and v4.

The qualifier to this is that today it’s very possible to use AI to do some very helpful, if basic, early market research. And I think you SHOULD do this! Before you even talk directly to a prospect, and certainly before you start coding an MVP. But I don’t consider this to be a replacement for those intimate, direct talks with prospects. Discussions aimed at discovering unaddressed customer pain points.

This is a particularly viable strategy with modern software businesses, especially SaaS. While there is still a significant amount of “art” to software development, compared to the “bad old days,” the speed and cost of software development have been reduced significantly. This was true even before the dramatic reduction by using AI coding tools. Using a SaaS model, you can make centralized, instantaneous changes to the product for all customers, which works well with the approach of creating an MVP and then iterating toward the market segment’s ideal product (although beware the “SaaS Development Gone Wild” scenario).

A real-life example of software product/market fit

An example of this “MVP first” approach comes from my own career, when I joined a $50M defense services company to start up and lead a new IT software product division. This was a diversification of the company’s free cash flow. One that was hoped to be a business yielding a higher valuation from investors and potential acquirers. It was also to be both the first commercial (non-defense) and product activity within the company. This added to the perceived risk and uncertainty of the project.

Because this was a new effort and quite different than the company’s core business, there was quite a bit of nervousness. That was due to devoting a large percentage of its free cash flow toward a new business not well understood by the company principals. As a result, we didn’t quite have the resources available to create a “great” v1 of our software.

Accidental MVP

Essentially, we ended up creating an MVP “by accident”, before that term even became popular. It didn’t sell nearly as well as we’d hoped. But it validated that we were solving a real problem and had a large market opportunity. If only we could produce the right product definition and execution. Using the knowledge gained while marketing v1, sales quadrupled with our improved v2 release. And quadrupled again with our highly acclaimed v3 release. At that point, we became profitable and were “off to the races”. What had seemed VERY hard in the beginning with v1 began to feel very easy with v3. It was because we had found the right product/market fit!

I could rewrite history and extol our startup brilliance. But we didn’t follow a set process to create just an MVP initially on purpose. It happened because we were resource-constrained. And under a lot of pressure to get to market as soon as possible, due to political pressures within the parent company. But in hindsight, it fit with the process of “find a problem and create an MVP as soon as possible” very well.

Of course, if you can get it right the first time, all the better. But it’s hard without a “real” product out in the market to obtain perfect market feedback. So my message is find a market segment with a significant unsolved problem and go to work. Doing early market research, both primary and secondary, and getting your MVP to market as soon as possible.

Another real-life example of the wrong approach

The other important message in this area is how critical it is to avoid believing you’ve achieved a winning software product/market fit – before you actually have. Many startups believe they have found a product/market fit too soon and start scaling based on this. An example of this problem was a company that a VC I know introduced me to a while back. They were also in the IT software business, and the CEO asked to have lunch with me to discuss his business model. A very smart guy, but from a technical background. I believe that they had around 7 customers at that time. All of which were of the “brand name” variety. But regardless of the customer stature, they hadn’t even reached double-digit customers yet.

All of the sales had been made with heavy involvement by the CEO and senior product developers. Yet at our lunch, the CEO stated that they had just hired an expensive “rockstar” VP marketing to generate demand, and that they were in the process of scaling their sales force. This was not advisable. They clearly hadn’t established a repeatable sales & marketing process and almost certainly didn’t yet have a winning software product/market fit. I wasn’t in close contact with them, so I don’t know the details. But the VC later told me that the company had adopted an open-source business model. and apparently not for the right reasons, but as the “business model of last resort”. It was eventually sold, and the VC didn’t get their full investment back. Not a great result for the founders or the investors.  This is a cautionary tale of the hazards of scaling before software product/market fit is achieved.

The “perfect” product/market fit isn’t universally the same for all

Marc Andreeson, in his legendary post on this topic, opined that the most important thing for a VC is MARKET, not product or people. I admire him for taking a stand and trying to provide a simple answer. For his purposes – trying to build huge, unbelievably successful “hit” companies, even if there are a lot of failures in the VC portfolio, this makes a lot of sense.

But a great market also usually attracts BRUTAL competition. So, unless you know you’re going to get funded with $100M to attempt to reach Unicorn status, trying to find the absolute biggest/best market may not be the best advice to follow. His post also makes a big deal of stating that you know you’ve reached software product/market fit when you’re seeing OVERWHELMING demand for the product, and that’s when you can REALLY start to scale. I understand his viewpoint. But I see “overwhelming demand” as a trailing indicator of Product/Market fit in the software business.

It’s different if you have VC funding

Again, Andreeson’s may be a great approach if you have essentially unlimited resources. But I believe that if you wait to scale until you almost can’t fulfill demand to decide that you have a great product/market fit, that may be too late for most SaaS or mobile software companies. If you wait too long and you’re more of a “long-shot” contender in your segment, you may miss your window of opportunity. So it’s important to find leading indicators of traction, not trailing.

So what demonstrates great product/market fit isn’t universal, but more nuanced, depending upon your particular situation. The one thing I will say is that today, don’t try to launch a software product without SERIOUS AI integration and features. You won’t be able to raise money without real AI product benefits. And you will fail in the market, almost certainly. And I’m not talking about some weak attempt at using AI just so you can put it in your marketing. This is true even if you’re aiming at some relatively small, sleepy vertical market. That time has passed. You need REAL AI product benefits.

Leading indicators of software product/market fit

1. If your model is sales-intensive, your regular sales folks can sell the product as currently constituted
2. Your sales cycles are starting to shorten
3. Word of mouth marketing is really starting to pick up via your customers and prospects
4. Vertical publications in your market segment are providing positive articles on your product
5. You are getting many more inquiries from channel partners and prospects outside of the current geographic/vertical marketing focus.
6. A broad segment of your marketing program is starting to show increased results, without any changes to the campaigns themselves.
7. Your marketing programs are now converting at a rate that will grow the business fast without more than “light” sales intervention, if your model is marketing-driven
8. In general, things seem to be “getting easier”

Things getting easier is the key indicator

Bullet point #8 is the clincher for me when it comes to validating whether you’ve reached software product/market fit that will enable success. In my experience, once you’ve found a good product/market fit, doing business every day seems to transition from one analogy of “pulling teeth” to one of making sales “like a knife through butter”. Obviously, this isn’t an objective/quantifiable measure of traction. But I really believe that you will know it when you see it. You will actually FEEL it.

I recommend using the list above as a rough guide when considering the very important question of when to begin to scale. Once you can recognize at least a majority of these milestones on this list, then, and only then, should you put the pedal to the metal on scaling your sales force and marketing efforts.

That’s a summary of my thoughts on the importance of software product/market fit for a SaaS or mobile software product or startup. Objectively find a big unaddressed problem. Create an MVP to enable real market research. Don’t delude yourself into thinking you’ve got software product/market fit prematurely. And don’t scale until you actually do. Use the list of bullet points in the list above to gauge whether or not you’re there yet.  What have I left out, or what don’t you agree with? Post your own comments on this important topic below.