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Institutions, organisations, and businesses have amassed petabytes of data which is not being utilised to benefit the owners nor potential users.

There are many reasons why this data has not been converted to dollars, but once a value can be identified then the road to building the business starts by creating strategies, products and leveraging resources.

We aim to identify the basic concepts in converting the potential dollar value of proprietary data and information into real revenue. Revolutionary and evolutionary changes in market data consumption, with greater enterprise usage, less terminal usage, combined with enhanced regulatory requirements is altering the market data landscape of who is using what, where, why, and how.

So what are the 8 Basics rules to building a market data business?

8 Basic Rules

1. Rule Own, Protect, and Police Intellectual Property Rights (IPRs)

2.Rule Know Your Data Inventory.

3.Rule Value Your Market Data.

4.Rule Understand The Market Place.

5.Rule Beg, Steal, Borrow, Having the Right Business Model.

6.Rule Leveraging the Right Technology.

7.Rule Building Successful Partnerships.

8.Rule Follow the Relationship Flows.


  • IPRs are the lodestones of the market data business.
  • Market Data ownership must be transparent and established at source.
  • This ownership should be recognised and acknowledged wherever and whenever their data is distributed, and at all points within the distribution universe.
  • IPRs must be protected and policed.
  • All contracts, agreements, distribution, and usage must reflect the IPRs of the source owners.
  • There must be clear line of sight from source to end user.
  • Data and information is licensed, not sold.
  • All IPRs are vested in the data source, not the distributors, not the subscribers.
  • There are 3 Key areas needed to be addressed:


  • Know your data inventory.
  • Starting at the very beginning, create a complete 360 degree view of all available content, and all associated attributes.
  • Building a data inventory of content establishes the offering.
  • Internal ownership must be established and incorporated as part of the service framework.
  • The inventory must identify all details regarding to the original source, how the data was created and its component characteristics.
  • The inventory needs to be kept up to date, and include identifying future additional datasets to grow the business.
  • Each data point is unique, so how will it be identified?
  • Data needs to be categorised, but a lot of data cannot be placed in 1 single category, e.g. convertible bonds.
  • There are 4 Key attributes.


  • What is the data worth? Why, and to whom?
  • Establishing the value of the data is dependent upon the dynamics of its usage.
  • Proprietary data which cannot be sourced elsewhere has more value than data than can be accessed from different sources.
  • An example, FX rates are available from multiple vendors, therefore there is competition amongst suppliers, but there is only one creator of the S&P500.
  • Where there are competing sources, quality and coverage has greater value on an aggregated basis, but there is a cost benefit analysis.
  • Breadth of coverage widens the potential audience.
  • Depth of coverage creates its own premium.
  • Regulators place their own premium on quality, and can themselves define the sources.
  • 3 competitive edges.


  • Understanding who the clients are is a start, understanding how they use the data maximises revenue.
  • Knowing who the clients are creates the business strategy.
  • Knowing how the clients intend to use the data creates the sales strategy.
  • No two clients are alike, but they do tend to share characteristics.
  • Financial institutions want to reduce costs, but at the same time are being forced into consuming ever more data.
  • This means financial institutions must, and are, becoming more discriminating.
  • But is this necessarily true of all financial institutions?
  • End users find new ways to use date before sources and distributors become aware.
  • The market place is both in a state of evolution and revolution.
  • Flexibility and intelligence is required.
  • Do sources and vendors artificially limit their horizons?


  • The wheel has been invented with many versions, some work, some do not (i.e. the square ones).
  • Each business is unique and copying others blindly rarely delivers like the original.
  • However each business model does share successful principles.
  • There are reasons why some models work and some do now.
  • Many have tried to emulate Bloomberg, right down to the screen colours, but each business is unique.
  • Too often new products fail because the business model is wrong for the target market.
  • The business strategy must be easy to understand and transparent.
  • Available resources are a major limitation, this means leveraging partnerships.
  • Understand what strategy means in its business application.
  • Know the difference between good business and good sales.


  • The revolution in technology is impacting market data at all levels. By the time this written, let alone read, it will have moved inexorably forward. Understanding the impacts is key
  • Having the right future looking technology strategies can make the difference between success and failure.
  • Traditional market data feeds and distribution channels are changing, breaking down and re-constructing.
  • However data licences especially for regulated entities, such as Exchanges, do not match capabilities in ‘The Cloud’ for ‘Big Data’ and other new game changing technologies.


  • All market data businesses require partnerships.
  • Technology and connectivity partnerships. Making sure the technology delivers.
  • Sourcing partnerships. Who supplies what and at what cost?
  • Distribution and sales partnerships. Vendors, sub-vendors, facilitators, ISVs and others. The force multipliers.
  • Client partnerships. End users and original works creators. The people who turn data into dollars.
  • Consulting partnerships. Expertise is another force multiplier.
  • Audit Trail. Document everything, maintaining easy access to complete contract information and documentation.
  • Clear line of sight on how the data flows from source to end users defines the relationships.
  • Keep to core IPR principles, implement effective control, monitoring, and reporting of market data usage.


Understanding relationship structures builds success.  Source. Quality. Flow. Fees


Building a market data business is not rocket science, and this article provides a guide to the more salient points to be considered when delivering information services to the financial community. Success requires research, investigation, and attention to detail, while trying to keep business as simple as possible.

Many of the points discussed above can be applied to any business, however, there are unique factors which make developing a market data business uniquely challenging.

These include:

  • Establish IPRs and adopt a transparent approach to ownership.
  • Content is king, so know what you have, what clients will need in the future, and then where to source it.
  • The value of data is relative, some information is worth more than others, however context is important and 1+1 can equal more than 2.
  • Intelligence is better than ignorance, research starts conversations.
  • What works for one business might not work for others, adopting the best features of others can work, but look out for the differences. Also what goes wrong for others can provide valuable lessons.
  • Technology is changing, it should now be part of the strategy, not just a facilitator.
  • Good business is built upon good relationships.
  • Understand how the information flow jigsaw fits together.

Remember Good Business and Sales are not necessarily the same thing.