How we found early product / market fit for DoWhatWorks

How we found early product / market fit for DoWhatWorks

This post is written by our Co-Founder and CEO Andres Glusman.

We've been getting a lot of questions lately about how we launched DoWhatWorks and found early product/market fit. So, I thought we could share that story with you and 4 lessons from that journey.

By way of background, my cofounder, Will Howard, and I spent a decade working together at Meetup. I led Product and Growth (among many other roles). Will led large engineering teams. We worked together to launch new features, drive growth, and occasionally launch new products.

Along the way, we ran tons of experiments. We loved the process, but were frustrated by how long it took to get results and how often experiments do not win. 

We left Meetup after the company had had a successful exit and set out to create something new. We started collaborating on ideas. As we kicked around ideas we frequently created rough prototypes to feel out specific opportunities. 

One prototype was for a technology we invented (and later patented) to detect experiments from companies we thought were cool. We focused our new engine on companies like Netflix, Warby Parker, and GEICO because we assumed they might run cool tests. 

When we found tests we were over the moon. But we are nerdy and passionate about experimentation. 

So we showed screenshots of the tests to marketers and product managers to get their reaction. In addition to listening to how it would help them, we looked for emotional cues.

Did they get excited? Did they lean in? Did they talk faster?

Our product manager friends immediately understood the power and expressed interest. But they were friends, so we took it with a grain of salt.

We showed the prototype to folks at a conference. One VP of Product there started selling it to others. That was a good sign. We asked the people who said they were interested if they would be willing to pay for it. When they said “yes,” we challenged them to prove it. So, we sent them a Stripe payment link and promised a PDF report if they subscribed. We had not built the user experience yet; we just had the engine and a payment page. But we felt confident we could deliver a PDF in time.

Early version of signup page
When they actually went through and put their credit card down, we knew we were on to something.

We promised early adopters a monthly PDF, but we raced to build a v1 dashboard of the product before our promised delivery date. 

Early version of website dashboard

We then iterated like crazy with users to create a unique experience tailored to our customers' workflows. Since customers were paying for the service, they were invested and shared solid feedback. We also felt confident that their feedback could help us prioritize the right things.

We then sought out more customers that looked like our happy customers.

We studied what types of customers were successfully using the product (what industries they were in, how big the company was, what role, etc). We then looked for reliable ways to reach people like them with an offer they found compelling.

I wish I could say that we nailed all those elements on our first try. We did not. We went through the painful process of sharing the product and pitch across tons of sectors and types of customers. With time, we refined the pitch and saw what types of people loved it, and what types of people were uninterested. The process was exhausting.

Which brings us to today. We have an amazing roster of clients, a patent on the technology, a polished solution, and we are starting to scale. 

We are applying the same approach and questions to figure out how to scale DoWhatWorks.

4 key lessons learned in the process

As a founder, I can tell you that launching a new product can paradoxically be thrilling and painful at the same time. You spend countless hours in ideation, prototyping, and developing your product. But, how will you know if it'll resonate with your target audience?

You need to get signals early, often and quickly. 

1. Get outside signal fast

We were familiar with the pain because we had lived with it. But we quickly validated others had that pain in ways they were willing to pay to solve.

As we began talking to people interested in our product, we focused on their pain and how they used our solution.

Some questions you might ask in early discovery:

  • Are they trying to solve this now? 
  • Are they spending time on it? 
  • Are they spending money on it?  
  • What is the impact of solving it? 
  • What is the impact of doing nothing?
  • Will this positively change their workflow? 

In addition to listening to what potential customers are saying, you need to look at what they do, especially for the emotional cues. From our experience, we would suggest you to look for signals like:

  • Are they leaning forward when you talk about your product or service? 
  • Are they sharing how it would fit in their workflow?
  • Are they excited about it? 
  • Are they asking questions? 
  • Are they engaging in some level of commitment of time?
  • Are they engaging in some level of commitment of money?

By tracking these signals, you can gain confidence that your product has the potential to be successful.

2. Charge early in your journey

So many people give the product away for free and get feedback from the wrong types of customers. Feedback from free users is not always the same as that from paying users. After all, they may never feel the pain enough to pay to have it go away. I had personally led a transition from a free product to a for-fee product at Meetup and did not want to relive that experience. 

By charging users from Day 0, we could trust the feedback. We could learn from churn since churned customers are communicating honest feedback with their wallets.

It feels great when people compliment your product, but you know they mean it when they put down their credit cards and literally put their money where their mouths are. They will have skin in the game and you will know their feedback caries more weight.

3. Group similar users into clusters

Figure out what people who love the product have in common. And just as importantly, figure out what people who hate it have in common.

As we sold the product to potential users patterns emerged from people who loved the product and people who had no interest. It hurt a little whenever I spoke with someone who wasn't interested. I knew it was not realistic to build something that would be loved by everyone. It is hard to remember that people who honestly dislike the product are doing you a favor. Once I could name the patterns of what nonusers looked like, I could save time (and a lot of mental energy) not serving those segments. 

I've found that as we have scaled, we can now serve some customers who were wrong for us in the early days. But we would have failed if we had over-invested in those segments on Day 1.

4. Bring in the know-how early instead of reinventing the wheel

We named our company DoWhatWorks because we believe you do not need to reinvent the wheel on every facet of business - just the ones that create competitive advantage. So we sought experts to help create sales playbooks, outbound messaging, and routines that worked for others. They were unbelievably helpful. A lot of problems have already been solved by others. You can save time and money if you can learn from them and apply it to your situation. Saving months of trial and error. is money well spent.

Every time we add an expert we wish we had done it sooner. We are happy to grind, but it's important to pull up to save months of time. As we’ve grown, we’ve assembled a roster of experts to create sales playbooks, outbound messaging, and routines that have been proven to work.

Right now we are hiring experts with growth expertise so drop me a note if you are interested.

Summing up…

When trying to drive adoption for your product, you're trying to change their existing behavior. And changing behavior is always hard. 

It is easier than ever to launch things. But it's harder then ever to launch things people use (and pay for). Thanks to no-code, generative AI, and open source libraries, more products are getting launched daily. That creates noise and it's hard to get people's attention. It is harder still to get them to change their behavior. 

Look for signals that specifically show an intent to change and, more importantly, the willingness to pay. From there, you can find people like them and figure out how to cost-effectively serve them at scale. 

But it starts with authentic signals that someone values your solution enough to pay for it.

Image credit: Maarten van den Heuvel