Juice has spent the last year and a half developing Blueprint and bringing it to market. It all started with the idea that we could monetize the data we have access to through our partnership with HealthStream, and create and launch something useful for our customers.
As we worked to bring this idea to fruition we put together a product roadmap of features we would like to see and ways that we think our customers would interact with it. We realized that it wasn’t enough to just put the data into Juicebox and throw some visualizations at it; we wanted to ensure we had a product that would sell, be easy to describe, and bring value to our customers. In order to do that, we established some phases that we needed to go through with the product to bring it to market.
For the purposes of this blog post, I am going to just talk about market validation and the steps we took that you can incorporate into your own data product research.
Our first step in launching our data product was to validate some important things. Primarily, we needed to discover if there even was a market for Blueprint. We went about that a number of ways, and ultimately discovered that there was indeed a good-sized market. We researched who our potential competition was and studied their features to ensure that our product was unique enough to differentiate ourselves. This turned into a really valuable exercise for us as a team. We took the time to write out, brainstorm, and verbalize how we are different from others in our space. This was a vitally helpful step in the process to not only gel our team, but to get us all on the same page.
Secondly, we needed to validate that we had buyers! This was quite possibly the most important step, as we could have created the most stunning visuals in the world with the cleanest possible data, but without a buyer we would be left with only some fancy visualizations and no one to share them with (whomp whomp). We were strategic in our approach to finding the right buyer. We worked hard to understand industry trends, their pains, and craft Blueprint to make sure it met those needs.
We also had to understand our customers' motivation for buying Blueprint. Was it to fix an immediate problem? Address an issue coming down the pike? Or proactively equip their organization to make good decisions in the future? We found out all of these were motivations.
User feedback was vital for us in understanding if the end user of Blueprint was an organization, a person, or a group of people. We had to work through who we wanted our end users to be and settled on HR leadership as our primary users within a health system. We discovered that other executive leadership received value from insights into their staff. This turned out to be a discovery that led us to new customers. When reaching out to these groups of leaders we offered a demonstration of Blueprint and asked for feedback of what they would like to see in such an application. It was important for us to take their feedback and incorporate it into Blueprint, and then go back to them once it was completed to get more input. We also asked some of the individuals we interviewed and demoed for to be on our product advisory panel. Doing that gave us great insight on how to best design the product for the market.
Incorporate these steps into your own data product market research, and you're well on your way to your first sale!
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