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!

Is Faster Better?

When it comes to information, is faster always better? As information users, we all want to have the freshest possible information possible on which to base our decisions. But, as many data publishers have learned the hard way, while everyone wants up-to-the-second accuracy and currency in their data, not everyone is willing to pay for it. Indeed, we’ve noted with concern the growing trend towards “good enough data,” where users are willing to sacrifice some amount of accuracy and currency in favor of a significantly reduced price. So, on a practical basis, a data publisher could be excused for concluding that the most accurate and current data shouldn’t be a top priority.

Things, however, are a bit more complicated than that. The speed of information updates does matter, a lot, in specific applications and markets and people in those markets will happily pay a stiff premium to get hold of such data. The obvious place to look for proof of this is the world of finance. If you have information that can move the price of a stock or the entire market, speed matters. Consider that Thomson Reuters used to charge a premium for those who wanted access to an important consumer sentiment survey just two seconds before everyone else.

There are more mundane examples of this in non-financial markets. Consider sales leads. While every second may not matter when it comes to sales leads, there is added value in delivering them quickly, particularly if based on a real-time assessment of a prospect’s online browsing pattern.

Given all this, it would seem that a new service called Now-Cast Data has a winner on its hands. That’s because the company, run by economists, is preparing to offer a real-time economic forecasting service. Real-time delivery is actually something of a breakthrough in the world of economic forecasting, which is used to monthly, quarterly and even annual reporting. Clearly, by accelerating forecasting, the financial types will gain an information advantage for which they will pay handsomely. Or so it would seem.

But as an article in the Wall Street Journal notes, Now-Cast Data has some convincing to do. The core issue is that while Now-Data is certainly accelerating forecasting, at the end of the day, it is still offering forecasts. It can’t be sure what will or won’t happen, or whether specific events (e.g., inflation) will persist. As an economist in the article notes, “When a big outside event disrupts the economy, those are hard things to forecast. By definition you can’t build them into your forecasting model because they haven’t happened yet.” In short, we’re guessing faster, but we’re still guessing.

So where do I come out on speed? Is faster data always better? At least for now, I don’t think it is. Right now, it’s only really valuable in a specific, limited set of applications. Keep in mind too that we’re already drowning most of our customers in data. Getting the fire hose to pump faster just makes things more unmanageable for them. And speed is a relative concept as well. If a company changes its address, that’s a valuable, time-sensitive piece of actionable information. But if you already pass that information to your customers the same day you learn about it – say 8 hours at most – accelerating that to 8 minutes won’t improve either customer sales results or your bottom line. As data publishers, we want to be continually looking for ways to obtain and move information faster, but speed is something that’s ultimately defined by your customers and your competitors.

LinkedIn's New Corporate Directory

In my view, the future of LinkedIn depends on finding ways to get itself inside of business workflow – the essence of infocommerce – because the history of databases that remained standalone reference products is a sad one.

LinkedIn’s first big push to build ongoing user engagement was to add user-generated content, lots of it, creating a B2B Facebook if you will. This is certainly a valid approach, but with the Internet already groaning under the weight of endless content, much of it free, this is a tough road. I think workflow integration is a lot easier and ultimately much stickier. It is, fundamentally, the difference between logging into LinkedIn to “stay current” or perhaps find a useful morsel of information through sheer serendipity, and logging into LinkedIn because you need it to do your job.

Well, LinkedIn took a small but important move in the direction of workflow this week with the launch of LinkedIn Lookup. Very simply, this new app allows you to turn LinkedIn into an internal company directory.

As you can imagine, if you were to filter all LinkedIn profiles by current employer, you would essentially get an internal company directory. And it would be better than almost any company directory that exists given the depth of its profiles and the high level of data accuracy. But the new LinkedIn app does more than just filter listings, it also prioritizes fellow employee listings over your own connections so you’re really using it as an internal directory. Corporate email addresses are shown as well.

Overall, LinkedIn Lookup is a fairly weak version 1.0 app. But if LinkedIn sticks with it, it could take this product in some very interesting directions. Consider:

·        Setting up the product with a corporate administrator could help make listings more accurate (many people don’t update their employer information if they are not immediately going to a new job). In addition, LinkedIn could make this administrator the point person to maintain the company web page as well, helping to insure deeper and more accurate data

·        With listings now used for employment purposes, employees will be more diligent in maintaining their listings to the benefit of both the company and LinkedIn

·        By letting employees see all the connections of other employees, an extremely powerful networking tool along the lines of those offered by Reachable can be offered.

·        Non-public fields could be made available for corporate directory purposes such as reporting relationships, and this could in turn enable real-time organizational charts

·        The product could offer links to a company’s payroll system (as many internal company directories already do), to help insure even higher levels of accuracy

And that’s just a starting list. Indeed, an enormously powerful product platform exists for LinkedIn to exploit with only some additional programming effort. And this product, properly evolved, is certainly one LinkedIn could charge for. No company wants to maintain its own internal directory if it can avoid doing so, and LinkedIn would bring to the table features and functionality no company could duplicate on its own because of its connections data.

Best of all, as companies adopt LinkedIn as their internal directory platform, LinkedIn automatically becomes a stronger database as a result. Employees who haven’t yet built a profile will do so; and those with existing profiles will be motivated if not required to keep them current.

Sure, there are some data governance issues that will need to be addressed and doubtless some technological and structural bumps in the road will emerge; as the saying goes, “hierarchies are hell.” But these issues will come to the fore because LinkedIn is simultaneously becoming more important and the end result of that is a more comprehensive and accurate database for LinkedIn, that will give it the basis to chase even more data-driven workflow opportunities.

If LinkedIn wants to offer high quality user-maintained data that gets accessed frequently, there’s no better way than to help it enable daily business activities. LinkedIn Lookup can be an important first start in this direction.

How Do You Rate?

Morningstar, the financial information giant, today announced that it will be licensing a ratings system from Sustainalytics, a Dutch company that assesses and rates public companies along three dimensions: environmental and social responsibility and governance. Morningstar will adapt this methodology and apply it to mutual funds.

Why the rush by Morningstar to add still more ratings to its data platform? And why license a ratings system when Morningstar already has demonstrated expertise in this area? Indeed, Morningstar has been rating mutual funds on their stewardship (akin to governance) for a number of years now.

The answer, in a word, is that ratings systems are hot. While they don’t look like much on the surface, they offer to users what they most want today: fast answers. You could even go so far as to say that the other reason ratings system are so popular is that they do the research – if not the thinking – for you.

Most importantly of all from a data perspective, a ratings system provides a consistent, normalized and sortable data point. This is especially valuable in the investment world, which is in the business of finding needles in haystacks. Ratings systems and other filters significantly streamline this process.

Imagine if someone asked to you identify the ten best restaurants in Dallas. Without Yelp and Zagat and the other existing restaurant rating services, this would be a nearly impossible task, particularly if you were looking for a comprehensive and objective answer. But these services in effect conduct mass-scale surveys, asking people to condense their opinions of restaurants into a predefined ratings scale. This user-generated approach to ratings has all sorts of imperfections, but most people believe that with enough people participating, the truth will present itself.

A step up from these open surveys are the professionally administered ratings systems. These distinguish themselves by identifying and rating companies against a fixed set of criteria. The goal of the exercise is to be objective as possible. That’s why data are used in place of opinions whenever possible. The more rigorous the system, the more valuable it tends to be. That’s because in addition to being normalized and consistent, these ratings systems allow you to make dependable comparisons. Companies rated “A,” for example, are all rated that way because they met a certain specified set of criteria. That means you can place more trust in the ratings system.

Interestingly, most ratings systems happily publish their underlying criteria and ratings methodologies. While this might seem to be their highly proprietary “secret sauce,” the reality is that nobody wants to undertake the same laborious ratings work if somebody else has done it, and publicizing the underlying methodology builds credibility and trust. In fact, the underlying methodology of most professional rating systems is central to their marketing efforts.

Rating systems reflect the fundamental shift we are seeing from data publishers selling vast piles of raw data to high value, more analytical datasets. The next opportunity is to actually do the analysis for them.

You can learn more about how publishers are using their data to produce a wide range of high value products at this year's Business Information and Media Summit. Hope to see you there!

How Zillow Spends Zero on Advertising

Doubtless everyone reading this is familiar with Zillow. We honored them as a Model of Excellence in 2006 .

They’re now a real estate listing behemoth that sports a market capitalization of $5 billion. We all know what Zillow does and how successful it’s been. But did you know that Zillow launched with virtually no advertising budget?

In a fascinating interview, Zillow’s Chief Marketing Officer, Amy Bohutinsky, explains Zillow launched with the classic “sell data with data” strategy. Using data to promote your data is – unsurprisingly – a marketing tactic available only to data publishers. And it’s a tactic well worth exploiting to the maximum.

Zillow launched itself with press releases aimed at the consumer mass market. It offered free access to data that was catnip to almost every consumer: instantly find the estimated value or your home, or anyone else’s for that matter. Zillow, after collecting and normalizing property assessment records from all 50 states, had developed an algorithm that looked at recent sales and area demographic data to calculate a home price valuation. Sure, it was necessarily imperfect, but the data was credible if not authoritative, comparable (all homes were evaluated the same way) and of course free. This quickly drove millions of page views, allowing Zillow to execute on its business model of selling listing enhancement to real estate agents.

But Zillow didn’t stop with this single gambit. Instead, it allowed consumers to sign up to receive email updates to their home valuation – every time the estimate changed, Zillow would send an email. This created critical ongoing engagement (important because the average person doesn’t buy or sell a home all that frequently), brand enhancement, and an important advertising vehicle (the email also presented information on nearby homes for sale).

Beyond this, Zillow regularly mines its own data to find newsworthy statistics that keep its brand front-of-mind and implicitly credential it as an authoritative and central industry player. It issues press releases on everything from the standard reports on where homes are selling most quickly and slowly, to offbeat data on the “10 biggest homes” or “10 most expensive homes,” and the like. Obviously there’s no shortage of material.

As we noted earlier, you’re most likely to get media coverage if you can provide facts and statistics. That’s hard news as opposed to opinions or transparent gimmicks to try to attract attention. More importantly, every piece of data you release reinforces your central market position, your authority, your knowledge and your expertise. You become generally understood to be the “go to” place for data in your market. There’s no better positioning than that, and best of all if you do it right, it’s practically free.

You can hear how another Model of Excellence winner, Capterra,  pulls of this trick when its CEO Mike Ortner joins us for our infamous “Excellence Revisited” panel at this year’s Business Information and Media Summit. Hope to see you there.