See how Google, Yahoo and MSN measure up to the task of connecting a man on a search for illumination.
Driving home last night, I was cut off by a shiny white Porsche Cayenne. Not one to honk my horn, I flashed my high-beams, only to realize that one of the bulbs was out. Instead of showing my toughness with a flash of light, I winked. So today I set out for a new headlight bulb for my BMW, and I thought I’d give the mobile local search applications from Google, MSN and Yahoo a try.
I searched « auto parts » 90046 (my zip code in LA) and called each listing I received. The search results were all very different — and all really bad.
The listings: good, bad and disconnected
Only Google listed my neighborhood auto parts retailer, Autozone, but then gave me nine bad listings (including one wrong number). Yahoo had nine listings on the first screen, and eight were auto parts retailers (no Autozone), but all were inconveniently further away than Autozone. Yahoo’s phone call answer rate was 78 percent, and five out of nine had the bulbs (56 percent) — great scores, but the stores were not in my neighborhood. Lastly, MSN Live Search had 20 listings within 2 miles of my house, but listed no retailers that carried bulbs. Twelve merchants of the 20 answered my call (60 percent), but three had disconnected numbers (15 percent).
I’ll note that there are a few more Autozones, a Kragen and Pep Boys (all national chains) as well as several BMW dealerships in the area. I also live near a Target and Sears. Any of these would have been good sources for auto parts — and are better choices than the results I found from Google, Yahoo or MSN.
What went wrong
At a time of incredible hype over the devices — the iPhone, the Google-backed Android and the BlackBerry Bold — it is easy to forget the fundamental challenge in mobile local search. The problem starts with the base data that every mobile local search property licenses from an aggregator.
For example, Google Maps credits Navteq (now part of Nokia), and in the terms of service (TOS) it credits local data to Acxiom or infoUSA (which is also credited by Yahoo). MSN credits Navteq for maps and Yellowpages.com for sponsored results (I don’t know if MSN uses Yellowpages.com for organic results too, but they credit Localeze and Acxiom for data). Either way, these are the aggregators who too often license out-of-date, and poorly categorized data to the industry.
Why hasn’t a solution been found to deliver a better consumer experience? Surely mobile local search is a high priority at Google, Yahoo and MSN. Recent industry reports from The Kelsey Group and others indicate that the number and variety of searches on mobile phones have jumped in an iPhone-fueled surge this year. Global mobile search revenue is forecasted to reach $3.8 billion by 2012 ($1.4 billion in the U.S.). And JP Morgan estimates the global market for paid search will approach $60 billion by 2011. « It is hard to imagine that mobile search growth won’t track the growth in aggregate paid search, » says John du Pre Gauntt, eMarketer senior analyst and author of the company’s report, Mobile Search: Location, Location, Location.
How to make it right
I suggest that the problem be solved by breaking down the top 50 or so categories and a few hundred neighborhoods to identify the best results for each combination; surely, a search for auto parts in Los Angeles would qualify. I’d note the national chains and retailers like Target, Sears, Walmart — which have products that fit in many categories — as well as other, more specific brands, like BMW.
We see continued activity in local search from companies like Yelp, ReachLocal, MerchantCircle and SpotRunner, each taking a different approach with reviews, search engine marketing, community and local video. My view is that its time to add voice. Google acquired GrandCentral; Microsoft acquired Tellme and Yahoo has voice assets. Why haven’t we seen these assets integrated into their mobile local search products?
With Asterisk (the open-source PBX) and great economics of VoIP, a fairly easy solution to tackle the base merchant listings problem is to call local merchants on the phone to 1) test that the number is in working order and 2) ask the merchant if it will categorize itself.
In directory assistance searches, and in many mobile searches, providers connect consumers by phone to the local merchant. I see a trend in using the record of the connection of each phone call (call length, etc.) and consumer reviews of the call to weight the local listings. We need to identify disconnected numbers, penalize merchants with busy signals and unanswered phones and allow users to rate if the merchant had what they were calling for.
Users should add meta-data to correct a listing (the Rolls Royce repair shop I called from the listing on MSN would be a great example.) It’s a new twist on directory assistance. Over a series of phone calls, the data will begin to identify which merchants are relevant based on a quality of service score. Given the vastnesses of local search (industry estimates peg the number of local businesses between 15-20 million), we need to break this problem down into more manageable parts.
2009 will be another year of innovation in mobile local search. Directory assistance applications as well as mobile applications for the iPhone and Android will push to solve this « last mile to the merchant’s door » problem. The result of these efforts would give consumers the quality of Yahoo’s listings, the favorable geography of MSN and a much better experience.
Until our industry finds a scalable solution to improving the quality and relevance of the base listings, local mobile search will not live up to its promise.