Sachin Rekhi

The hunt for finding product/market fit in an early-stage startup is an elusive one, often fraught with chaos, and certainly never easy. I've led the hunt for product/market fit in 3 startups that I co-founded and also had the opportunity to do so for 3 new products launched at established tech giants LinkedIn and Microsoft. Most recently, in advising 5 early-stage startups, I have been helping other founders through their respective hunts.

I put together this presentation to share a framework I've leveraged in my own startups as well as now in those that I'm advising to bring some much-needed discipline to the hunt for product/market fit. While there is certainly no silver-bullet, I do find that leveraging an iterative cycle of defining, validating, and iterating on each of your most critical product/market fit hypotheses is a sure-fire way to bring some predictability to the process and provide guidance on whether your team is getting closer or farther from the ultimate goal. I hope some of the best practices I detail in the deck can be helpful for your team as well.

One of the characteristics Reid Hoffman often mentions he values in great entrepreneurs is that they are infinite learners. Those who possess this quality are constantly expanding their expertise to new domains, regularly overcoming their own shortcomings, and their capacity for taking on new challenges seems limitless. Mark Zuckerberg is frequently cited as an infinite learner who has grown immensely in his ability to lead Facebook’s now 10,000 person organization and shape a product experience that touches over a billion people daily. In the world of technology where absolutely all the rules are constantly being re-invented, being an infinite learner has become a critical skill to the survival and longevity of great leaders and their organizations.

Today's best products not only solve a clear pain point, but do so while understanding, eliciting, and amplifying the emotions of the consumer. The gold standard of this is Apple, whose products are not only useful, but delight us, surprise us, amaze us, and elicit incredible emotional responses. Yet designing such products is no easy task, requiring product designers to bring deep emotional intelligence into their product and product design process. I wanted to share some examples of products that do this well as well as techniques to bring such emotional intelligence into your own product design.

One of the most critical aspects of finding product/market fit in the earliest stages of a startup is identifying and targeting your ideal customer. I find though that many startups don't give this task as much attention as it deserves. Sure, coming up with an initial hypothesis of a high level ideal customer description is easy. But the challenge often is that these descriptions are not nearly as specific and narrow as they need to be to be actionable for the business. Equally concerning is that the rigor leveraged to ensure that the initial target audience hypothesis is truly ideal and validated is often lacking.

On the other hand, in the search for product/market fit, I've seen successful teams find it not only by pivoting and adjusting the value proposition they deliver on, but also simply by pivoting their target audience to a more ideal customer who better resonates with the value position they've already delivered against, further justifying the importance of getting your target customer segment just right.

Given this, I wanted to share a set of strategies that can be leveraged to help guide the process of finding your ideal customer segment.

In my previous post I detailed how I typically go about documenting the initial set of product/market fit hypotheses for an early stage startup and each of the key elements that are important to capture as part of it. Once you've done that, then the far more interesting work begins: validating whether there is in fact truth to each of your most uncertain hypotheses and iterating upon them to eventually find product/market fit.

When it comes to customer validation, the most important piece of advice I can give you is exactly what Steve Blank has been prescribing all along: to get out of the building and talk to potential customers and eventually actual customers leveraging your MVP or later product iterations. This advice sounds so simple and so obvious, yet I see way too many product and design teams spending significant iteration time within their four walls holed up in conference rooms debating the merits of various strategies, features, and design decisions with limited direct customer input. Or maybe they did talk to customers, but months ago on the last iteration, and haven't incorporated it into a systematic process for getting regular feedback from customers. Quantity and quality of customer feedback are both important, but if you have to pick one to optimize for, frequency of exposure to actual customer feedback is incredibly important. Jared Spool's research showed a few years ago that increasing exposure hours to customers had the strongest link to building great customer experiences. So heed Steve Blank and Jared Spool's advice and get out of the building and talk to your actual customers early and often.