What Can Online Directories Learn From the Yellow Pages?
The scene outside my home on a recent evening was straight out of a nostalgic, sepia-tinged movie. My six-year-old daughter spied a squarish object in a bright plastic bag as we pulled into the driveway. We parked and she jumped from the car. “Dad, what’s this? It’s some kind of yellow book.” I explained that the telephone company had left us a copy of the yellow pages. She looked up at me, innocent and curious. “Dad, what are the yellow pages?”
Though they may be an object of nostalgia, the yellow pages have hardly been missed. Indeed, they’ve been cast aside with nary a backward glance (though certainly not by everyone), and are two or perhaps three evolutionary steps behind us at this point. With Google now reporting that as much as 50% of mobile search is local, the time is upon us when even looking up a business on one’s trusty laptop will seem a relic of the last decade.
Surely, we’re better off with digital search, by and large. We certainly assume that we are, and probably do not spend much time questioning that assumption. Yet the old media endured for a reason, beyond the fact that no one had yet dreamed up something better. From 1886, when Reuben H. Donnelly printed the first official yellow pages book, until somewhere around 2007, the yellow pages saw not only continued usage but steady and predictable growth in revenue. In fact, the evidence suggests that especially in smaller markets and among the older population, usage of the print yellow pages remains strong.
As a technology, books have a lot to going for them. They organize information into logical hierarchies with indexes and headings that make lookups and cross-referencing easy. Flipping through pages lets you discover content you wouldn’t have thought to type into a search box. And given a limited data set, such as all of the businesses in a moderately sized community, it’s arguably far easier for a locally sourced and curated publication, working on a longer and more painstaking update cycle and staffed by editors familiar with the community, to produce a directory that offers a complete record of local businesses.
In fact, the very search query that stymied me in a recent post on the shallowness of local search data — “Which local landscapers provide lawn aeration services?” — was answered in two minutes of searching through the phone book. The Lawn Maintenance heading contains an ad from a local company called Turfmasters Inc., and “lawn aeration” is proudly displayed in the list of services. Score one for the dinosaur.
Like a lot of things about the Internet, it’s a question of scale. We’ve come to expect that massive amounts of data must be sliced and diced by sophisticated algorithms in order to tell us how far it is to Starbucks or whether there’s a dry cleaner open on Sunday. Put that way it sounds a little absurd, but when we think of data on a worldwide scale as the search companies do, clearly the algorithmic approach is the correct one. The laudable efforts of data aggregators to build and maintain accurate databases, as well as Google’s large-scale approach for processing a constant stream of real world inputs from users and staffers and the comparably global operations of other search and mapping providers, has produced a corpus of local search data that works remarkably well, generally speaking, across the hyperlocal landscape.
But when the global approach to local data fails, it fails in some pretty obvious ways, and I’m not just talking about Apple Maps. My post on service-oriented businesses, for instance, covered some of the very noticeable gaps in Google’s coverage for that sector. In the yellow pages book I’m perusing, of the sixteen local listings under Lawn Maintenance, only three carry a street address; compared with the Google results I analyzed in the earlier post, I have to assume this is a far more accurate representation of businesses that either do or do not have a location for customers to visit.
Of course I’m not advocating a return to the phone book, but I am curious about the lesson it might have to teach us. In particular, the notion of restricted and curated data sets may be worth a revisit. Without foregoing the benefits of scalability, search sites could do more to enable the curation of local data by business owners and other members of local communities. Google’s crowdsourcing approach (via entry points like Mapmaker) has no particular community focus, so doesn’t quite get at what I have in mind. Facebook carries a great deal of information about what people and organizations belong to what communities, but seems uninterested for the time being in leveraging those latent networks to build better local experiences. Given the level of built-in engagement, either one of those companies could create community networks quickly if they saw the benefit.
Local media outlets who already act as voices of their communities are also well positioned to help source local content, and would benefit greatly from the support of a strong organizing body and technology provider such as Google or Facebook. Then there are the applications that derive data today primarily through crowdsourcing, such as Open Street Map, or the granddaddy of them all, Wikipedia, which already plays a demonstrably significant (if little-known) role in local search rankings.
Whether a lateral move or the introduction of a new local level of organization within nationwide and global networks, the opportunity is there to build better local services that are more attuned to the communities they serve. For the moment I’m talking about local search, but there are surely more altruistic benefits to be had as well.
Damian Rollison has served as VP of Product for Universal Business Listing since 2010. He holds degrees in English from the University of California, Berkeley, and the University of Virginia, where he did graduate work at the Institute for Advanced Technology in the Humanities. Damian’s articles on emerging technology have also appeared in Venture Beat.