## Building a Product Vision: From a Specific User’s Problem to a Solution

# Introduction

For starters, a bit of statistics that might calm some individuals and slightly worry others. On average, when you have an idea and first feel that you’ve found Product-Market Fit (PMF), approximately two years will pass. About one year will require continuously refining the solution to transform it into a product that users genuinely need.

Some companies (like Slack, Figma, Airtable) took more than four years, but these are more the exception than the rule. The journey for most can be seen in the chart below 👇

# Starting with the Problem

Another crucial point: no company has ever felt absolutely certain that they are in their niche. Finding PMF is not a trip with a clear destination; it’s more of a journey where you constantly change your route based on internal and external circumstances.

I clearly feel this now as we shape and iterate the Co-Founder Ai product. For me, finding PMF is intrinsically linked to creating a solution. I have a formula that I keep in mind when building a product because a product is not just a set of features but a solution. A solution is not random; it’s a solution to a specific problem. Problems aren’t just anyone’s but belong to a specific user/persona. The persona isn’t in a vacuum but in a specific context and market segment.

In the end, the product is: A solution to a problem for a specific persona within a specific context and market segment.

# Gathering “Segment — Persona — Context”

My basic principle here is that you need to be immersed in the market. This way, you receive feedback from the world more effectively and quickly understand whether something works or doesn’t.

Continuing with the Co-Founder Ai example, assume we have a problem between marketing and sales—a gap in metric growth, demo generation costs, and registrations. Marketing brings in leads, but the first-line sales team loses them.

Through conversations with people, we add context to this problem: demos are handled by individuals who are both expensive and prone to failure. Moreover, hiring them costs money (sometimes twice the monthly salary)… In general, there’s a lot of context.

Alright, in which verticals do CJM (Customer Journey Mapping) points exist that we can help with? Describing the context, we see that such a funnel works in EdTech, Wellness, SaaS, and more.

# Deciding Where to Focus

Next, you need to decide which of these segments to focus on. Again, it’s about deep immersion in the context. Confirming a vertical is straightforward: you need to find companies that are genuinely willing to pay for your solution 😉

# Creating the Solution

The solution is formed through engaging with the Ideal Customer Profile (ICP) and early clients. With their context, it comes together into a cohesive picture and inevitably evolves. And more than once (read with a heavy heart).

The first step in finding PMF is to make one customer love your product, ensuring that they start using it, love it, and continue to use it. This, in my opinion, is the most crucial aspect of product development.

Some founders said they set up Slack notifications and contacted clients whenever issues arose. In another company, a dedicated team was created to customize reporting exactly as the client needed.

At Dashly, we work in a pilot format. Our team implements “the work we hire our product for” for the client. This means we are in constant contact with clients, deeply immersed in their context and pain points. We test product scenarios ourselves, gather results ourselves. The main goal is to achieve the result for which we and the client came together. This helped us create several critical pivots in our solution.

For example, I used to think that the main solution to the problem in the inbound funnel was working on conversion—conversion to a lead, to a meeting, and so on.

Now, I think it’s not quite like that. Conversion is still important, but there’s so much additional nuance…

Conversion is a highly volatile aspect that depends on many factors: advertising channels, current market situation, seasonality. Therefore, creating a solution that promises conversion growth with such volatility is not a great idea.

But there’s another approach: creating solutions that become must-haves for organizing the process, which will replace the current, less effective solution for the client.

For instance, Calendly. The calendar is an essential tool for organizing meetings. It affects conversion, but Calendly itself is needed not for conversion but to allow a person to book a meeting in a convenient format, at a convenient time, with clear options. Conversion here is a consequence. It’s about improving user experience (UX).

Therefore, we stopped viewing Conversion as the key objective. It’s too dependent on external factors: a client started increasing traffic, and conversion dropped because advertising channels worsened.

Instead, we discovered another problem—managers. They are always problematic. Because a system built on human reliability is inherently unreliable.

And only such deep immersion in the problem’s context provides an understanding of what the product should do.

“Firing” first-line managers who handle meeting scheduling and stabilizing conversion in dialogues and meetings is also about conversion, but it sounds entirely different.

In our current solution, the hypothesis is to replace first-line managers who handle meeting scheduling.

We are building a Conversation AI platform that qualifies leads, ensures they are Marketing Qualified Leads (MQL), transitions them to a “solid” channel for dialogue, schedules meetings at the right time, and ensures they attend. You could say it’s AI Sales on steroids.

The idea is that it creates a process but fundamentally in a new way.

# The CEO’s Role in Shaping the Vision

Firstly, it’s about making decisions. Which hypothesis are we testing? What is the team’s focus? What are we building the product about?

We’ve shifted our focus from conversion to creating AI Sales assistants. This is a significant decision from a product strategy standpoint, and one must have the ability to make such decisions.

If the hypothesis doesn’t work, whose responsibility is that?

Decisions that impact the entire team cannot be made by someone who isn’t responsible for the team’s overall results.

Secondly, it’s about interacting with clients. To make informed, strong decisions, you need a lot of context. The deeper you immerse yourself, the stronger your hypotheses become.

Thus, 50% is intuition, and the other 50% is experience.

Interacting with clients is the biggest channel to train your intuition. You talk to a client, think, “Oh, it seems there’s a growth point here,” and your task is to connect the solution’s vision with what you’ve observed with the client.

Hypotheses need to be discussed with the team. If I don’t do this, I’m taking the entire responsibility for the decision on myself without any filter or feedback from the world.

Hence, the ability to talk to someone (an expert, the team, a client) is crucial to validate your decisions. If they’re wrong, it affects the entire team’s results.

Do we have this?

We have early adopters who are willing to take this risk with us and continue paying because we create value for them. But have we found PMF? No 🙂 It’s a journey.

# Conclusion

Building a product vision is an intricate process that involves deeply understanding a specific user’s problem within a particular context and market segment. By immersing yourself in the market, interacting with clients, and being willing to pivot based on feedback, you can create solutions that truly meet users’ needs.

At Co-Founder Ai, we are committed to this journey, continually refining our Conversation AI platform to ensure it delivers real value and helps startups achieve their goals with the support of venture capital firms, angel investors, and other investment opportunities near me.