From Startup Pivot to Finding Product-Market Fit : One Year Later

A year ago, I shared a blog about our bold decision to pivot our HRTech SaaS Startup and how we shifted from a business with $700K in Annual Recurring Revenue (post churn, at peak we were at $900K ARR), a 25-member team, and $3.2 million in funding, to embracing the uncharted territories of a startup pivot. This meant starting from scratch: zero revenue, a smaller team, figuring out what to build next and bringing all the stakeholders on the same page.

A quick TL;DR on why we pivoted?

1. Churn — We struggled to demonstrate recurring ROI for customers. Without sticky value, churn began compounding.
2. Geo-limitation — We started in a small, familiar market. But customer discovery about expanding internationally revealed a mismatch between our product and broader needs.
3. Founder/Team/Market fit — Our personal design choices as founders differed from the product direction the market needed. This misalignment cascaded across talent recruitment and work streams, leading to siloed efforts and mediocre output.

Read more about why we failed to achieve a strong PMF here.

Before you continue reading, the intent of this blog is to provide an inside look at our product-market fit journey — the aftermath of pivoting, the ups and downs, key lessons learned. I’ll also cover our process over the past year and how we evaluated our stage of PMF and tracked progress.

My goal is to pull back the curtain on our experience to help others turn ideas into products users love and navigate startup journey post pivot.

Before diving into the tactical details of pursuing product-market fit, I want to share a personal note about the importance of being willing to pivot rather than slogging with weak to zero PMF.

Pivoting is a humbling experience. Going from repeatable revenue back to zero feels like a 3–5 year setback. People who once praised your leadership can turn and make harsh remarks. It’s emotionally taxing.

However, my cofounder and I believe having the courage to admit something isn’t working and change course is crucial and because of this decision we learned three valuable lessons this year which helped us become better founders too:

1. Focus beats busywork: We spent around 30% of our time this year in the US meeting with top founders. Their ruthless prioritization of 1–2 goals stood out. Rather than spreading ourselves thin on mediocre, chaotic tasks, it’s better to zero in on 1–2 goals and excel at them.
2. Solve the hard problems first: I recalled Sam Altman’s writings on hard startups — whose real meaning dawned on me years later. An easy startup is a headwind; a hard startup is a tailwind. With Inferless, in our early days we did rigorous customer discovery and found two major problems that we need to solve to get to the right solution. One was straightforward, one extremely tricky that no one had cracked. We chose the latter first, knowing success could be hugely valuable when we solve it.
3. Set realistic expectations with team, customers & investors: The startup world often glorifies founders who sell a rosy, hyped future vision. While inspiring, this attracts people wanting overnight fame and riches. Instead, we’re fully transparent on the hard engineering challenge we’re taking on. We explain the exact potential value when we succeed, but also the risk we may not solve it. We showcase our strategy for improving the odds through opinions on building the company, our approach, and tangible results so far.

What did we really achieve this year?

Reflecting on key milestones this past year, we took a systematic approach to achieve product-market fit and validate our business model:

Months 0–3:
Engineering — We initially dedicated time to thoroughly understand the existing solutions for the problem we were addressing, analyzing them from the user’s perspective. This involved identifying the most effective methods currently in use. Once we established these benchmarks, we shifted our focus to examine the problem from a fundamental physics perspective. This approach allowed us to determine the optimal architecture for solving the issue. After that, We asked ourselves: If we had all the resources, how would we tackle this problem? This helped us find the ideal engineering approach.

Growth — While my cofounder focused on engineering, I worked on validating our product-market fit and key business risks. I used a Product-Market Fit Loop framework to document our product-market fit hypothesis across six dimensions: target audience, problem to be solved, value proposition, competitive advantage, growth strategy, and business model. This created our product-market fit narrative. Next, we prioritized validating the riskiest parts of our narrative through a deliberate, sequenced process using two validation techniques. Broad techniques helped comprehensively identify risks across each dimension. We then applied targeted techniques to validate the riskiest, highest-impact parts of our narrative. This approach helped us build a path to increase our odds of achieving product-market fit by ensuring that we focus on the most critical risks early on.

Credits : Sachin Rekhi Blog

Months 3–6:
Engineering — After developing our initial engineering architecture, we pinpointed the two most critical technical risks to address. We dedicated three to six months to resolve these issues, which ultimately resulted in significant performance improvements in our field.
Growth — With our Product-Market Fit (PMF) Narrative established, we initiated growth experiments with meetups, newsletters, blogs, social media to identify our best channels for acquiring ideal customers. Top 2 content approaches led to maximum waitlist sign-ups.
Team — Defined the talent profiles needed to drive ongoing innovation.

Months 6–9:
Engineering — Launched a point solution (MVP) with essential features to collaborate with design partners.
Growth — Doubled down on top-performing content strategies, refined ideal customer profile [For those who don’t know, ICP stands for Ideal Customer Persona ( Persona — Buyer, Decision Maker, Influencer, Location, Type of Company, Stage, Budget etc — a blog for some other time)] , combined with targeted outbound ( learn more about the process here) to convert waitlist to customers.
Team — Added 1 engineer.

Months 9–12:
Engineering — Enhanced the point solution with feedback from early customers, started the focus on improving user experience.
Growth — Continued with the same growth levers and delegating one of them to a new engineering hire while having weekly interactions via Slack connects with users and monthly value-add check-ins to guide engineering priorities.
Team — Added 2 engineers.

Key achievements:

• V1 product delivering value and solving one job really well for high-quality customers
• Initial ARR with zero churn so far
• Product roadmap guided by paying customer feedback
• Clear goal plan for the coming year

Team that made it happen:

Our team currently consists of eight members, including the two founders, primarily composed of engineers. We plan to maintain this engineering-focused culture. A piece of advice: prioritize hiring engineers in the early stages of your startup. Engineers possess a knack for logically addressing issues and bring agility to quickly resolve user problems. (I’ll delve into this topic in a detailed blog post another day.)

How do we Measure PMF?

It’s too early to declare we have achieved high quality product-market fit (PMF), but we have strong leading indicators based on following parameters:

1. PMF is a process, not a static milestone. We leverage a popular framework on different types of PMF to help us benchmark where we are in the journey.

4 Types of PMF — Shreyas Doshi

2. Engagement is Truth & Retention is God. Depending on your PMF stage, tracking core platform engagement (for us, API calls) and retention (monthly usage and growth) separates low vs high quality PMF.

What can you learn from this process?

Phase 0 : Problem-Solution Fit

1. Months 0–3 : The first 3 months can make or break your startup. Avoid writing any code before rigorous customer discovery ( learn more about the process here) to validate top assumptions with target users. Measure what % have the problem, urgency to solve it, and whether they’ve tried on their own (to assess need for you). Once the problem is clear, test business model risks like technical feasibility, go-to-market, etc to find your competitive edge.

Phase 1: Feature-Problem Fit

1. Months 3–9: Launch a minimum viable product — a basic point solution users will pay for repeatedly. If new market, replace a manual process; if existing market, replace a competitor. Test content channels to find what best engages your ideal customer.
2. Months 9–12+: Onboard 5–10 early adopters. Obsessively track their onboarding time, weekly/monthly engagement, usage growth, retention. Ensure a path from free trial to paid. Resist scaling up customers until you see the full user lifecycle play out. If time allows, observe for 6–12 months before expanding.

Disclaimer: The timeline outlined above should be viewed as a general framework — the actual number of months can vary significantly depending on factors like technical complexity of the product, target customer segment etc

What’s next for us?

We want to continue building with the same approach with 1–2 top quality product goals, double tap on the successful content channels to attract the right ICP and onboard and listen to high-quality customers.

If you wish to connect with me, I am here — @Twitter.

Resources:

1. Sachin Rekhi’s Framework on Finding Product-Market Fit Loop here
2. Shreyas Doshi’s Framework on measuring PMF here
3. Sam Altman’s Blog on Hard Startups here
4. Founder-Led Sales by me here
5. Customer-Discovery Process by me here
6. Check our our company Inferless here

Note: This blog is an original post. I have used AI for certain sections to only fix grammatical errors & enhance the language.