When Bad Data Is Good Business

The New York Times recently ran a story that describes the inner workings of the tenant online screening business, where companies create background reports for landlords on prospective apartment renters. These are companies that access multiple public databases to aggregate data on a specific individual that the landlord can use to determine whether to rent to that person. The article is a scary take-down of a segment of the data business that decided to compete largely on price, and in the process threw quality out the window.

 This is not a small segment of the data industry. Indeed, it is estimated that there are over 2,000 companies involved in generating both employment background and tenant screening reports, generating over $3.2B annually. Companies in this segment range from a handful of giants to tiny mom-and-pop operators. 

 As the Times article notes, the tenant screening segment of the business is largely unregulated. In the tight market for rental apartments, landlords can afford to be picky and apartments rent quickly, so prospective renters typically will lose an apartment before they can get an erroneous report corrected. And with no central data source and lots of small data vendors, it’s impossible to get erroneous data corrected permanently. 

The Times article pins the problem in large part on the widespread use of wildcard and Soundex name searches designed to search public databases exhaustively. And with lots of players and severe price pressure, most of the reports that are generated are fully automated. In most cases, landlords simply get a pile of whatever material results from these broad searches. In some cases, the data company provides a score or simply a yes/no recommendation to the landlord. Not surprisingly, landlords prefer these summaries to wading through and trying to assess lengthy source documents.

The core problem is that in this corner of the industry, we have the rare occurrence of unsophisticated data producers selling to unsophisticated data users. Initially, these data producers differentiated themselves by trying to tap the greatest number of data sources (terrorist databases, criminal databases, sex offender databases). This strategy tapped out pretty quickly, which is why these companies shifted to selling on price. To do this, they had to automate, meaning they began to sell reports based on broad searches with no human review. There are also a lot of data wholesalers in this business, meaning it is fast and relatively inexpensive to set yourself up as a background screening company.

There is also a more subtle aspect to this business that should interest all data producers. The use of broad wild card searches is ostensibly done because “it’s better to produce a false positive than a false negative.” This sounds like the right approach on the surface, but hiding underneath is an understanding that the key dynamic of this business is a need to deliver “hits,” otherwise known as negative information. This is where the unsophisticated data user comes into play. Landlords evaluate and value their background screening providers based on how frequently they find negative information on an applicant. If landlords don’t see negative information regularly, they begin to question the value of the screening company, and become receptive to overtures from competitors who claim they do more rigorous screening. In other words, the more rigorous your data product, the more you are exposed competitively.

There’s a lesson here: if you create a data product whose purpose is to help users identify problems, you need to deliver problems frequently in order to succeed. This sets up a warped incentive where precision is the enemy of profit. Place this warped incentive in a market with strong downward price pressure, and the result is messy indeed. 

Facebook Stores Come Up Empty

Facebook recently rolled out, to great fanfare, a new offering called Facebook Stores. In brief, it allows businesses with Facebook pages to add e-commerce functionality to those pages. It’s a free service to businesses, because Facebook hopes to profit mightily off transaction fees and additional advertising on its sites. Reportedly, over one million businesses have already signed on to use this new feature.

 It’s a bit difficult to assess the significance of this new offering. This is inarguably a smart, if not particularly inspired move by Facebook to cut itself (as all marketplaces and platforms dream of doing) into the revenue of the businesses on its site. But the value Facebook adds through Facebook Stores isn’t all that large. That’s because, despite its huge base of users, Facebook isn’t doing anything to drive these users to Facebook Stores. Anyone who makes a purchase through Facebook Stores is an existing customer or prospect of the store owner or has been driven there by paid advertising on Facebook. Nor does Facebook offer any classification structure or taxonomy to help its users discover businesses on Facebook. You really need to already know they are there. Indeed, businesses can’t even really use Facebook Stores in place of an ecommerce website because Facebook business pages provide only limited access to non-users of Facebook. In many ways, I feel about Facebook Stores the way I feel about Apple’s App Store: yes, it will make a lot of money, but imagine how much money it could have made had it been done right. 

 For those who are writing breathlessly about Facebook Stores as the dawn of “social commerce,” there is a theme. First, they say, forget about Facebook and focus on its sister company Instagram, where brands can promote new products and users can order them seamlessly. It sounds interesting, but when you pick it apart the same issues arise: you’re spending money with Instagram to build your audience and drive traffic, and then you give a percentage of your revenue to Instagram in exchange for capabilities you already have on your website.

In short, Facebook Stores is a smart move for Facebook. Is it a smart move for small businesses? I remain unconvinced. As the saying goes, “If your business depends on a platform, you don’t have a business.” 

Getting to the Top

It’s very gratifying to me to watch how quickly and successfully the data industry has evolved in its lead generation capabilities over the last two decades. We’ve moved from the legacy print directory model to highly sophisticated, multi-sourced signals and other inferential data to more precisely identify and pre-qualify sales leads. But where do we go from here?

I have long said that the path forward for data publishers is to move up the so-called value pyramid, from poorly differentiated “there’s a pony in there somewhere” lists that characterized the legacy print directory era to today’s evidence-based, high-confidence, highly targeted sales leads. The top of the value pyramid is actually making the sale on behalf of your customer, presumably in exchange for a sizable commission to justify the effort. Many data producers would be thrilled to shift from $100 sales leads to $10,000 commissions. But when you even scratch the surface of this idea, you see large obstacles, not the least of which is trying to scale a business model like this.

 So what’s the next highest level of value? Pre-qualifying leads. In this model, the data producer takes the leads it is generating, and further qualifies them by making direct contact, and asking, for example, “are you actively in the market for a new CNC milling machine?” If the answer is in the affirmative, you have developed information of extremely high value. A number of companies that sell technology sales leads have been doing this for a while.

 Alas, at the present time, this is a market-dependent idea. Technology marketing and sales teams tend to be highly sophisticated when it comes to lead management. But for most markets, as I’ve noted before, marketers are still out primarily looking for lists to load into automated marketing platforms, and most sales teams prefer to trust their instincts and sales prejudices over verified data, meaning great leads end up on the floor and the data producer is told its data wasn’t very good.

 All this suggests to me that for data producers to move further up the value pyramid, a lot of market education is going to be required first, and that will take a lot of time and resources. We’ll get there, but not anytime soon.

You Will NEVER Replace This

Elon Musk is probably best-known as the founder of Tesla. When Elon isn’t re-inventing the automobile, he’s running SpaceX, a company that builds and launches rockets and spacecraft. To keep busy, he also runs The Boring Company that plans to tunnel highways under major cities to relieve traffic congestion (a company that also generated a reported $10 million selling flamethrowers to consumers – yes you read that correctly!). On the more esoteric end of the scale, he also founded Neuralink, a company focused on developing brain-computer interfaces. Love him or hate him, you can’t deny he’s brilliantly innovative.

Many people know that Elon Musk got rich as one of the founders of PayPal. Far fewer know that his initial business success came as the creator of an online yellow pages company called Zip2 way back in 1996. Seeking to partner with print yellow publishers, he and his brother visited a top executive at the largest yellow pages publisher in Canada. After pitching their vision, the executive responded by picking up one of his thickest directories off his desk, throwing it at them and saying, “You ever think you’re going to replace this?”

 Well, 25 years later, we know the answer to that one. Not only did the Internet replace the print yellow pages business, it largely destroyed the legacy yellow pages industry as well. Not surprisingly, the Musk brothers did well when Zip2 was ultimately sold for $300 million.

 But what caused the death of the huge and fabulously profitable yellow pages industry? At the time, a lot of people (including me) thought the Internet would herald a new era of growth for the industry. The answer, in large part, was hubris. 

Almost without exception, the big yellow pages publishers decided the fastest path to online riches was to take their regional products and go national. Overnight, these companies bought national business databases to roll out national yellow pages products. In doing so, they moved from having deep information on all the companies in their region, to having nothing more than name, address and telephone for all companies nationally. They vastly degraded the information value of their products in the belief that advertisers would flock to their doors. That’s critically important, because with yellow pages and buying guides, the advertising is the content.

That leads to the second miscalculation: these publishers all had regional rather than national salesforces. Good as these salespeople were, these publishers didn’t have the capability to sell nationally. This led to the third big miscalculation: the publishers all had regional brands and couldn’t come to grips with the fact that nobody had heard of them outside their regions. Without strong national brands, prospective advertisers yawned at these new national products that seemingly emerged out of nowhere.

Of course, the other big shift is that search engines got better. While still imperfect, in large part you now can find a plumber in your area with a simple search. And businesses flock to advertise on the search engines because with pay-per-click pricing, their advertising spend is now (at least in theory) more efficient.

The key take-away lessons for data publishers? First, a database that is a mile wide and an inch deep isn’t an effective product strategy these days. Far better to know a lot about a specific group than to know a little about everyone. Second, advertising-driven online data businesses are tougher than ever to pull off. Third, when you start believing your own press releases, things never end well. Fourth, when Elon Musk calls, listen before you throw something!

A Good Business in Bad Times

As I write this, the federal government has announced 3.3 million new unemployment claims – and this in just one week. In other words, this could likely represent just the tip of the iceberg. The human toll of the coronavirus is difficult to comprehend, with the toll on businesses not far behind.

In any sudden downturn, it has long been understood that some businesses will always get hit harder and faster than others. The rule of the game in any business downturn is to preserve cash in anticipation of reduced revenue. Consequently, expense reduction becomes the focus. Rightly or wrongly, most companies view advertising and marketing as something that can be suspended for some period of time with little consequence. Other business activities, such as company meetings and events, quickly get postponed. Every company reacts slightly differently, and often in uniquely arbitrary and sometimes ill-advised ways. But the goal is always the same: slow spending as much as possible to conserve cash.

With everyone trying to cuts costs and slow payables at the same time, an adverse ripple effect is created that amplifies the pain. That’s why in widespread business downturns, few businesses are left truly unscathed by the resulting fallout.

Can one ever find safety from events of this magnitude? Probably not, but while few if any businesses will be totally untouched, some business models are clearly stronger than others. 

The information business is inherently one of the stronger industries to be in right now. That’s not because information products are uniformly essential to their customers. We learned during the Great Recession that many information products believed to be “must-have” became “nice-to-have” almost overnight. But the B2B subscription model employed by most information and data publishers adds an important additional level of resiliency.

B2B subscriptions tend to be, in effect, annual or even multi-year contracts. Many are prepaid. Many are difficult to cancel during the contract term. This buys information and data publishers the most important protection of all: time. Time to ride out the storm, for conditions to improve or at least for calmer heads to prevail. Sure, new subscriptions will decline and renewal rates will drop during a downturn, but the bulk of the business will remain relatively safe.

In addition to being contractual and often prepaid, subscriptions to information products typically are not high visibility or so expensive that they capture the early attention of cost-cutters. And for data products in particular, they don’t sit idle during downturns like our current one, because they are just as useful to employees working from home.

Some data products have even a further level of protection because they are embedded into the workflow and systems of their customers. Simply put, it’s too slow, complicated and sometimes even risky to turn them off.

As I said earlier, there are no winners in a global pandemic. But the importance and value of data products, coupled with the strength of the dominant industry business model, will help this industry spring back quickly.

This pandemic is bigger than all of us. But if we all act responsibly, we can minimize severity and duration and get back to business sooner. Stay safe … and stay healthy. We’ll get through this if we all work together!