The birth of local SEO

The origin of local SEO can be traced back to 2003-2005 when search engines tried to provide people with results in their vicinity as well as additional information such as opening times of a store, listings in maps, etc.

Local search results

Local searches trigger search engines to display two types of results on the Search engine results page: local organic results and the ‘Local Pack’. The local organic results include web pages related to the search query with local relevance. These often include directories such as Yelp, Yellow Pages, Facebook etc. The Local Pack displays businesses that have signed up with Google and taken ownership of their ‘Google My Business’ (GMB) listing.

Information displayed in the GMB listing and hence in the Local Pack can come from different sources:

  • The owner of the business. This information can include opening/closing times, description of products or services etc.
  • Information taken from the business’ website
  • User-provided information such as reviews or uploaded photos
  • Information from other sources such as social profiles etc.
  • Structured Data taken from Wikidata and Wikipedia. Data from these sources is part of the information that appears in Google’s Knowledge Panel in the search results.

Depending on the searches, Google can show relevant local results in Google Maps or Search. This is true on both mobile and desktop devices.

Google Maps

Google has added a new Q&A features to Google Maps allowing users to submit questions to owners and allowing these to respond.

Ranking factors

Major search engines have algorithms that determine which local businesses rank in local search. Primary factors that impact a local business’s chance of appearing in local search include proper categorization in business directories, a business’s name, address, and phone number (NAP) being crawlable on the website, and citations (mentions of the local business on other relevant websites like a chamber of commerce website).

In 2016, a study using statistical analysis assessed how and why businesses ranked in the Local Packs and identified positive correlations between local rankings and 100+ ranking factors.Although the study can’t replicate google’s algorithm, it did deliver several interesting findings:

  • Backlinks showed the most important correlation (and also Google’s Toolbar PageRank, suggesting that older links are an advantage because the Toolbar has not been updated in a long time).
  • Sites with more content (hence more keywords) tended to fare better (as expected).
  • Reviews on GMB also were found to strongly correlate with high rankings.
  • Other GMB factors, like the presence of photos and having a verified GMB page with opening hours, showed a positive correlation (with ranking) albeit not as important as reviews.
  • The quality of citations such as a low number of duplicates, consistency and also a fair number of citations, mattered for a business to show in Local Packs. However, within the pack, citations did not influence their ranking: “citations appear to be foundational but not a competitive advantage.”
  • The authors were instead surprised that geotargeting elements (city & state) in the title of the GMB landing page did not have any impact on GMB rankings. Hence the authors suggest using such elements only if it makes sense for usability reasons.
  • The presence of a keyword in the business name was found to be one of the most important factors (explaining the high incidence of spam in the Local Pack).
  • Schema structured data is a ranking factor.

Local ranking according to Google

Prominence, relevance, and distance are the three main criteria Google claims to use in its algorithms to show results that best match a user’s query.

  • Prominence reflects how well-known is a place in the offline world. An important museum or store, for example, will be given more prominence. Google also uses information obtained on the web to assess prominence such as review counts, links, articles.
  • Relevance refers to Google’s algorithms attempt to surface the listings that best match the user’s query.
  • Distance refers to Google’s attempt to return those listings that are the closest the location terms used in a user’s query. If no location term is used then “Google will calculate distance based on what’s known about their location”.

 

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