Monetizing Information Flows

StreetContxt is a hot, Canadian-based start-up that just raised $8 million from A-list investors, including a number of big banks and brokerage houses. Its mission is simple: to maximize the value of the mountain of investment research that gets generated each year. But what really makes StreetContxt stand out to me is that it offers a very compelling business proposition to both those who create the research and those who use it.

For the sell-side (those who create the content), it’s currently difficult to measure the impact much less the ROI on the huge volume of research they create annually. They send it out to presumably interested and qualified recipients, with no way of knowing if it is acted on, or even viewed.

For the buy-side (those who receive and use the content), it’s impossible to keep up with the blizzard of information being pushed out to them. Even more significantly, some of this research is very good, but a lot of it isn’t. How do you identify the good stuff?

StreetContxt offers the sell-side a powerful intelligence platform. By distributing research through StreetContxt, research producers can learn exactly who viewed their research and whether it was forwarded to others (multiple forwards are used as a signal to suggest a timely and important research report). What naturally falls out of this is the ability to assess what research is having the most market impact. But StreetContxt also helps research producers correlate research with trading activity to help make sure that their research insights are being rewarded with adequate commission revenue. Even better, StreetContxt helps the sell-side by providing insight into who is reading research on what topics and with what level of engagement in order to help power sales conversations. In short, StreetContxt tracks “who’s reading what” at a very granular level both to measure impact but also to inform selling activity.

On the buy-side, StreetContxt helps those who use research with a recommendation engine. Research users can specify topical areas of interest that get tuned by StreetContxt based on who is reading and forwarding what research reports. In other word, StreetContxt has found an approach to automatically surface the best and most important research. StreetContxt also helps research users by monitoring relevant research from sources to which the research user may not currently subscribe. And since much research is provided in exchange for trading commissions, StreetContxt can help research users get the most value from these credits.

The magic described here happens because the content creators post to the central StreetContxt portal, and research users access content from the same portal. This allows StreetConxt to monitor exactly who is using what research.

Why would research users allow their every click to be tracked and turned into sales leads? Because StreetContxt offers them a powerful inventive in the form of curated research recommendations, a better way to manage research instead of having it flood their in-boxes as it does now, and most importantly of all, a way to ferret out the best and most important research.

The big lesson for me is that with a sufficiently compelling value proposition on both sides, smart companies can position themselves in the middle of an information flow and monetize the resulting data in powerful and profitable ways.

Data With Backbone

You may recall a political dust-up this summer when the Clinton campaign accused the Sanders campaign of gaining illicit access to its voter data. How was this even possible? Well, it all traces back to a private company called NGP VAN.

NGP VAN, which works only with Democratic and progressive candidates for office, maintains a central national voter database that it regularly updates and enhances. Providing campaigns with convenient access to enhanced voter data is a good product in and of itself, but there’s a lot more going on in addition to that. Each campaign uploads its own donor files to NGP VAN, where they are matched to the central voter database. In a sense, NGP VAN offers a comprehensive backbone file of all voters, and each campaign attaches its transaction history to that backbone file. If a single voter gives to two campaigns, the voter will have two records attached. Critically, campaigns can only view their own records, or that’s the way it’s supposed to work. A botched software upgrade apparently gave the Sanders campaign the ability to view records from the Clinton campaign.

This software snafu notwithstanding, this “backbone” data model is an interesting one. Because NGP VAN only works with candidates blessed by the Democratic Party, all the activity by all the campaigns is viewable in the aggregate by the Democratic Party, providing real-time insight into campaign field activities nationwide.

In addition, by matching to a dependable backbone file, each campaign has unduplicated access both to known supporters in addition to everyone else in its area, all in a single, normalized dataset The matching process also helps campaigns identify and eliminate duplicate records. As NGP VAN identifies new third-party data elements that might be helpful to its campaign clients, it appends them to its backbone database, making them immediately accessible to all its clients. NGP VAN also supplies a sophisticated user interface to its clients, including door-to-door canvassing tools that operate on an iPad. Finally, NGP VAN makes it easy to export client data to any of a number of analytical tools and services used by the campaigns.

The basic idea of building a comprehensive industry database and software platform, and letting clients deeply integrate their data into it, so that all their customers and every possible prospect reside in one place in one format – that’s deep embedment. A number of data companies are backing into this model, albeit slowly, but SaaS really opens up the prospect of everyone in a vertical industry sharing the same data without giving up any confidential information. Could your market use some backbone?

2015 Models of Excellence: Bucking the Disruption Trend

With the deadline for the Business Information & Media Summit fast approaching, here are four excellent reasons to look forward to your trip to Ft. Lauderdale (or to sign up if you haven’t already).

Trucker Path – Trucker Path is laudable from several perspectives. First, it developed a useful, much-needed and very successful app for truckers to use to find gas, food and even rest stops while on the road. It’s all neatly executed, utilizing GPS to pinpoint the nearest amenities, crowdsourced data and even user reviews. Even the advertising in the app is driven by proximity to the advertiser. This would be a nice business in itself, but Trucker Path has gone further. Leveraging the 300,000 users of its app, it is now launching a matching service to connect truckers to those who have freight that needs to be shipped. Marketplaces like this can be tough to launch, but Trucker Path took its time, and built not only a loyal following, but a trusted neutral brand, all key elements to succeeding with a new industry marketplace. All of this hard work is driving it towards a billion dollar valuation.

Parking Panda – Parking Panda was originally envisioned as sort of an Airbnb for parking spaces. If you lived near a stadium, for example, and wanted to rent your driveway, Parking Panda would connect you to those looking for parking.

The concept has evolved quite a bit since then. Parking Panda has now allied itself primary with parking garage operators, an industry badly in need of a technological assist. Now a consumer can specify a destination, and Parking Panda will identify available parking garages – all with guaranteed availability – provide rates and allow for online booking. Increasingly, Parking Panda users are even able to enter and leave the parking facility using only the Parking Panda app.

For garage operators, there’s also a payoff. They get greater operational productivity, a way to market themselves to better sell available inventory, the ability to vary prices in real time to respond to demand, and powerful customer analytics tools. High profile partners the Horseshoe Casino Baltimore, Tampa Bay Rays, and the Washington Nationals.

PeopleTicker – PeopleTicker is a classic, ground-up data play. Numerous systems already exist to help companies compare and benchmark full-time jobs to help them select the correct salary level. But what about the burgeoning contingent or “gig” economy? PeopleTicker saw a need to develop comparable benchmarking tools. It now draws on feeds of data supplied by major employers, augmented by web harvesting and other data sources, to build this unique dataset. Moreover, it’s made a significant investment to build more precision around job descriptions for greater comparability.

Quorum – Quorum is a data analytics company founded by two Harvard school buddies who went from mapping proteins to mapping relationships between members of Congress. Barely a year old, this startup is an online legislative strategy platform that provides legislative professionals access to the world’s most comprehensive database of legislative information, unique quantitative insights, and modern project management tools. With Quorum, users can easily search, save, comment on, and receive email alerts for all bills, votes, tweets, press releases, floor statements, caucuses, committees, and staff contact information from the U.S. Congress and all 50 state legislatures.

Quorum’s advanced quantitative analytics provide information on each legislator’s top issues, most frequent collaborators, ideology, voting history, and legislative effectiveness. By enabling users to easily log meetings, clearly highlight differences between bills, create legislative spreadsheets, and quickly email multiple legislators and congressional staff, Quorum’s productivity features save users valuable time.

Quorum’s comprehensive data, quantitative insights, and 21st-century productivity tools are changing the way people track legislation, build support, and take action – and it just might change the Beltway’s influence peddling industry for the better.

Bucking the Trend

As with all of our Models of Excellence, these are clearly all very different businesses. But all four are trying in different ways to enhance the efficiency of the markets they serve. In the case of Parking Panda and Trucker Path, their solution was to actually build online marketplaces. For PeopleTicker, it’s putting information infrastructure in place to make the market run more efficiently. With Quorum, the goal is to help organize and manage the process of creating and influencing legislation.

Perhaps more significantly, all four companies didn’t feel they had to disrupt their markets to make a place for themselves. Trucker Path’s new marketplace doesn’t try to cut out the freight brokers; indeed, it welcomes their participation. Parking Panda isn’t trying to find an alternative to parking garages; it’s helping that industry operate more conveniently and efficiently. And PeopleTicker didn’t try to become a recruiter or job site; it simply provides the critical data needed to make the existing market more efficient. What we see with Quorum is a sophisticated effort to organize a complex and unwieldy process for the benefit of those working in that industry. So while disruption is all the rage these days, there are still plenty of strong opportunities to bring what I call “innovation overlays” to markets.

You’ll have the unique opportunity to learn from the innovators behind these fascinating companies at BIMS 2015 in Ft. Lauderdale, See you there!

Big Data: The Power of Plug and Play

InsideSales.com recently announced the launch of a new service called The Predictive Cloud that provides API access to its powerful predictive engine. InsideSales made its name, not surprisingly, by adding predictive capabilities to sales prospects. By aggregating very granular prospect data from its customer base (over 100 billion sales interactions), InsideSales can not only predict who is a top sales prospect, but even what day of the week is best to make contact. The Predictive Cloud throws this impressive analytical and predictive capability open to anyone who wants to use it, even if they want to use it to predict their own top prospects, though what really excites InsideSales is the belief that other companies with lots of data will find non-sales applications for its predictive engine, such as logistics, marketing and even human resources.

While The Predictive Cloud has obvious applicability to many commercial data products, it’s representative of an important trend: the ability for data providers to tap into cloud-based plug-and-play datasets and analytical tools to enhance their own products. It’s a hugely positive development for data companies, because these new tools and datasets allow us to access Big Data in a useful and powerful way without having to become Big Data experts. Similarly, we can now start to tap into analytical toolkits without the expense and complexity or having to build them … or even run them.

I’ve been saying it for several years now: Big Data doesn’t imperil commercial data producers, most of which produce what can be called “Little Data.” Indeed, Big Data can be used to enhance Little Data and make it deeper and more powerful. The analytic tools and capabilities that have come out of the rush to Big Data can also now be profitably employed by Little Data producers as well.

There’s a lot going on out there, but everything I see still tells me that those who control a valuable dataset are still in the driver’s seat, especially if they take full advantage of these plug-and-play opportunities to make their datasets smarter, deeper and ever more useful to their customers.

Evolving From Data Providers to Market Makers

Trucker Path is a young company, founded only in 2013. Yet its mobile app, providing truckers with basic directory information such as location of rest stops, parking, diesel fuel stations, weigh stations and more has already attracted over 250,000 users. Its formula for success is a familiar one to data publishers: collect information that is really needed by a specific niche market but not readily available in one place elsewhere.

Another mobile app success story to be sure. And Trucker Path could have rested on its laurels. But just a few days ago, it signaled a much more ambitious vision with the launch of a new product called Trucker Marketplace. It is exactly what the name implies: a marketplace where truckers can find and connect with those who need to ship freight, either regionally or nationally.

It’s a simple concept, and it’s also not a new concept. Many companies have sought an intermediary role in this inefficient marketplace, particularly in the area of backhauls, where trucks often return home empty after delivering a load. And the opportunity is huge: more than 75% of all freight in the U.S. is delivered by truck.

Obviously, Trucker Path has a natural point of leverage in that it can offer this service to its existing base of satisfied directory users. But in another twist I find both significant and smart, Trucker Path is embracing freight brokers, not trying to disintermediate them. Rather than embracing the standard tech playbook of trying to blow up an inefficient industry in order to carve out a position, Trucker Path is simply trying to graft a new layer of efficiency onto an existing market. I would argue they’re trading a bit of potential upside for a radically increased chance of success.

Trucker Path does some other tried and true things such as providing credit, insurance and license data to its marketplace participants, a tested way to increase both value and trust.

Trucker Path is a case study for my long-held view that B2B data publishers in market verticals are well positioned to consider the marketplace model. They’ve got a brand, they’ve got the audience, and they know how to use data (e.g., license and credit information) to create the trusted environment that is essential to driving transaction volume. And despite their noisy collapse after the dot com bust (too much, too soon),  I am very optimistic about the future of B2B exchanges. We all now recognize the value of workflow integration: if you’re enabling the flow of work for an entire industry, you’re obviously in a very good place.