How to find data providers that add value to Ocean Protocol

TLDR

  • Some data providers might be able to provide data, but raw data on its own is not very valuable (relatively speaking). We should try to aim higher in the value chain.
  • Data buyers don’t buy data, they are buying valuable insights or better performance for their algorithms.
  • It all starts with a use case. A data buyer will have a use case in mind when looking to buy data. Data providers need to focus on and target specific use cases.
  • Even when armed with raw data and a use case, work is still required to extract value from that data. If a data provider can do some of this work the data they provide becomes a lot more valuable to data buyers.
  • Some data providers have no reason to use Ocean Markets and so should be avoided. 
  • Try to find data providers who cater towards use cases potential data buyers on Ocean Market would find valuable.

In this post I look at what makes up a successful data buying and selling transaction from the perspective of both the data buyer and data seller (aka data provider) to illustrate how to find data providers that add value to Ocean Protocol.

Breaking down a ‘successful’ data buying & selling transaction

Buying and selling transaction
I’m using a Japanese fish market as reference imagery throughout this post because you know… Ocean 🐟 Photo by Beth Macdonald on Unsplash

I define a ‘successful’ transaction as one which adds more value to the data buyer than the cost to acquire it. If the buyer doesn’t get more value from a data purchase than the cost to acquire it they’re unlikely to be happy and even less likely to come back for more.

Successful data buying and selling transaction = Value Gained – Cost is >1

Raw data on its own is not very valuable (relatively speaking)

Raw data
Photo by Matt Alaniz on Unsplash

It quickly became clear that not all data was equally valuable and data on its own is of lower value. 

Raw data is like raw materials feeding a manufacturing supply chain. It’s valuable on its own but it becomes a lot more valuable as it makes its way through the supply chain with each step of the manufacturing process.

No point in chasing down ‘raw data’ suppliers for this task!

It all starts with a Use Case

As soon as data has a use case it becomes significantly more valuable. Some use cases will be more valuable than others and so looking for high value use cases is a really important factor too.

You can add a lot more value to your raw data by appealing to the use case your data buyers are looking for. 

Examples include:

  • Recommended use case(s).
  • Providing case studies and illustrating the value your data could add to buyers.
  • Defining the industries &/or types of organisations who would be interested in buying your data set.
  • Defining and reaching out to the individuals that would be interested in purchasing your data set to validate your assumptions.

One of the benefits here is that you can literally validate demand within the market in much the same way that a startup does when launching a new venture. It’s a lot cheaper and easier to go out and validate demand for your use case before incurring the costs of acquiring data and doing the work to make it appealing to potential data buyers.

Data + Use Case

Work is a key input that makes a data provider even more valuable

Sometimes there’s not much work to be done in order to adapt the raw data for a specific use case and the cost of doing that work is low, but other times there is a lot of work to do and the cost of doing that is much higher. 

As a data provider, you can’t always do all the work required to deliver on the needs of the buyer’s use case, but ideally you want to do as much of this work as you can to ensure your data is of maximum value to the target buyer.

Examples include:

  • Enriching your data to better cater towards the recommended use case(s)
  • Doing some of the work (cleaning, analysis, recommending ML algorithms etc) to make your data set more attractive.

Data + Use Case + Work

Data providers still need to make a profit

Because Ocean Protocol relies on successful transactions, one key factor is missing from this and that’s profit. 

If it’s not profitable for the data provider then why would they stay and keep providing data to Ocean Markets? 

With Ocean Protocol this profit is made up of both revenues from data sales and staking rewards. 

Data + Use Case + Work + Profit

Turning this all into a ‘successful’ data buying and selling transaction

We saw earlier that the cost of the data needs to be less than the value the data buyer gains from it.

Value – Cost is >1

This means, we should try to attract data providers who have access to raw data and can do work which makes their data valuable to data buyers. The data buyers are looking to use the data for a specific use case and the data provider needs to remain profitable throughout this process.

There are some Ocean related instances where the profitability side becomes quite unique. With data unions for example, a data provider might ‘delay gratification’ for the value their data set provides by creating shared ownership of a data token. 

In this instance, the data union still needs to remain profitable over the long term through providing a combination of Data + Work + Use Case.

Some data providers have no need for Ocean Markets so should be avoided.

Photo by Thomas Marban on Unsplash

To illustrate this point we can look to some of the biggest data companies of our time, Facebook and Google. 

While they have all the fundamental characteristics (Data + Use Case + Work), AND can sell their data to data buyers at a profit (advertisers), they already have established products which are generating value from the data they collect. 

These are two examples but there are millions of other potential data providers like them. They have no need for a secondary market so we need to avoid data providers who fit this criteria (for now).

Avoid data provider traps!

Jokes, Octopus can be delicious, I’m just not good at working with it 🐙 Photo by Beth Macdonald on Unsplash

When searching for data providers it’s important to avoid the traps!

You could have a data provider who has access to data, a use case and has done work to make it valuable. Yet still they are unable to provide enough value to data buyers and therefore the data set is not valuable enough to be sustainable in an Ocean Market!

To avoid this we can put a specific focus on finding data providers that provide a valuable combination of Data + Use Case + Work while remaining profitable. 

Better still, we can try to find data providers who would appeal to the types of use cases our potential data buyers would find valuable.

Up next…

The criteria for a data provider that adds value to Ocean Markets and would be most likely to gain value from Ocean Protocol (in these early stages) is becoming more clear. 

I’m going to bring together all of these learnings in an attempt to find my target data providers which I can then begin testing some of these assumptions with and understanding why they might be interested in providing data to Ocean Markets.