One of the most interesting slides in my four sessions at SMX West yesterday was presented by Microsoft’s Raj Kapoor on the mobile search session. These data are from 2008 and based on an internal Microsoft analysis:
What the chart above appears to reflect is the contrast between explicit query distribution and user intent. It reflects roughly 70% of “measured” mobile queries were for entertainment, news and general Web search. It shows about 25% of queries seeking local information and about 5% looking for “shopping info.”
By contrast the self-reported “session intent” breakdown data is different. General Web queries fall to 23% and local information rises to 62%. If we include “shopping info,” which is ultimately about physical places to buy things, that combined figure rises to 87%.
I didn’t discuss this slide with Kapoor so I might be misinterpreting it. At a minimum it means that consumers are more interested in local categories of information than it appears on the surface. The larger point is that what the search engine sees is often different than what people want and intend. Indeed, the search engine also doesn’t capture behavior (what people do after their research).
The search engine sees a meaningful but relatively smaller number of mobile queries for local information. The users report a much larger percentage of local intent queries.
The problem and challenge in quantifying local search has always been in the difference between the “explicit” and “implicit” local queries, as well as capturing subsequent behavior (which reveals intent). This recognition led Google to start showing maps and local results for queries without a geomodifier, recognizing that there are lots of queries that are ultimately local where the modifier is included.
Most of what happens online and certainly much of what happens on mobile devices, when commercial queries are involved, is about offline buying. The challenge has been to measure and make this phenomenon more transparent.
Amazingly, most analysts and marketers still don’t clearly see or understand the behavior. But this online-offline pattern is much much bigger than e-commerce and, frankly, anything else going on online.