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Standard Stuff Is Actually Cool

In the not-too-distant past, there was something close to an agreed-upon standard for the user interface for software applications. Promoted by Microsoft, it is the reason that so much software still adheres to conventions such as a “file” menu in the upper left corner of the screen.

The reason Microsoft promoted this open standard is that it saw clear benefit in bringing order out of chaos. If most software functioned in largely the same way, users could become comfortable with new software faster, meaning greater productivity, reduced training time and associated cost, and greater overall levels of satisfaction.

Back up a bit more and you can see that the World Wide Web itself represented a standard – it provides one path to access all websites that function in all critical respects in the same way. Before that, companies with online offerings had varying login conventions, different communications networks, and totally proprietary software that looked like nobody else’s software. Costs were high, learning curves were steep and user satisfaction was low.

There are clear benefits to adhering to high-level user interface standards, even ones that bubble up out of nowhere to become de facto standards. Consider the term “grayed out.” By virtue of this de facto user standard, users learned that website features and functions that were “grayed out” were inaccessible to them, either because the user hadn’t paid for them, or because they weren’t relevant to what the user was currently doing within the application. Having a common understanding of what “grayed out” meant was important to many data publishers because it was a key part of the upsell strategy.

That’s why I am so disappointed to see the erosion of these standards. On many websites and mobile apps now, a “grayed out” tab now represents the active tab the user is working in, not an unavailable tab. And virtually all other standards have evaporated as designers have been allowed to favor “pretty” and “cool” over functional and intuitive. I could go on for days about software developers who similarly run amok, employing all kinds of functionality mostly because it is new and with absolutely no consideration for the user experience. What we are doing is reverting to the balkanized state of applications software before the World Wide Web.

And while I call out designers and developers, the fault really lies with the product managers who favor speed above all, or who themselves start to believe that “cutting edge” somehow confers prestige or competitive advantage. Who’s getting left out the conversation? The end-user customer. What does the customer want? At a basic level the answer is simple: a clean, intuitive interface that allows them to access data and get answers as quickly and painlessly as possible. Standard stuff, and the best reason that being different for the sake of being different isn’t in your best interest.

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The Low Hanging Fruit Hiding in Plain Sight

One of the unintended consequences of the rapid shift to sales force automation tools, CRM systems and large-scale lead generation campaigns is that things only work well when you target prospects and they respond to your promotions. It’s an outbound world now. Pity the poor prospect who unprompted calls you to buy something!

I have recently been in that position, having to make sales inquiries to data companies on behalf of clients. At first, I simply bemoaned the quality of salespeople these days. But then I realized it wasn’t the salespeople who were the problem; it was me! None of these companies had put any thought into how to handle an unsolicited lead, probably because they assumed it was a non-issue. But it’s a big issue. I consistently fell through the cracks because none of these companies had made any provision to deal with me. I didn’t fit their workflow.

The first thing you learn about being a buyer in this situation is that you better not be in a hurry. Callbacks to unsolicited leads in my recent experiences ranged from two to four days. And when I did get a response, it was often by a screener, charged with determining if my business was worth a salesperson’s time. Indeed, after being screened by one major data provider, I received a surprisingly curt email informing me that the size of my potential order didn’t merit their attention, but that my name had been passed along to one of their distributors, and I would hear from them in due course. I’m still waiting after three weeks.

I’ve also learned that using the phone doesn’t accelerate the buying process at all. In fact, it makes things worse. Two of the data companies I contacted had automated attendants that would helpfully connect me … but only if I already knew who I wanted to talk to. In one case, I actually reached a live person who answered the company’s main number. When I asked to speak to someone in Sales, I got the response I hear nearly 100% of the time: there are no salespeople in the office. When I asked to leave a message for someone in Sales, I got a long pause, followed by a very hesitant and somewhat dubious “sure, if you really want to.” One receptionist actually made the mistake of connecting me to someone in the sales department. I say “mistake” because the person answering the phone said he “wasn’t allowed to talk to me,” but he’d have someone call me back. When I said I needed some basic product information first, he did in fact provide it, after swearing me to secrecy because “I could get in a lot of trouble for doing this.”

Since companies have clearly abandoned the telephone as means of inbound contact, you think they would pay close attention to incoming leads by email. If only that was true! After submitting my sales inquiries to three companies via the ever popular “contact us” form, proving that I was not a robot, and in some cases being asked the size of my budget (required field), I sat back and waited. And then waited some more. One company responded fairly quickly, but the salesperson was apparently so incredulous that a sales lead would be unsolicited that I had to submit to a grilling via email to confirm my interest and my bona fides.

The second company responded three days later, and apologetically asked for lots of information about my product requirements and me so that he could “get me in the system.” Once properly in the company’s lead stream, I had a satisfactory buying experience.

The third company? Three weeks and I am still waiting on a response.

You surely know where I am going with this: with so much technology and so many resources being devoted to lead cultivation, generation and management, we seem to have forgotten about the most valuable sales lead of all: the unsolicited inquiry. There is apparently no place for them in our automated workflows.

Not your problem? I challenge you: complete the form on your own company’s “contact us” page and sit back and wait, not with a stopwatch but with a calendar. If you want an even more dismal experience, call your own company’s main number and ask to speak to a salesperson. Yeah, it’s that bad ... which means the opportunity for quick increased revenue is that good!

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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. 

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.