The Evolution of Personalized Search

Search Engines are in a race toward demystifying the most important user data to provide the most relevant search results. Google has even revealed its desire to build a search engine so personalized that it resembles the ‘Star Trek Computer.’ For you non-Trekkie’s out there, this computer analyzes mass amounts of data in order to answer any question with one response and upon voice activation.

While it is not clear if all engines share this vision, it is clear that each is working toward a more relevant and data driven personalized search experience. As a result, the engines have created a space that is constantly changing in terms of physical layout and search results. In this article we will discuss what type of search personalization exists today, and what this means for brands.

Personalization through Semantic Search

According to Wikipedia, Semantic Search:

Seeks to improve search accuracy by understanding searcher intent and the contextual meaning of terms as they appear in the searchable dataspace, whether on the Web or within a closed system, to generate more relevant results.”

Bing does this by testing the order of the results displayed for each search. Google does this by proactively “assuming” what you’re looking for to provide organic cards that display useful information about that interest within the SERPs. These assumptions, however, are based upon aggregated and real activities, like previous searches, physical location, emails, calendars ... the habitual things people use every day. These habits, and changes in them, continue to drive search engine optimization.

Semantic Search and the Knowledge Graph

The quest to provide the most relevant results for searchers has driven a lot of innovation in search engines. Since 2011, semantic search has driven many major changes in the layout of each engine’s results. For example, Google shows this data in what they call the Knowledge Graph, which has numerous ways of appearing on SERPs for different types of searches.

User Online History

For example, when shopping for “engagement rings” Google pulls in two types of search results – navigational (the shopping block) and research (the Knowledge Graph in the right rail). Assumingly based upon user habits within this user’s result, Google will learn whether the query “engagement rings” is more navigational or research related.

Localization

Another common example can be seen through localized searches for brick and mortar establishments. With the rapid user adoption and use of smartphones, search engines can incorporate location features to determine the most relevant results possible. Those results will be very different for a family driving down the highway at night and a business traveler whose flight just got canceled. So, a search like “Hotel” can have two distinctly different meanings based upon each searcher’s location.

Customer Service

Sometimes these changes show an error in online brand information and the way that google pulls in this data. Recently, Google tested the addition of brand phone numbers on queries that indicated a desire to place a phone call. Once implemented, many brands realized that the phone numbers Google pulled in were not the most accurate or relevant.

The Next Phase in Personalized Search: Google Now!

Because smartphone adoption is growing faster then any other technology in history, Google specifically is putting a major focus on semantic search in mobile. The result is Google’s mobile app: Google Now!, which was released in July 2013. It predicts what a searcher’s next search will be based upon all of those identified personalized components and habits.

Google Now! pulls in data from numerous sources, including much from its own properties like Gmail, Gcal, YouTube and Search. It also uses structured data like the Schema.org microformats to provide searchers with nearby attractions, food, and points of interest in “cards” that appear within the app.

What to Take Away

Online brand data will continue to be incorporated into the Knowledge Graph, Google Now! and other Google technologies. We also expect to see Bing and Yahoo! test into new personalized SERP features. Businesses can take advantage of personalized search today and prepare for more changes tomorrow with some quick digital health checks. 

Think Globally, Act Locally

A company that relies on location based information – like hotels, restaurants, and brick & mortar shops – will want to ensure their NAP is accurate across all of their assets. One of Google’s latest layouts, for both mobile & desktop, includes a scrolling Knowledge Graph across the top of the results called a Carousel. This placement pushes down both Paid & Organic listings. An extensive study was conducted by Digital Marketing Works which suggests quality & quantity of Google Ratings along with physical location to a user’s search are the top influencers of knowledge graph order.

Make sure you have a single page dedicated to your contact information. If you have multiple locations, create multiple pages serving unique content for each location’s page. Ensure all contact information is in HTML code on every page of the site.

Localized links on local anchor text will help boost your brand for other renderings of local search results. Offer your business as a local book club meeting spot, reach out to event planners to inform them of your services, and make sure you’ve added yourself to the city’s BBB or Business Directory listings. Don’t forget about all those social sites you’re engaged on, you’ll want to build links from those URLs as well.

Cross-Reference Your Records

Review your Wikipedia listing and make sure your information is accurate. Many areas of the Knowledge Graph are populated with references from Wikipedia.org. Also, Google’s Freebase.com contains much of the data that is referenced by the Knowledge Graph. Make sure your basic information matches your “Contact Us” page and that there is at least one link cited for your website. Additional audits of your listing will help, but Wikipedia Editors are notorious for spotting & removing keyword-stuffed listings, so keep it simple & factual.

It’s Really Personal Now

Businesses can already take advantage of “predictive search” technology with microformats, like Schema.org. For example, a hotel chain should incorporate microformats on their NAP, Check In Time, and Check In Date in their reservation confirmation emails that target Gmail users. Google Now! picks this up and uses it to populate their “cards” within the app. Having those reminders coded with microformats helps the engines understand the information, which helps brands get included in these new technologies.

Focus on engaging with fans and followers across social networks. Google+ has built a strong correlation to ranking search results. Interactions by Google+ users follow basic organic search best practices – primarily by building network links using keyword rich anchor text. For example, Google+ users can leave comments for YouTube videos, which pull your video & the comment over to their Google+ page. Your YouTube video name now acts as anchor text for your video page. Additionally, Google has incorporated Google+ business reviews in Google Search Ads, providing the user’s Google+ image & review as text for your ad. 

What’s Next

Searchers will continue to adopt new technologies and purchase habits, requiring Search Engines to also change their approach. We have already seen search evolve, and we continue to see the Engines hire the brightest developers to create the best search results. Make sure your business is also hiring the best and the brightest marketing teams and partners that can help you and your web based content stay agile. A nimble marketing team or partner is vital, because if one thing is certain, it is that change is inevitable.

Join the Discussion