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Passing the Quality Test

You can’t be a successful data publisher unless you’re selling high quality data. It’s not just because customers want value for their money, it’s because they increasingly depend on third-party data for their own business success, so it's a high-stakes decision.

Even if your product has the slickest interface, the most granular and well-structured data and the best integration tools, there is nothing that matters more than the data itself. That’s why data quality is an integral part of your sales pitch. But quality is so easy to claim, and so hard to prove.

Anyone who has ever sold a data product knows that moment of dread when the prospect asks to check its quality by looking up his or her own information. Yes, it’s a way to test quality, but it’s not a good one. To take a single record, one that the prospective customer happens to know more about than almost anyone else in the world, and project the results against a database with thousands if not millions or records, is inherently imprecise. But what’s a buyer of data to do?  

Clearly, a third-party audit of data products would fill an important need. The major circulation audit agencies have taken a stab at it, but with what I would argue are weak methodologies and a lack of commitment to their offerings. Now there’s a brand-new initiative called the Data Quality Labeling Standards program. It’s being pushed by the Data & Marketing Association (formerly the Direct Marketing Association) and has a vision of providing a report card on different datasets akin to the FDA nutrition label on a food product.

While I wish this venture success, the difficulty of the undertaking can’t be underestimated. It starts with the simple but profound question of “what’s a database?” When you look at the range of data-driven products on the market today, that’s a surprisingly difficult question. The discussion gets even more complicated as you look for consistent and comparable measures across wildly varying datasets. Most complex of all are the inherent value judgments that have to be addressed when you discover a particular dataset has, for example, really good revenue data but mediocre contact data. That’s when it becomes clear that a dataset’s quality is in many cases a function of how the data will be put to use.

It may be the biggest conundrum of the data business: quality is everything, yet quality is difficult to assess. Third-party assessments, much as I like them in concept, may just be too difficult to implement. The best answer remains the simplest: if you believe in the quality of your data, let prospective buyers put it to work on a test basis for a week or a month and let the results speak for themselves. 

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Say Yes to Market Neutrality

A few weeks ago, Zillow, one of the leading real estate listing sites, made a surprising announcement: it was going to enter the business of flipping homes, the process of buying a home, fixing it up and quickly reselling it.

This immediately raised two questions in my mind: why and why?

First, good things generally don’t happen when you as a data platform or provider give up your market neutrality. No matter the specifics, you are putting yourself in competition with your customers. That means your customers see you as putting yourself first, which makes them very receptive to taking their business elsewhere.

Second, there’s nothing about this new venture by Zillow that gives it any market advantage. Zillow has no unique insights, no privileged data that others lack. It sees listings only when an agent posts them, so there is no timing advantage. In short, Zillow could have quietly invested in a company that flips homes and nobody would have blinked. But Zillow is integrating this right into its main website. Again, Zillow’s function is real estate discovery. Simply knowing a property is for sale at the same time as everyone else confers no market advantage.

Zillow has a slightly different prism though. It sees this new business as a feature that will differentiate it. Just as eBay went from strictly running auctions to adding a “buy it now” button, Zillow sees itself as adding what is essentially a “sell it now” button on its website. But to appease its advertisers – real estate agents – it plans to pay commissions to agents on every house it buys and sells, eliminating any price advantage it might get from buying directly from the seller. The more Zillow contorts itself to make this new business palatable to real estate agents, the more complicated and less attractive this business opportunity becomes.

Even if this venture is really more about adding some sizzle to drive site traffic than a serious source of new revenue, it’s probably not a good idea. That’s because even the appearance of favoritism or self-dealing can put a real dent in your business. And if this new venture really isn’t about making money, then it’s positioning itself for the worst possible outcome: not making any money while simultaneously confusing/annoying/scaring your advertisers.

Does this mean a data provider or data platform can’t ever consider related sources of revenue? Absolutely not. Had Zillow decided, for example, to get into the mortgage business to streamline the home buying process, it would have been rewarded with more site traffic and happier advertisers – the classic “win-win.”

As a data provider, you should say yes to market neutrality. 

Thinking About Privacy and Data? Good.

We have heard a lot in the past few weeks about the travails of Facebook, as it became widely known that many millions of its user profiles had been,  for lack of a better term, hacked. That in turn brought Facebook’s advertising microtargeting capabilities into focus, creating more widespread privacy concerns.

But does the average data publisher have to worry about privacy? The short answer is yes.

Data publishers, including B2B data publishers, often control a wealth of extremely valuable data. Many data publishers don’t fully appreciate what valuable insights they could glean from their own data. Fortunately, data thieves haven’t figured it out either … yet.

The highest value data in a typical commercial database isn’t the data itself, it’s the information on what users are doing with the data. Knowing, for example, that the head of acquisitions at a public company was doing deep research on another public company, could be extremely valuable to certain people. Knowing that an executive suddenly started looking at job openings could be valuable. Knowing that five venture capital firms in three days had looked up information on a particular start-up could be extremely valuable. You get the idea.

We already sell some types of information about how users interact with data, and we do this with very little thought about how it might blow up in our faces. Other of our data is clearly quite sensitive and we’d never sell it, but what if somebody stole it?

Going back to 2013, Bloomberg came in for tough public scrutiny after it was revealed its reporters had used Bloomberg terminal access data to track an individual in order to write a story. That’s pretty tame compared to the recent Facebook revelations, but it shows there is often tremendous inferential data hiding in the intersection between our databases and how our customers interact with it. Monetize where appropriate. Protect where appropriate. But whatever you do, don't ignore it. 

Get Me a Lawyer!

When you own the domain “lawyer.com” you inherently have a big opportunity. But trying to be a national B2C online lawyer finding service means you need both creativity and deep pockets to cut through the competition.  That’s why it was fun to see the new owners of Lawyer.com choose someone with extensive experience with the law to become their new spokesperson: Lindsey Lohan.

The challenge for lawyer.com is to build and maintain broad, front-of-mind awareness among consumers. The domain name is a great start, and having a memorable spokesperson adds even more marketing firepower. 

Lawyer.com does another smart thing, too, by emphasizing personalized assistance to consumers. While every data provider would prefer that consumers answer their own questions by searching the database, there is a large percentage of the market that can’t or won’t try to find answers themselves. If you are trying to be a “go to” destinations for consumers, you can’t afford to write off this big piece of the market. 

Another interesting tactic is a program called LAWPOINTS, a 1 to 100 scoring system that is not based on consumer ratings as you might expect, but rather on the completeness of the lawyer’s profile. The LAWPOINTS score appears with each lawyer’s profile. While I have some concern that a system like this could be confused for a rating (although the company does clearly explain its function), it does recognize the important key to a buyers’ guide that is so often forgotten: the advertising is the content, and this is an attempt to get lawyers to do the right thing by providing as complete a profile as possible. You can call this hokey, because the LAWPOINTS scores really doesn’t mean anything, but detailed profiles can mean the difference between success and failure, so if it works, go for it!

We’ll see if lawyer.com has more staying power than Lindsey Lohan, but they are off to a promising start. 

Zagat: Down But Not Out?

This week, Google announced that it had sold its Zagat guide business, for which it paid a stunning $151 million in 2011, for “an undisclosed amount” to a company you’ve likely never heard of, The Infatuation.

It’s an ignominious development for the former household name brand, and true pioneer in the data business. Well before the Internet, Zagat had blazed new trails in the area of user-generated content and consumer reviews. Tim and Nina Zagat, the founders, proved to be creative and talented marketers and self-promoters. For many years, the name Zagat was synonymous with restaurant ratings in the United States.

But the Zagat empire was print-based. Moreover, the Zagat business model depended in large part on selling bulk orders to companies with their names and logos on the covers, to be given away as gifts. That made it difficult for Zagat to economically expand its coverage beyond the largest cities, so it never became a truly national data provider. And its attempts to expand into other segments of the hospitality industry where more competition existed, fell flat. But the Zagat brand transcended all these shortcomings.

And it is the brand that Google apparently paid so much to acquire. Everything about the Zagat business was at odds with the Google model and ethos. I trashed the deal at the time.

The irony is that Google couldn’t even find an effective way to leverage the Zagat brand. Fortunately, the $151 million purchase price is a rounding error for Google.

What’s the future of Zagat? I do believe the brand still has some life, and could be resuscitated. There’s a role for well-curated, tightly edited slightly snarky, user-generated content that helps you decide where to eat – especially when coupled with a restaurant booking engine. That’s why I would have been much more excited if Zagat had been acquired by, say, OpenTable.