Being in the Middle of a New Data Product

I’ve written before about the application model called the “Closed Data Pool.” In this model, companies (and many times they are competitors) contribute proprietary data to a central, neutral data company. The data company aggregates the data and sells aggregate views of the data back to the very companies that contributed it. Madness you say? Not really, because these companies get great benefit from those aggregated views (think market share, average pricing and other vital business metrics). It’s the neutral, trusted data provider in the middle who makes it possible. 

But there is another twist on the closed data pool that represents an even more profitable business for the data provider in the middle. Consider a company called The Work Number.

The Work Number came into being because a lot of credit grantors need to be able to quickly verify employment status and income. At the same time, companies hated getting an endless stream of calls from creditors seeking to verify employment data. The Work Number came up with an ingenious solution. It went to big companies and said that they could outsource all these nuisance calls to The Work Number. All the company had to do was supply a feed of its payroll data. 

The Work Number then went to major credit grantors such as banks and said that instead of those painful verification calls they were making, credit grantors could just do a lookup on The Work Number website and instantaneously get the exact data they needed.

The best part? The Work Number was able to charge credit grantors for access to the database because of the big productivity gains it offered. But The Work Number was also able to charge the companies supplyingthe data because it increased their productivity as well by eliminating all these annoying verification calls. Yes, The Work Number charges both to collect the data and provide access to it!

If this sounds like an interesting but one-off opportunity to you, it’s not. Opportunities exist in vertical markets as well. Consider National Student Clearinghouse, which does the same thing as The Work Number, only with college transcripts.

Is there an opportunity in your market? Look for areas where relatively important or high-value information is being exchanged by phone or one-off emails or even by fax. If the information exchange constitutes a serious pain point or productivity drag for either or both parties, you’ve probably got a new data product. 

Workflow Elimination

The power of embedding one’s data product into a customer’s workflow is well understood by data publishers. Simply put, once a customer starts depending on your data and associated software functionality, it’s hard to cancel or switch away from you because the customer’s work has become designed around your product. It’s a great place to be, and it’s probably the primary reason that renewal rates for data products can sometimes verge on 100%.

But should workflow embedment be the ultimate objective of data publishers? This may depend on the industry served, because we are starting to see fascinating glimpses of a new type of market disruption that might be called “workflow elimination.”

Here’s a great example of this phenomenon in the insurance industry. A company called Metromile has rolled out an artificial intelligence system called Ava. What Ava does is stunning.

Auto insurers using Ava require their policyholders to attach a device called Metromile Pulse to their cars. As you may know, virtually all cars now have onboard computers that log tremendous amounts of data about the vehicle. In fact, when your local auto mechanic performs a computerized diagnosis of your car, this is where the diagnostic data comes from. Metromile Pulse plugs into this onboard computer. The device does two things for insurance companies: It allows them to charge for insurance by the mile, since the onboard computer records miles driven and the device transmits them wirelessly to the insurer. That’s pretty cool and innovative. But here’s what’s mind-blowing: if a policyholder has an auto accident, he or she can file an online claim, and Ava can use the onboard data to confirm the accident, re-construct the accident using artificial intelligence software, and automatically authorize payment on the claim if everything checks out, and all this can be done within a few seconds. The traditional claims payment workflow hasn’ just been collapsed, it’s effectively been eliminated.

How does a data publisher embed in workflow if there’s no workflow? That’s a problem, but it’s also an opportunity, because data publishers are well positioned to provide the tools to eliminate workflow. If they do this, and do this first, they’ll be even more deeply embedded in the operations of their customers. And doubtless you’re already thinking about all the subsidiary opportunities that would flow out of being in the middle of so much highly granular data on automobile operation.

“Workflow elimination” won’t impact every industry quickly if at all. But it’s an example of how important it is to stay ahead of the curve on new technology and always seeking to be the disrupter as opposed to the disruptee.

Meet Three of the Best…

We created the Infocommerce Models of Excellence program back in 2003 to recognize data products that provided good examples of innovation in business models, markets served, content innovation and technology.

The point is that they offer fresh ideas and approaches that are applicable across many market verticals, and that’s why they’re worthy of attention and study.

The three honorees this year, in no particular order are:

Franklin Trust Ratings, a healthcare data provider that has not only done an impressive job integrating nearly a dozen public domain databases, but has an innovative business model as well. Franklin Trust founder John Morrow is building his business around the idea of “democratization of data.” In simple terms, this means that that he is consciously building an end-user analytics tool, using a powerful but simple user interface with pricing that makes it accessible to all. In an era of five- and six-figure analytics-driven data products built for trained data analysts, Franklin Trust has built an analytics product that can be used by anyone, and that anyone can afford.

Savio has developed a talent marketplace for the marketing research industry. Talent marketplaces aren’t a new concept. Indeed, it can be argued that they helped jumpstart the growth of the gig economy. Savio has bigger ambitions, however, seeking to tap into the growing shift to automated vendor discovery and procurement, as well as to start to evolve its existing online buying guide product to a truly transactional meeting place for buyers and sellers. It’s almost inevitable that all buying guides will have to move in this direction. Savio is blazing the way.

LexisNexis Risk Solutions is one of the largest and best-known data players out there, but that’s not inhibiting it on the innovation front. Consider its new Active Insights product for the insurance industry. How many millions (billions?) of dollars have been spent building out cutting-edge lead generation technology. Whatever the number is, it’s huge. How much has been spent on similar technology for custom retention? It’s a tiny amount by comparison.

What Active Insight does is simple yet brilliant. It flips lead gen technology on its head and applies it to customer retention. An insurance company supplies its custom file to LexisNexis Risk Solutions, which monitors them in real-time for trigger events. Did a customer just put her house up for sale? LexisNexis Risk Solutions spots the real estate listing and tells the insurance agent to get in touch with the customer ASAP to help her seamlessly transfer her coverage to her new home. We have the technology. This is just a great new way to put it to use.

All three of our 2017 honorees will be presenting at the annual BIMS conference next week in Ft. Lauderdale just. Their creators are people you’ll want to meet to put their experience and innovation to work for you in your industry. See you there.

Good Databases Are More Than Just Good Data

We can look to the UK for a case study of how a government agency, after several tries, couldn’t build a user-friendly data product, creating a giant opportunity for a for-profit data company.

The story begins with a regulatory agency called the Financial Conduct Authority (FCA) that among other duties, registers and regulates financial advisors and advisory firms. The FCA has a searchable database on its website, but like so many government websites, it is optimized for one purpose: checking the registration status of a known individual or firm. As a tool to assist you in identifying an advisor to help you with your investments, it’s pretty useless.

In recognition of this shortcoming, the FCA called on a quasi-governmental organization called the Money Advice Service (MAS) to help build a better adviser database, and MAS accepted the challenge. I took a look at this website when it first launched, and though I saw some design issues, it had potential.

But even though MAS nominally had the freedom to build a creative database with almost any business model behind it, its need to avoid controversy ultimately resulted in a very limited and timid product. And when, unsurprisingly, there wasn’t a lot of revenue to be had with such a product, MAS buried the database three levels down on its website and moved on to greener pastures.

With two free databases of financial advisers out there, you think there wouldn’t be much opportunity left for anyone. However, a company called Unbiased saw things differently, and said there was indeed an opportunity … for the right product.

Unbiased has been a big hit in the marketplace, and the way it differentiated itself from the free government services with the same basic listing data holds lessons for us all

• Greater visibility – Unbiased wants to be found because its business model depends on driving lots of traffic to its participating advisers
• Deeper data – ratings, discount offers and detailed profiles
• Strong user interface – clean, inviting design and both parametric search and a custom matching service         

If you have ever wondered how you could compete against a free, government online database, Unbiased provides the answer: data presentation can be as valuable as the underlying data itself, particularly if you are serving a consumer market. And aggressive promotion of your online database will let you run circles around government agency databases, that are generally hard to find in addition to being hard to use. 

Knowing More Than You Can Tell

Most of you have some familiarity with Gerson-Lehrman Group (GLG), the phenomenal success story that pioneered the idea of connecting experts on a wide variety of topics with those who needed fast, trustworthy and unbiased insights into a market, a company, a technology … whatever.

Not surprisingly, GLG found most of its clients in the financial sector, from hedge funds to private equity firms and others that needed expert insight fast to inform the often significant investment decisions they were making. These clients paid fat fees, and the experts were well paid for small chunks of their time, and it all went swimmingly for many years.

Where things got awkward is that some investors wanted more than background information: they wanted confidential information. GLG was very aggressive about policing this, understanding that it could damage its business. However, some GLG competitors didn’t have the same ethics, and differentiated themselves by playing on the often-murky line between public information and inside information. This potential to misuse the raft of expert services that now exist continues to cast a pall over another otherwise strong business model.

Enter a new start-up called Emissary. It’s an expert service, but rather than focusing on connecting experts to investors, it seeks to connect experts to salespeople. Want to know how to tailor your pitch to a particular company? Emissary can find someone who knows. Similarly, salespeople often find themselves wondering if they are dealing with a decision-maker or not at a particular company. Say hello to Emissary, whose experts may well have worked at the company in question.

Visit the Emissary website, and you’ll see a carefully crafted message: we’re just people helping other people. At one level, this is certainly true. And connecting a sales team to a recent former employee of the prospect company doesn’t seem to be rife with the same legal and ethical issues that exist for investors, but I suspect Emissary’s long-term success will depend on it also establishing an ethical line in the sand and policing it closely.

What also makes Emissary interesting is it’s a model that can be moved not only across verticals, but across functional areas as well.