Solving “Local” Challenges: Combating Bulk Calls
If you a) believe in the power of search—as a technology, as a consumer experience and as a business model, and b) believe in the economic promise of the “local” opportunity, then you need to commit to a simple axiom: the ultimate destiny of a local search is a phone call. Two relatively new macro […]
If you a) believe in the power of search—as a technology, as a consumer experience and as a business model, and b) believe in the economic promise of the “local” opportunity, then you need to commit to a simple axiom: the ultimate destiny of a local search is a phone call.
Two relatively new macro trends have converged on the phone. First, as everyone’s data will attest, web searches are increasingly local in nature, focusing on discovery of products and services offered in the physical world. The second is the migration of a very large small and medium business marketing spend from antiquated offline models (the phone book) to performance-based online vehicles (search, etc.). But while consumer behavior has changed (using search and social media instead of the book), nothing has changed the fact that the great majority of local businesses—whether the sole-operator plumber or a national advertiser like Roto-Rooter—still consider phone calls to be the lifeblood of their business.
To sweeten the deal, for many of these businesses, the phone call is much closer to what they consider the “transaction.” And as we already know from operating an active pay-for-call exchange, phone calls in aggregate convert at 3-10x the rate of clicks.
After a half-decade of connecting, tracking and analyzing hundreds of millions of phone calls, most generated from online marketing activities, we know that one of the key challenges our customers face is preventing fraudulent calls. In the search world, giants like Google and Bing have invested heavily in their ability to detect, understand and scrub fraudulent click activity. But in the calls world, we’re still at the beginning of a long learning period.
Unlike fraudulent clicks, which merely skew tracking data and cost calculation and which can often be backed out of totals for a marketer, phone calls that don’t come from customers have a serious side effect: tying up the line and blocking calls from live customers and leads. And much like the conventional wisdom from the web, a dropped call results in the same outcome as an abandoned visit: a lost customer.
Since the 2003 advent of the National Do Not Call Registry in the U.S. enabled an estimated 150 million consumers to block telemarketing calls, bulk dialers have turned to targeting business lines with B2B offers. And with the explosion of web-based activity focused on finding local businesses, those local business numbers are easier and easier to crawl, scrape and aggregate.
For some of our largest customers, the problem reached a critical point not long ago. Our response—which is half research and half product feature—was to deploy a “honeypot” (a pool of hundreds of thousands of inactive numbers) to detect bulk-dialing activity. When we detect and confirm patterns of repeat call activity across multiple calls, we can calculate the likelihood of telemarketing activity and block the origin. Over time, the system learns more and more about bad behavior and self-corrects for false positives. And because we’re using a dedicated, ever-shifting honeypot, we can learn without affecting actual customers.
While we have thus far been very successful at identifying and blocking hundreds of thousands of fraudulent calls, we’re just at the beginning of the learning process. And given the axiom I laid out above and some of what we see on a daily basis, making good on the promise of “local” is going to mean—for all of us in the industry—beginning to identify, understand and creatively solve the challenges that stand in the way of delivering phone based leads to local businesses.
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