Data Monetization 101 – KDnuggets


By John Farrall, Co-Founder at 90 West Data, LLC.

“Data Doesn’t Sell Itself” ~ Emmett Kilduff, July 2020

I co-founded 90 West Data, LLC in late 2019 and have been working to monetize a unique panel of US Consumer Transaction Data. This blog is an attempt to share what I have learned about the market.

It is important to note that this industry is dynamic and rapidly evolving. We are in the early stages of growth. This has fostered a wonderful culture of cooperation among the industry participants. It is a joy to be along for the ride.

 

Target Market

 

“The Big Guys”= Top ~50 Global Institutional Investment Managers

  • Professional investment managers
  • Significant internal data science resources
  • Systematic/quant-focused investment firms or, increasingly, “quant-a-mental”
  • Looking to buy data (raw, clean, complete, consistent)
  • “Get me the data & I will figure it out from there.”

“The Long Tail”= The next 500-1,000 Global Institutional Investment Managers

  • Professional investment managers
  • Understand why additional new data sources would improve decision-making
  • Typically do not have significant internal data science resources
  • “Make it easy for me to answer my questions with new data sources.”

“The Project-based Guys” = VC & PE

  • Professional private company investors
  • They understand why new data sources will improve decision-making
  • The largest firms are starting to build internal data resources, but most do not have
  • More project-oriented
  • “Help me find & diligence my next project.”

“The Next Big Thing” = Corporate Market

  • Business decisions for corporate managers
  • This prospective customer might not yet understand this type of data is available.
  • The use case is not always obvious
  • Only the largest Fortune 500 firms have dedicated data resources
  • More of a consultative sales process (& ongoing relationship)
  • “Help me understand why this data will help me & help me sell that internally.”

 

How do you sell to these markets?

 

In my attempt to understand the market, I’ve grouped industry players into five categories:

  1. The Conference Providers & Data Vendor Listers
  2. The Refiners
  3. The Product Creators
  4. The Introducers
  5. The Marketplaces

The Conference Producers & Vendor Listers

These “OG” alternative data firms continue as conference producers (virtual during COVID) & typically have the most robust lists of the thousands of data vendors available.

These live event conferences have served as networking must-attend-events in the past and will again in the future.

These players have been tremendously helpful when it comes to organizing the space & reducing friction in the process.  The events are a great way for both the data vendor & data buyer to get a high-level overview of the market.

In my experience, the direct selling of your data starts with these companies & events.

Revenue Model

  • Traditional pay-to-attend conference model
  • Various fees from both data buyers & sellers for introductions, list access, other resources

Target Market

  • All data buyers & all data vendors

The Players

  • BattleFin
  • Eagle Alpha
  • Neudata

The Product Creators

These firms have invested in the ability to process large amounts of alternative data and include the resulting insights in a digestible format for decision-makers.

The larger players are modeled after traditional sell-side equity research firms. These firms track stocks, publish reports & can offer buy-hold-sell ratings. Other firms create dashboards, specific models, or signals that are used to create portfolios and/or drive specific buy-sell signals.

These firms own the client relationship. They buy data directly from data vendors to use in their offering.

Revenue Model

  • Modeled after traditional sell-side equity research firms
  • Investment professional typically pays an annual subscription fee
  • Can be “hard” or “soft” dollar

Target Market

  • Large Institutional Investment Firms
  • Can move “down-market” into RIA’s & Family Offices
  • VC & PE firms
  • The larger firms are starting to create products targeted at the corporate market (non-investment space)

The Players

  • 1010data (Advance)
  • Consumer Edge
  • CloudQuant
  • Earnest
  • M-Science
  • Neuravest
  • Quandl (NASDAQ)
  • Second Measure (Bloomberg)
  • UBS Evidence Labs
  • YipitData

The Refiners

Data is the new oil. And like raw oil, raw data is not much good to the ordinary person unless it is refined into something much more useful.

These firms are largely trying to remove friction from the process. Most institutional investors recognize that new data sources can improve their decision-making, but the amount of available data is overwhelming. This service can be anything from making sure the data is clean & easily ingested to providing slick dashboards to make it easy to answer relevant questions.

For the data vendor, a key point to consider is who “owns” the customer relationship. In many cases, these firms will control the customer relationship, which can be a positive as this model evolves into the go-to method for the “long tail” to consume alternative data.

Revenue Model

  • Data vendor often pays to be included in a platform
  • Revenue share of the final offering
  • “Refiners” may be on retainer with data buying firms

Target Market

  • The “Long- Tail” of investment firms
  • Can move “down-market” into RIA’s & Family Offices
  • Growing presence in the corporate market

The Players

  • AlphaROC
  • BitVore
  • Bright Data
  • CloudQuant
  • Crux
  • CueMacro
  • Data Lagoon
  • Exabel
  • Explorium
  • Invisage / AltHub
  • Knoema
  • OttoQuant
  • SimilarWeb
  • System 2
  • Tickmill

The Introducers

These are firms that will provide warm introductions to proven data buyers. The data buyers appreciate this because the intro firms understand what the data buyer is looking for & have diligenced the data vendor at some level.

Beyond the introduction, these firms might advise but typically aren’t engaged in the procurement, cleaning, and delivery of the data. The client relationship is often left between data vendor & data buyer.

Revenue Model

  • Data vendor pays the introducing firm a % of first-year revenue
  • Data vendor potentially pays a declining portion of future revenues
  • These firms may also be held on retainer by the data buyer & treated as a “data-hunter” for these firms

Target Market

  • Top ~50 largest data buying investment firms
  • Expanding into Top 100-200 firms as the industry matures

The Players

  • Alqami
  • AltHub / Invisage
  • Alternative Data Analytics
  • Amass
  • BattleFin
  • CP Capital
  • Eagle Alpha
  • Neudata

The Marketplaces

These are firms attempting to create robust buy-sell marketplaces for data. Some of the varying aspects of these marketplaces are fee structure & customer ownership.

Data vendors are free to publish their data on the marketplace.

The biggest challenge is getting engagement from the data buyer. Data can often be complex and need some direct sales effort to execute.

Revenue Model

  • Marketplace gets % of the deal size

Target Market

  • Anyone interested in buying data
  • Investment professionals of all sizes
  • Non-investment market

The Players

  • Amass / Big Data Protocol
  • Amazon Data Marketplace
  • Datarade
  • Data Lagoon
  • FactSet
  • IEX Cloud
  • Nomad Data
  • S&P Global
  • SnowFlake Data Marketplace

Original. Reposted with permission.

 

Bio: John Farrall has 20+ years of experience working with institutional investment managers. Most recently John was a founding partner with Cleveland Research, a premier fundamental investment research company. The founding of 90 West Data is an opportunity to become a leader in the use of big data analytics to improve investment decisions. John lives in Cleveland, Ohio with his wife Daneen and their four kids.

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