Achieving a Product-Market Fit
21 October, 2020
Director Product Management at Amazon Lab126
One of the problems we encountered early on was achieving a product-market fit. We simply couldn’t understand why customers were not buying our product and it took us three to four years to come up with the right solution. The underlying reason impeding our efforts was that we couldn’t pinpoint what was the problem we were trying to solve and what was the right solution that we could implement in a repeatable manner.
To achieve a product-market fit, you have to precisely define what a product-market fit for your product is. For us, it was selling to the same customer persona, the same solution without any customization in the software, sales process, or contract. Once we could prove that repeatability -- the same type of buyer and same service solution done in the same way -- we could argue that we had achieved a product-market fit.
However, what is repeatable differs from one product to another. Depending on what your unit of value is it can range from five to a million customers. If you are selling an API call, you will have to reach 10,000 API calls at least; if you are selling something that is priced by number of users you will need 100 or 1,000 users; or at least 5 customers if you are selling enterprise software. As an enterprise software company, we were trying to reach those first 5 to 10 customers.
To reach them we had to work backward answering two main questions: what was the problem that we were trying to solve and who were the customers who would buy our product. Our initial product was aiming to solve five different problems at the same time and we knew that we had to focus on the most important one. For many Industrial IoT (Internet of Things) companies, getting the context around their data -- understanding how data from different silos were interrelated -- was the most challenging problem. However, customers were unaware that this was the main problem as there was no direct top-line or bottom-line benefit.
However, as we began talking to customers about the need for contextualizing their data, we found that a key database was hard to keep its structure up-to-date. People were feeling that problem regularly, and they had begun to create a budget to get this problem solved. Once we saw project budgets popping up for this request, we developed a new product offering (a streamlined version of our core product) that focused on solving this core problem. This provided a clear “land and expand” strategy as we were going forward. And helped us win several deals as our software competed only against consulting services.
By focusing on one narrowed-down and precisely defined problem, we were able to immediately get 20 customers and began to easily convert them into much larger contracts as they saw the value of data contextualization across other databases. As these customers began to see success, other customers began to inquire how they could get the same service on the initial database.
- If you’re defining a product in a new category, once you identified a broader market problem, work with your customers to narrow it down to a laser-focused problem where people have the budget to buy immediately.
- When creating your buyer persona, look for a person who decides on and approves the purchase. The buyer persona isn’t necessarily the person who is daily troubled by the problem but instead is the person who will decide where to allocate the budget among multiple rivaling products or services.
- Once you come up with the right solution for that narrow, budgeted problem, align the pricing, product, and sales process to make it a competitive product. Then, you can develop follow-on sales and follow-on go-to-market, but first, you need to land and acquire the customer. The last step would be to secure retention by ensuring a repeatable use of your product and referring other people to use your product.
Scale your coaching effort for your engineering and product teams
Develop yourself to become a stronger engineering / product leader
Adi Purwanto Sujarwadi, VP of Product at Evermos, shares how he diligently managed a product in one of the biggest eCommerce companies by being an individual contributor.
Adi Purwanto Sujarwadi
VP of Product at Evermos
James Engelbert, Head of Product at BT, recalls when he had to battle imposter syndrome when managing a new team.
Head of Product at BT
Matt Anger, Senior Staff Engineer at DoorDash, shares how he took the risk and shipped features in a startup.
Senior Staff Engineer at DoorDash
Richard Maraschi, VP of Data Products & Insights at WarnerMedia, shares his insight on incorporating data science, AI, and product management to overcome slowing growth of the company.
VP Data Product Management at WarnerMedia
Prasad Gupte, Director of Product at Babbel, shares his insights into the challenges behind successfully growing a team.
Director of Product at Babbel
You're a great engineer.
Become a great engineering leader.
Plato (platohq.com) is the world's biggest mentorship platform for engineering managers & product managers. We've curated a community of mentors who are the tech industry's best engineering & product leaders from companies like Facebook, Lyft, Slack, Airbnb, Gusto, and more.