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Monetizing the Middle

Regular readers know that I am focused (fixated?) on a concept I call “central market position.” I use this term to describe companies (typically media and data companies) that occupy a trusted, established and neutral position in the markets they serve. Central market position is important because it can be monetized.

Traditional data publishers collect data themselves, whether via manual or automated means. They scrub it, organize it and otherwise add value to it, then turn around and sell it This is a solid, established and successful model, but companies with central market position have a much larger opportunity.

With central market position, you have the potential to do things that nobody else can, things that would otherwise be viewed as impossible. You can, for example, ask all the companies in your industry to share their customer lists with you, their sales data, employee information, their prospect lists – practically anything. How is this possible?

Well, two conditions must exist. First, this privileged information will only be provided if it is directly used to solve a major need or problem in the marketplace. Second, the intermediary who will be handling the information has to be established, trusted and neutral. The natural intermediary is a company that has a central market position.

Consider a product called PeerMonitor, a Thomson Reuters product. PeerMonitor literally hooks into the accounting software of participating law firms and sucks out all their billing information, right down to line item detail. Why would any law firm allow this? Because the need to know the going market rate for, say, a bankruptcy attorney in Atlanta far outweighs the reflexive need to protect information like this.

Consider also a company called SQAD in the media world. Advertising agencies electronically submit their purchase orders to SQAD. Are they giving away key company secrets by doing this? Yes, but it’s worth it because the data that comes back to these agencies – namely the real prices being paid for television and radio advertising – is more than worth it. And SQAD, as discussed, is a central, trusted neutral player that normalizes, de-identifies and aggregates the data in such a way that companies can give away their secrets without giving away their secrets. It works for everyone involved. Another interesting company is MDBuyline. Here, participating hospitals submit price quotes for medical devices and other hospital equipment. MDBuyline aggregates the data so that all participating hospitals can see the true going rates for medical equipment, not the meaningless list price. Again, the benefit is sufficiently large to justify supplying confidential information to a third party.

What you need to do is recognize your central market position, and start identifying market needs you can address as the central collector and aggregator of critical industry data that would otherwise never be shared. Trust me, the opportunities are endless. 


The Hidden Data in Invoices

The data business is one of creativity, and what could be more creative than asking companies to send you their invoices and other types of billing data so you can get them into a database and sell the aggregate results back to them? Now, why would something like this ever make sense? Well, in many industries, there is nothing more useful or important than pricing information. Yet the pricing information that many companies publish (if they publish it at all) is almost always the list price. And in many industries, the list price is close to meaningless, since every customer will have a special deal and varying discount. So how do you develop a database of what companies are really paying for specific products and services? Ask to see their invoices!

There are lots of spins on this intriguing model, so let’s take a look…

The question already on your mind quite likely is, “Why would any company let me look at its invoices?” The simple answer is what I often refer to as “strength in numbers.” A company will happily give up its individual data (properly secured and anonymized) in exchange for access to the aggregate results. And they’ll pay for that access, and that’s exactly the play here.

A great example of collecting, normalizing and reporting out information drawn directly from the internal systems of advertising agencies can be found in a company called SQAD. Its NetCosts product collects data for media purchases from advertising agencies worldwide, generating what may be the only honest look at what broadcasters are charging for media buys, and even what they have charged into the future. You can immediately see how valuable this information can be.

Thomson West has a product called Peer Monitor that does the same thing in a slightly different way: rather than work with the recipients of invoices, it works with the senders of invoices, in this case law firms, to collect similar data to be used in similar ways.

If it sounds like a lot of work, it is, or probably was. That’s because SQAD now receives most of its purchase data digitally, through interfaces with client systems. And while those interfaces were doubtless painful to build, at the same time SQAD has built an almost impregnable franchise, because as long as SQAD doesn’t get greedy, nobody can justify the time, cost and pain to try to compete with them. The same holds true for Peer Monitor.

There’s also what might be called the pre-order model. Here, your objective is to gather RFPs and proposals to get a true look at what companies are proposing to charge for their products. One advantage of picking up information at this stage is that there is often a lot more detail, allowing you to collect even more granular product price data. A great example of this model is MD Buyline, a company that collects price quotes and proposals on medical equipment to build a high-accuracy pricing database.

Lots of variant models, but the objective is the same: gather data on actual prices being charged in the marketplace, the more granular the better. Your job is to aggregate, normalize, and report back to the marketplace, while protecting the anonymity of those who participate.

It’s important to note that the need for pricing data isn’t equally compelling in every market. The dynamic seems to be a reasonably large pool of both buyers and sellers, and a solid tradition of haggling over price. It won’t work for everyone, but it’s certainly worth considering if it would work in your market.