How to identify buyers for your datasets using Ocean’s Data Markets

Market research by Dr. Mark Siebert & Scott Milat

Finding buyers for your datasets can be a time consuming process. If you don’t have much experience with sales, or if you’re doing this for the first time you may not even know where to begin.

Together with the Ocean DAO, we’ve developed a buyer segmentation strategy and a guide to building a target buyer list for selling your datasets using Ocean data markets.

Primary Segmentation Criteria

After a series of interviews and desk research, the two primary factors we identified for finding buyers for data sets on Ocean markets were;

1. How the business purchases data — Companies purchase data directly (acquire it themselves) or indirectly (through brokers and other data aggregators). Often when thinking about the ideal buyer for our datasets we think about the end user. Our research showed that intermediaries and data aggregators were among some of the most important data buyers in the data market today.
2. The size of the business — The buying behaviours (and needs) of data buyers from small businesses were very different to those at larger ones. This also had a large impact on the types of datasets they would be interested in, the budgets involved and the way in which you would need to approach the buyer to make a sale.

We summarised these two factors into the above matrix and identified 4 key buyer groups:

1. Small data brokers — niche use case intermediaries
2. Large data aggregators — big data market platforms
3. Individuals — independent researchers, data scientists, developers etc
4. Institutions — Governments, NGO’s, Big corporates

Secondary Segmentation Criteria

The secondary segmentation criteria is about identifying the buyers most likely to purchase from a Web3 data platform given the infancy of Web3 currently.

The two main criteria we identified were:

1. Data maturity of the industry — Is buying data new to them or are they likely to have already done this before? This helps to segment those buyers who would find purchasing data a relatively easy process vs. those having to figure out how to do it for the first time (can be more of a problem with larger organisations).
2. Crypto Maturity — Are they crypto native or will they find friction trying to understand crypto principles and/or using crypto tools? Ideally you want to target those already familiar with crypto wallets, ERC20 tokens etc. If not, an opportunity may still exist but you will need to put more effort into education and awareness first.

From this we were able to create a buyer matrix, used to help identify how likely a target buyer would be to purchase your datasets from Ocean data markets.

1. Short-term growth — Ideal ocean data buyers pioneering the market. Given how closely aligned they are they may even become a competitor.
2. Medium-term growth — These buyers are proactive and passionate about crypto but have no core data business (yet).
3. Long-term growth — Strong data economy but may need more hand holding/time to become part of the Web3 ecosystem.
4. Ignore — These prospective buyers need education and inspiration first.

Identifying Buyers for your Datasets using Ocean’s Data Markets

The two segmentation criteria outlined above provide you with a foundation to begin building your target buyer list.

Step 1: In a spreadsheet, write down a list of potential data buyers in the first column. Don’t know where to begin? We put together a list of 500 data prospects as part of this research. You can request access to this on the Ocean DAO’s discord channel.

Step 2: In the next two columns, use the primary segmentation criteria to classify the potential data buyers into four groups (small data brokers, large aggregators, individuals and institutions).

Step 3: In the next two columns, use the secondary segmentation criteria to classify the potential data buyers into four groups (short-term growth, medium-term growth, long-term growth and ignore).

Step 4: Add the data buyers to a table like the one below based on the primary and secondary segmentation criteria. You should quickly be able to identify the most likely data buyers for your data sets or identify critical gaps in your buyer list.

How to get the most from this template

• If you’re still in the early stages and wanting to see if you have a market for your dataset, you should aim to fill in the short-term growth and medium-term growth columns at the very least. This will ensure you have a relatively strong market for your data set.
• Once you have placed some potential data buyers in the short-term growth column you should start to look for patterns among these buyers to see if you can find more like them. Focusing your efforts here is likely to give you a much higher ROI on your efforts.
• When you have identified a target buyer list you can focus on better understanding the needs and wants of this buyer group to improve your chances of success. Try to identify who does the data buying for these organisations, understand what their needs are, learn how they look for data sets and identify where you need to position your dataset in order to stand out.

Further Research Findings

This is one of 5 articles that was published from this research. Links to the remaining articles can be found below.

• Go To Market Analysis for Data Markets & Data Brokers on Ocean Protocol
• 4 New Ocean DAO Projects that Build Upon our Research Findings
• Useful resources for future Ocean Data Brokers & Markets
• 7 lessons Web3 data markets can learn from the Web2 data economy

This work was made possible thanks to the Ocean DAO and created as part of our research proposal looking into which buyers are most likely to purchase data from Ocean markets rather than going anywhere else.