What’s Going on With the Business Side at TIKI?

(And What it Means for Users)

Great question. In order for the business side of our project to work (our data marketplace) we have been working to solve two fundamental problems. First, how do businesses buy something that is constantly changing? And second and most importantly, how do you sell data to businesses who only know they need data, not necessarily what they are looking for or how they are going to use it?

As for the first problem, businesses want “now” data, not old data. A marketplace similar to Amazon, which is something we were pondering earlier, does not do a great job of offering something constantly changing. It’d be like ordering a product on Amazon and immediately realizing there is a new and improved product in its place for sale, on and on indefinitely. It doesn’t make a ton of sense, so we needed to think of a new way to sell data that is constantly new and “now.”

And the second problem? It’s a bit more complicated. In the current landscape, you either know how to work with data or you don’t. The percentage of businesses who actually know what they want is a tiny percentage of the number of businesses currently in operation. So do we only sell to businesses who are informed and know what they looking for? Given the percentages, that is not a logical route to take. These businesses already would have access to a ton of data, so the data they do want would be very specific, likely not very privacy-oriented (and therefore less likely for users to want to license that data) and would involve long contracts and lots of negotiation.

Not great.

So how do we sell to the majority? Especially when the majority of businesses don’t know what they want, what to ask, or what is even possible for them to access? These are the questions we’ve been wrestling with, and after lots of back and forth conversation, we arrived at an answer we feel is the future of our data marketplace: Spotify, but for data.

Allow me to explain:

You don’t need to be a musician to enjoy music. Spotify doesn’t offer you sheet music and make you create the music on your own. They just give you the music. Lots of it. With recommendations. Similarly, you shouldn’t need to be a data scientist to use data. What if, like Spotify, all the insights you can imagine were available at your fingertips? If the data is streamable and real-time, it solves the problem of how to buy something that is always changing. Streamable data will always be the most up-to-date version. If we can replicate the features that makes Spotify great, like search, recommendations, discovery, similar insights, etc, then we solve the problem of selling to businesses who aren’t sure where to even begin with data.

On the user end of things, it is very similar to how Spotify works with artists and song-writers. The artist gets paid when their songs are streamed. Users get paid when businesses stream insights that include their own anonymous data. With this model at the forefront of our minds, the pieces really started to come together.

So, if that’s the model that solves the two fundamental problems we faced in creating a data marketplace, then what are the next steps?

Well, we are beginning efforts to onboard 100 businesses to lead our initial cohort. These are businesses that will be able to understand our vision and the power of our platform as it is built out over time. These businesses need to see the potential, because early on, we are not ready to release our marketplace to the entire world. As you know if you’re using our beta, we currently operating exclusively with user email data. If we released it to the world, it’d be like if Spotify released with just classical music on the platform, or to be even more granular, if it released with strictly Beethoven music (or maybe even one album. Looking at you, Kanye.) If Spotify’s initial users expected a whole discography of music and only got Beethoven, they’d be unsatisfied and unlikely to come back to the platform.

So we’re looking for businesses who understand the initial iteration is not a value add, but a way to participate in a vision. As we onboard businesses, we will teach them how to use the platform with the insights generated from email data. We will ask them to test things out and provide feedback (Do they like it? Does it work? Is it useable? Is the UX friendly?), all the while proving that businesses want to use our product, a pivotal metric for when we raise our next round of funding.

The vision can be seen through limited insights similar to how the functionality of Spotify can be shown with just Beethoven’s music. Does it stream on your phone and desktop? Can it recommend similar compositions? Can you search for certain things? Can it be downloaded to your device? Is it fast? Is it reliable? Our initial cohort will be able to test these questions and provide us answers.

If this initial product works, it sets the blueprint for adding even more insights, just like Spotify provided a blueprint in its early days for what the product would look like with nearly all the music. The features didn’t change a ton, but they did improve and scale with the addition of millions of more songs. Same goes for releasing millions and billions of insights from the data we will add as we build. We’re priming the pump early to make sure what we’re building is scalable and is actually something businesses would want to use.

As mentioned, this is not only pivotal for raising money, but also for getting users paid. It’s a mutually inclusive relationship. We need user data in order to provide businesses with the insights they want, and we need a product businesses will actually use in order to get businesses to sign-up and stream the insights that gets users paid.

Rushing into the market was never an option. This is why we’re making sure what we’re building is a hit with an initial cohort that can see the future and potential of the world’s first free market for data.

Thanks for being patient with us. We’re excited as hell about what we’re building and signing up businesses should go live next week.

Stay tuned.