The Feed that Feeds Back

The Feed that Feeds Back

According to Chinese astrology, 2019 is the Year of the Pig. At Unacast, 2019 is also the Year of the Product. On top of internal ideas, market research and quality improvements, much of our product development is influenced by client feedback. We are motivated to build offerings that really matter to the people using our data. Whether it is an updated field, enhancement to an existing dataset or an entirely different direction to the roadmap, Unacast clients get exclusive sneak peeks of our new offerings. In fact, more often than not, our client-provided feedback initiated the request for that data in the first place.

From Products to Offerings

We recently launched a new focus, shifting from the concrete terminology of “products” to “offerings” - and yes, the change is more than just semantics. Offerings are constantly evolving and customizable, because we recognize that there is rarely a one-size-fits-all data solution, although there are certainly datasets with multi-industry value. When building out our offerings, we begin with the standard question: what challenge are you looking to solve? This creates a lively discussion with both Unacast’s and the client's product teams in a whiteboarding, brainstorming frenzy. Think: scribbles that make little sense to us commoners, in various colors of dry-erase marker.

Taking it to the Team

Next, we go back to our tech team in Oslo and download the highlights for them, ironing out the specifics of the problem that needs to be solved and how we might go about using our resource-rich data warehouse to solve it. This is where the magic happens. Our team of engineers hunkers down to create several iterations of solutions that result in a high-quality, scalable dataset that can solve not just the original challenge presented, but oftentimes other adjacent challenges as well. After that, it’s time to test and go to market!  

From Idea to Reality

A prime example of a client-derived offering is our Home & Work dataset. In early conversations with one of our very first clients, we learned that there was value in knowing the distance traveled between a person’s home and work location. This particular client would use the information to build pedestrian models based on how people move around in the world. In talking with other clients, we learned that home and work data is also helpful for targeting, conquesting and research. More importantly, we learned that we already had this data and it just needed to be analyzed differently to gauge how long a person was in a specific location during a specific time of day.  Fast forward to months later, we released our first iteration of the Home & Work dataset. The client spent a few weeks playing with the data and provided us with valuable feedback which helped us improve the methodology. We made the necessary tweaks and are now able to go to market with Home & Work more confidently.

The cycle of feedback on our data offerings  is continuous, and it brings tremendous value to our product team and to our entire client list. The fact that we can offer solutions to real-world problems using our real-world data is a true win-win.

P.S. - Pro-tip: Much like the example above, data can be manipulated in many ways based on a specific use-case. We recently decided to turn those use-cases into actionable, curated datasets that make life easier for our clients. You don’t need to do the leg work, we’re doing it for you. Just ask!

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