Mobile search has never been just one result type. It provides different results and presentation formats, depending on whether the search query is from a feature phone, smartphone or tablet.
Google has just announced a specially designated crawler for smartphones apart from what it uses currently for feature phones, which foreshadows a deeper divergence of results between the two mobile types, as well as from desktop results.
Until recently, the results for the different mobile types has been assumed to be the same as those for the desktop or simply just more Google local results. However, data and research findings detailed in a Covario whitepaper on Mobile Search validate that there is much more happening with search on mobile platforms.
How Does Google Differentiate Between A Feature Phone & Smartphone?
In a search engine’s view, the difference between feature phones and smartphones, other than an ever expanding list of devices, is that smartphones have a WebKit browser. This WebKit browser is always declared in a smartphone’s user agent. It is also why BlackBerry devices before BlackBerry 6 OS, when the WebKit browser was introduced, are provided feature phone results.
Why Would Google Do This?
Google’s number one rule is “Focus on the user and all else will follow.” As such, Google wants to be sure the resulting pages render properly on the user’s device and provides results based on the user’s search intent.
How Would Search Results Be Different On These Mobile Devices?
The intention of inputting a search term on a desktop, feature phone, smartphone, or tablet can mean different things for the same keyword. For example, when typing in the term “tacos” on a desktop I may want information or recipes; but on a feature phone, I may want to call a local taco shop; on a smartphone, I want directions to a local taco place, and on a tablet, I want to check reviews or what different items on the menu look like.
How Will Google Rank This Accordingly?
Google already provides the greatest divergence of search results for feature phones via Googlebot-Mobile by specifically crawling for those devices. Google wrote that your pages may be filtered from those results if it doesn’t render properly and declares the proper mobile DocType. This will be Google’s approach with smartphones and ultimately tablets as well.
What Will Be The Different Mobile Search Ranking Factors In 2012?
Standard inbound text links will be marginalized as a ranking factor for the different mobile search types as popularity will be determined more by sharing, such as through Google +, rendering via crawlers/headless browsers, and usability data from all those Android users.
Standard SEO ranking elements will be gathered by the desktop version of that page, especially if the mobile page is on the same URL as the desktop page.
How Can I Best Prepare My Site For Mobile Search In 2012?
Enable user agent detection to trigger a mobile type CSS on the same URL as your desktop pages if you can have a 1 to 1 relationship for the purposes of consolidating link juice in the current search environment.
If your mobile site will be smaller than your desktop site, using an m. subdomain is the next best option for both smartphone and feature phone results. These mobile results should be on the same m. URL, but triggering a different mobile type CSS based on the user agent.
When triggering the mobile type CSS it should also include the correct mobile format DocType.
Load time should be minimized not just via page size but in network/http requests, as well increasing compression and cache-control when possible.
Use semantic coding with microformats, especially address location tagging, and the formats used in HTML5.
Improve rendering and user experience by providing an app like experience with HTML5 and jQuery.
I foresee in 2012 Google pushing us more into the Mobile Semantic Web 3.0 and having a Googlebot specific for tablet rendering and perhaps even one for TV based on the acceptance of Google TV and a fully Web integrated Apple TV. These bots will provide new segments of search types for which to optimize sites for, especially as this semantic Web better prepares for inferred searches via voice.