This is Part 12/18 in the series “How to Build an Innovative New Product or Company” on the topic of spending time with your users to determine product iteration and early direction
“Product-Market Fit”: the moment when a startup finds that their marketing message, sales process, and product are all aligned perfectly against an unmet market need and customers run to their door, money in hand.
I was at a conference a few months ago and an audience member asked the speaker, “how do you know if you have Product-Market Fit?” His response was, “when your product is flying off the shelf faster than you can fill the orders.” I doubt the answer was helpful, but I think the problem may have been in the question that was asked.
The better question is: “How do I know if I’m on a path to get to Product-Market Fit? And how do I get on such a path if I’m not?”
You know you have “Product-Buyer Fit” when;
- your sales demo/value proposition gets you interest, meetings, and builds your sales pipeline
- buyers rate the pain you are addressing and your solution as 8 or 9+ on a scale of 1–10
- buyers become more engaged and more excited as you step into your demo during a sales meeting
Product-Buyer Fit may be all you need to close your first few deals.
You know you have “Product-User Fit” when;
- your users are using your product as often as you intend, getting the value from it you like, having the experience you expected, and having the impact they want
- your users tell their friends and colleagues about it and offer to help get others on board
As you’re iterating on your product, keep your source(s) of advantage as your north star.
If you have a choice, for example, in designing your product or marketing website in a way that highlights your sources of advantage versus another way that hides it, choose the former. (Sources of advantage are the main component of Step #3 of the “4 Steps to Develop a Strategy”).
For products I’ve developed, analytics has always been a major source of differentiation and so keeping analytics insights front and center in the product and sales demo has been a goal.
While you’re getting product-buyer/user fit, optimize for learning and speed of learning.
The currency of a startup is how much it has learned that others don’t know.
Add features based, not on what users say, but on what will make a difference. Work with mockups and “false-front” product features. The goal is shortening cycle time: getting as fast as possible from user feedback to a “false front” feature that gets deployed, usage levels measured, and user feedback collected. How fast can you overhaul the UI of your product? If by six months in, following a major engineering investment, the UI is built out and locked into where you can only consider incremental changes, you’ve not set yourself up to succeed.
The main thing you want to learn is what is the core feature and idea to build out — and product-buyer/user fit becomes a clear north star that allows you to determine what not to build and why. As Hewlett-Packard co-founder David Packard said, “More businesses die from indigestion than starvation”.
Spending time with users is a core tenet of the Lean Startup model, but how much time do engineers, product designers, and entrepreneurs spend talking to each other versus spending time with their users?
In my current company, we built an application for nurse managers in hospitals to help save them time and recognize nurses on their teams who go above and beyond.
When we first launched it, I was lucky to live near one of our pilot hospitals. For three days a week for many months, I’d meet with our users. I scheduled thirty minutes a week with each of them and they’d use the product while I took notes as they shared what they’d change, add, or correct.
The amount of actionable feedback was critical. We had enough of a working product for them to use and be able to provide feedback but it was clear we had only gotten things 60–70% right.
One example comes to mind. Weeks in after meeting with the managers many times and going through the product, one manager said to us, “this nurse you’ve highlighted for me who has been working a lot recently… she’s part-time and on Social Security. Now Social Security has a salary cap, so this nurse cannot keep working as many hours or she’ll lose her benefits. Now I see this information, I’m worried she’ll have to stop working for us later in the year.” What we do with that insight is a product decision, but it’s a great example of the level of depth that spending real-time with your users can uncover. None of us, in designing a product, even with hours of interviews informing the design, could ever come up with such an intricate use case — and getting feedback like this and making use of it enhances our value for every other user in the future.
Incidentally, there was an equal amount of valuable feedback and corrections proposed by our own internal QA team member. Even with a small team, a full-time QA person is exceptionally valuable.
Before you reach Product-Market Fit, everything you do needs to be in the service of learning as much as possible about your users and what they’re trying to accomplish.
Set your goals and measure progress in terms of the amount you learn (not the amount of revenue you create) in the early days.
One aspect of learning is to understand all the stakeholders around your user and buyer. Who influences them? Are there detractors — for example, who have an influence on your user, who you could also win over, thus creating a stronger ecosystem for reinforcing your product usage?
Focus on jobs the users are trying to accomplish
As popularized by Clayton Christensen, there are four types of jobs that users want to complete:
- Functional (e.g., driving to work),
- Social (e.g., looking like an expert or connecting with friends),
- Emotional (e.g., feeling safe, secure, and happy; express their personality by showing off a product brand),
- Supporting (e.g., making many small decisions as consumers, such as finding the best TV show to watch or leaving product feedback).
Not all jobs have the same actual or perceived importance. Jobs, even small ones, that occur regularly create more friction in users’ lives and are thus higher priorities for them to receive support for. The most powerful solutions solve one or two functional jobs but include social and emotional jobs. Examples include buying a bike that becomes a statement of identity or renting a movie while being part of a real-time online conversation with others who are also watching.
Users complete many jobs on autopilot. Even if your solution helps them do those jobs is better, the behavior change needed to use your product may be greater than the size of the pain. To overcome the autopilot, it helps to fit your solution into the users’ lives as seamlessly as possible. You can also advertise the dangers of continuing to do things the “old fashioned” way. Eliminate switching costs by offering to onboard users — for example, by importing the data they use from their old system into your new one to get them started. Reduce the number of features and focus on the core components that allow them to complete a job. Make sure you are helping users to complete the job they are doing much better.
Emotional jobs are particularly powerful and under-appreciated. Snapchat, for example, has built their product on allowing their users to share moments of their lives with their friends without worrying about whether others will click a “Like” button.
Stephen Wunker et al. give several examples in their book, Jobs to Be Done, based on the work of Clayton Christensen. You can’t tell what job any buyer or user is trying to accomplish by looking at what products they buy. Talk to them and ask: if you hadn’t solved this job that way, what else would you have done? For example, parents may buy move tickets for their kids on a weekend afternoon because their goal is to keep their kids entertained. The kids (as users) may want an authentic move experience; the parents (as buyers) are choosing a movie as an alternative to a playground or swimming pool.
In another example, people sometimes buy Oreos at the checkout line to stave off boredom; therefore, accessibility to mobile phones in supermarket lines has had a greater impact on last-minute snack purchases than any competitive food product.
In his article “True Colors”, Malcolm Gladwell shares the story of how Alka-Seltzer launched their product to cure a stomach upset, but users also took it to cure headaches. Understanding that could not come from watching sales numbers; they had to talk to users. And it was an important insight because it caused them to change their messaging. Stomachaches are typically the result of eating too much or too much of the wrong thing: it was a user error that the user wanted the product to help them undo. Headaches are very different: they are events imposed on you. Some might argue this is a marketing insight and not a strategic one. After all, in this case, the main adjustment was the introduction of a new marketing approach claiming Alka-Seltzer cures “the blahs”, a tidy way of including both needs. But how can you have a robust product strategy if you don’t know what your buyer or user values your product to solve for them?
When looking for ways to better solve a user’s job, Wunker et al. also give a few common approaches. On the jobs that users most care about, can your product allow them to significantly…
- Save time by doing the job 2x-5x faster?
- Reduce the complexity of a job by 2x-5x?
- Do more 2–5 different types of jobs in a single place — as Microsoft Office does?
- Improve the quality of the job being done by 2x-5x — as Windex does for users cleaning windows?
- Make completing the job 2x-5x easier or more comfortable — as Slack does for reducing email communication within a company?
- Add the completion of an emotional or social job with a functional job?
- Make the job completion meet the needs of more stakeholders — as McDonald’s does, branding Happy Meals for kids and coffee and salads for adults?
Is there a way to measure “product/market fit” as early as possible?
A recent article by Superhuman founder and CEO discussed how he stumbled upon a metric used by Dropbox founder Sean Ellie. The idea is a variant of “Net Promoter Score”: simply to ask users “how would you feel if you could no longer use the product?” and then measure the percent who respond “Very disappointed.” The other two answer choices: “Not disappointed” and “Somewhat disappointed”.
If the percent is >=40%, the evidence shows you are on track to fit; if not, you’re not there yet. According to the article, the popular application Slack reached 51% in 2015, when it was just at the beginning of its upward trajectory.
The article also claims that as few as forty responses are enough to get a directionally correct indication of this metric. Something that can be measured early and often in a startup’s growth.
An additional question to categorize the user — their role or personal as is relative to the product — helped Superhuman differentiate their detractors from their strongest supporters. Armed with that information, it can trigger the internal discussion of whether it would be better to target the product to the strongest supporters or to update the product to also win over the detractors.