How Mercator.ai is innovating alongside the industry

Why did we run a beta program?

Looking back on six months ago, we had just closed an impressive Seed round, we were starting to grow our team, and our board asks: What if we stopped selling and focused on product market fit?

If we consider that solution market fit means that you're asking the right question, product market fit means that you've created the right product to answer that question. At the time, we had validated and re-validated that we were asking the right question "", but our product fell short of being the best answer. What that looked like was slow time to value, and increasing tech debt that was preventing us from doing anything about it.

If we were going to make this investment of time, we were going to make sure we built the right thing. 

So we started with WHO to build for. As a startup, our eyes are always larger than our stomachs. We knew every stakeholder in construction is asking this question, but to build for them all would mean building for none. So we narrowed based on who we had seen find the most value to date. And then we narrowed again to just those who had the mandates to innovate. Finally, we landed on an ideal customer profile: mid-sized General Contractors with a focus on operational efficiency in their business development teams. We also brought on some larger and some smaller GCs to evaluate the transferability of learnings.

The cost of the program was minimal, but ensured meaningful participation.

The goal of the program was to build a tool that was a seamless extension of their business process. We would prioritize their collective voices over our own, while spending significant time on learning their challenges and addressing the root cause, not the symptoms. The ideal outcome at the end of the 6-month program was to not have a product that we were ready to sell, but customers want to buy.

What did we do? 

The meetings were deliberate, structured, but flexible enough in topic that we could target the sessions to what we (both the participants and Mercator) wanted to learn to make the product better.

The program sessions included:

  • 1hr Persona Interview: We needed to know their role, their company, their challenges before we could start truly collaborative work.
  • 1hr Product Roadmap: It was important that the participants understood where we are taking this product, that it's simply one tool in a wider suite and how we plan to evolve it
  • 30min session 2x a month included usability studies, language studies, pricing studies, value interviews, new feature usability testing, and low-engagement user interviews.

What did we learn?

As we conducted the program, we iterated on our product priorities, and learned the mental model of the industry. We refined the product and made it easier for new users to learn the platform; extracting value faster.

At a high level, we learned where the value lies, and where it does not.

  • Our product and company pages are high value
  • Integrations and dashboards (bloated features) are not!

Three buckets of improvements bubbled up to the surface. These are some examples of immediate improvements we made within each.

1. Missing data
  • Geographical coverage: Official city borders are too constraining to growing general contractors. A complete geographic market covers annexable area around the city centre. So we went after government partnerships to widen our reach.
  • Early project stage indicators: Due to the nature of early stage projects, it’s difficult to find core project information such as project name and size (or it might not exist yet!). Mercator can now fill those gaps with predictive modeling.

2. Workflow
  • Tracking early opportunities in a sandbox: There aren’t tools specifically built to track opportunities before they move into a CRM or go out to bid. We found many different processes at work; from notebooks, to spreadsheets, to sheer brain power. So we added the ability to organizing projects in this phase that simulated their existing workflow.
  • Quality-of-life quick wins: We found an ongoing bucket of quick win improvements we could make that wouldn’t be central to the product, but would make the lives of our users that much easier. Some examples of these included exporting lead lists to CSV, downloading projects as PDF for easy sharing, and adding links to the most common next step.

3. Searching and filtering
  • Exclusions filters: We learned that the filtering is a learning process. Our customers want it to start quite wide so that they aren't missing anything. Once they're comfortable, refining and eliminating noise becomes important to ensure their daily emails contain ideal projects 90% of the time. So we gave them the flexibility exclude and made it possible for Mercator to start learning those exclusions.
  • Simulating a google maps experience: We learned very quickly that our customers have tablestake expectations for their map interactions. Giving visual cues of where they searched to and allowing them to search by any possible parameter was critical to creating a barrier free experience. So we revised the experience to more closely simulate a Google Maps experience.

Ultimately both micro feedback (like usability improvements) and macro insights (like product direction) allowed us to refine the product to their immediate needs and helped us shape the company's future direction. At the end of the program, we presented again our 12-month roadmap, but revised, taking into consideration all of our learnings. The result? Sheer excitement.

Working with a startup is a partnership to build something great

A lot of startups talk about being customer obsessed. Yet very few take the time to pause and deliberately build alongside their customers. This experience not only taught us to really listen and think critically about who we're building for, but it also shifted how our customers perceived us. We stopped being a vendor and became an innovation partner. We both had the chance to see what it really means to our customer's business to have real industry insights at their fingertips.

Why this worked: we set the right expectations up front. We weren't going to build everything and our beta customers knew that. This is what allowed them to show up as partners first, customers second. They didn't expect a finished product. They expected to work on a product together.

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