Logo preload
close Logo

Understanding Local Search: From Schemas to Snippets

October 29, 2015


Nowadays, we use our smartphones to find and evaluate everything from local music venues to hot spots to eat lunch. But how does my search engine know when to serve up a list of sushi restaurants when I’m downtown, but serve up a how-to guide when I’m at my house? And what does it take to appear and stay visible in those local searches? Today, I’m taking you through a tour of the local listings ecosystem, from schemas to search snippets, to show you the several important factors and elements that go into appearing and ranking in local search queries.

The Local Search Landscape

How does Google know I’m looking for sushi restaurants when I’m on my phone downtown, but looking for recipes when searching from my desktop, especially when I use the same search query “sushi”?

Google has gotten much better in identifying the Implicit & Explicit elements that come from a query. The full query Google uses when making a search is not just the keywords used in the request (known as the explicit query), but also the device used, its GPS coordinates, time of day, etc (known as the implicit query).

Explicit and Implict Queries

Using these 2 query elements, Google can determine a person looking for “sushi” at 5pm near downtown St Petersburg would be better served with a list of restaurants in walking distance than a how-to guide to making sashimi. The types of businesses that see a local search snippet are typically brick-and-mortar businesses that serve clients from a location or within a predefined range from the searcher.

The list that pops up when a local search is run is known as the local 6-pack and typically looks like this:

6-pack example

It consists of a list of 4-8 businesses in the area that rank best for the explicit query. Often times, clicking on a link in the 6-pack leads to more information about the business in the Knowledge Graph, on the right hand side of the search page.

What is the Knowledge Graph? The Knowledge Graph is Google’s semantic search engine, which gathers and categorizes data about persons, places, and things in the real world. Google gets this information from scraping websites, noting relationships and keywords shared by pieces of data, and through structured data markup, like Schema.org and RDF-a. These marked up pieces of structured information reveal relationships and properties of a structured entity, which can be used later to provided detailed information to future searchers quickly (more on structured data and entities below).

The Knowledge Graph is filled with information about objects (for example, the movie “Transformers”), its relationships (has director = “Michael Bay”), and its properties (released on = “July 3rd, 2007”) and is shown when a person makes a general query on the topic

Transformers snippet

What do I need to appear in Local Search?

The bare minimum any business has to do to compete in Local Search is building out local listings on GoogleMyBusiness and BingPlaces. This alone will add visibility for people looking for your business. But for those businesses that are in a more competitive landscape, or want to improve their visibility in local search, this is what needs to be done to compete effectively:

  • Build consistent local listings on the big local search platforms (BingPlaces, GoogleMyBusiness)
  • Build consistent local listings on local directory sites (Look below in resources section)
  • Purchase a plan from a 3rd Party local listings aggregator for additional reach or if you have multiple locations (more information below)
  • Continually encourage reviews from happy clients and patrons
  • Add schema.org or other microdata markup to your site to help search engines develop a structured entity with your business NAP Data
  • Continually reach out and find new local sites for local listings and citations

I’ll go over each one of these points in detail below:

Local Listings and Citations

Creating local listings on local directories in your area is a good way to expand your business’s footprint online. A citation is a reference in a local listing that include your NAP data (Name, Address, and Phone Number). Ideally, across the net, you want your citations to be clear and consistent. For example, if you use “Mikey’s Pizza, 100 4th Boulevard” in one listing, yet “Mike’s Pizza, 100 Fourth Blvd” in another, these small inconsistencies may harm your overall visibility, as the search engines may think of these as 2 separate locations. In order to prioritize and maximize the effectiveness of your local listings, you need to know who the power players are in this ecosystem, & some tools to manage your listings at scale.

Local Listing ecosystem


GoogleMyBusiness (formerly Google Places) is the 800 pound gorilla in the local listings ecosystem. Directly providing data to Google Search, Google Maps, as well as hundreds of apps and partners like Waze, making sure your information is correct here is a top priority. Setting up your listing is as simple as visiting the GoogleMyBusiness portal, entering in your NAP data and other useful bits of information (description, pictures, logo, etc), and waiting for a verification postcard or phone call. Data is usually added within a few days, and changes to your data after verification usually take less than a day.


Bing Places is not as large as Google, but its listings reach into Bing, Yahoo, and their various search partners, so make sure your listing is correct here. Bing also accepts spreadsheet imports for businesses that have more than 10 locations, and can verify NAP info with postcards and phone calls, much like Google. To add your local listing to Bing Places, you’ll need a Live login. First, visit Bing Places, add your business info, and clicking the “Verify Now” button. Data usually takes a week to get added, and a few days to a week to get updated after verification.

3rd Party Aggregators

Why bother with an aggregator when most of the local listing sites are free? Well, imagine managing a spreadsheet of 150 local listing sites, with names, passwords, and NAP information, and then having to change one detail on all of them, like the business phone number. You’d be looking at hours or days logging in to each site, verifying the details, and making your changes. Sounds like a nightmare?

Local listing aggregators help distribute your listing quickly through their network of partners, and can insure a consistent citation on all of them. The three best are listed below, and vary due to size, scope and cost.

MozLocalMozLocal is the simplest and cheapest way to get a grip on your local listings. Conduct a quick scan of your business name and zip code, and see how you’re listed across the web. Great tool for diagnosing bad or inaccurate data, and correcting it from one easy portal (rather than dealing with tens of 3rd-party directories)

YextYext is an easy to use local listing aggregator with 50+ sites in its network. Add your citation to all of these sites at once, and manage them all through a easy to use portal that updates your listings within minutes. More expensive than MozLocal, but useful for businesses where hours and availability change frequently.

Localeze – The biggest local listing aggregator, Localeze has over 100 sites it manages local listings for. With a simple interface, and batch processing available, Localeze is best used by businesses with multiple listings or locations, who wish to manage multiple locations from one single interface.

The Importance of Reviews

Reviews are crucial in local search for a number of reasons, and analysis of local listings revolves around 3 important elements: Volume, Velocity, and Average Rating.

Review volume is the overall aggregate number of reviews your business has listed. Those with higher numbers of unique reviews (not from the same person or IP address) is a great indicator that a place is popular and has a steady following. For many local businesses, giving a review card to patrons encouraging them to leave a review on your business is a cheap and easy way to help achieve a nice volume of reviews over time.

Next, review velocity is a measurement of how frequent new reviews come in, and directly informs the search engine that a place is consistently busy or popular, and should receive better visibility. This also identifies bad agents, who might do a big push early on to get a high volume of fake reviews and appear popular. Later on, when no one reviews it for months, the velocity of new reviews drops precipitously, and it looks like a dying business to a search engine, which would harm its search visibility in the long term.

Lastly, average rating is useful as a qualitative metric for search engines, as it seeks to identify the quality of the actual experience. Changes in this metric are crucial, if a business starts receiving a lot of negative feedback, or feedback with bad keywords like “poor quality” and “never coming back”, the search engine will reduce its visibility, to allow higher quality businesses the chance to shine.

By building a review plan to continually ask your best customers and patrons for reviews, you can consistently build your review volume with quality reviews, without resorting to cheap tricks or spam. When it comes to reviews, playing the long game well pays off better than any short term tricks.

Structured Entities

A structured entity is a person, place, or thing wrapped in structured data markup that can be used in semantic search. It’s a way for bots and search engines to understand that particular piece of information has a special meaning and has relationships with other pertinent pieces of data as well.

Structured data provides a way for classifying a piece of information by labeling the constituent parts and identifying the sum as an structured entity with those properties. For example, below is a schema.org markup of a dentist office with a itemtype of “Dentist” and information labels such as “Phone” “Address” and “Hours of Operation”.

<div itemscope itemtype=”http://schema.org/Dentist”>   <span itemprop=”name”>Toothman Dentistry</span>   <div itemprop=”address” itemscope itemtype=”http://schema.org/PostalAddress”>     <span itemprop=”streetAddress”>123 Fake Street</span>     <span itemprop=”addressLocality”>Fakesburg</span>,     <span itemprop=”addressRegion”>FL</span>     <span itemprop=”postalCode”>33755</span>   </div>   Phone: <span itemprop=”telephone”>123-456-7890</span></div>

view rawgistfile1.txt hosted with ❤ by GitHub

This markup is invisible to visitors, but bots and search engine spiders pick up on this, and identify the information therein as a Local Dentist with an address, phone number and other useful bits of information tied to that entity. Later on, spiders may find other information that they can append to this entity (like geotagged images, reviews from other sites, etc), in order to generate a more useful snippet in the Knowledge Graph.

Structured Data

There are multiple types of structured data syntax, which offer differing ways of communicating your structured data to a search engine, and have slightly different functionality.

Schema.orgSchema.org is the preferred structured data syntax used by the 3 big search engines: Google, Bing, and Yahoo. All three accept Schema.org markup on pages, and use it to varying degrees. Not only can you mark up NAP info, but Schema.org allows you to mark up any kind of structured data — from movie reviews, to recipes, to tour dates. Schema.org is the easiest of the structured data syntaxes to implement, as most of the property types have already been defined (but custom ones can be developed through some creative use of RDF-A markup, see below). For quickly generating your own Schema.org local listing markup for your site, visit the Microdata Generator

RDF-a & RDF-a Lite – RDF-a stands for Resource Description Framework for Attributes, and its RDF-a Lite version is a very minimal subset of the RDF-a syntax. Typically for advanced users, understanding RDF-a allows for you to use vocabularies, identifiers and syntaxes (like Schema.org) to assign custom properties to information fields, for visibility in semantic search. For more information on RDF-a and RDF-a Lite, refer to the W3 Documentation on RDF-A Lite

JSON-LD – JavaScript Object Notation for Linked Data, or JSON-LD is a markup syntax made to easily integrate with existing JSON implementations. It allows you to map your existing JSON relationships to an RDF-like model for use in semantic search. There are some special JSON-LD markups used now for quickly including special contextual information (like corporate contacts) into the Knowledge Graph.

What Benefits Come With Having Structured Data Markup?

After you’ve chosen a structured data syntax to use, wrap it around the important information on your site (like an address in the header or footer), and check your implementation using the Rich Snippets Testing Tool. This tool, built by Google, reads structured data, and can let you see what the search engine sees when it scans your site. It can detect implementation errors, show you duplicate information, and help you diagnose issues with your structured data so you can get the most accurate and up-to-date information to a search engine easily.

For example, we used the schema.org markup on our parent site spatialnetworks.com to show how someone searching for our address might find us in search:

Address Snippet

Now when someones looking for our office, they don’t have to search our site for an address, plug it in a mapping app, and find directions, the search engine “knows” where we are, and can provide the information directly, without any additional steps.

This also works for other marked up information like phone numbers too.

Phone Snippet

There are hundreds of applications for structured data markup – from recipes, to products, to tour dates, and many ways to help search engines better understand your content better. Structured data will become more and more prevalent and useful in the coming years, so gaining a thorough understanding of what it does, and how it works will pay dividends when it comes to marketing your content and business in the future.

Wrapping Up

To navigate your way through local search, remember to:

  • create and verify your local listings on the big search engines
  • markup your important NAP information with Schema.org
  • encourage reviews from your customers and clients, and
  • add new citations on local sites and quality directories
  • use an aggregator to insure your listings get properly disseminated


Here are some great resources that have helped me out over the years in improving visibility for hundreds of local businesses across the US. If you know of any great resources not listed below or in the article above, feel free to send me an email.

Mike Blumenthal – Considered THE expert in local search, Mike Blumenthal’s blog covers best practices, system changes, and everything and anything Google Local search related since 2006.

Local Search Ranking Factors – Published every year by Moz, the Local Search Ranking Factors list qualities of and correlations associated with high ranking local pages, and the weight of those factors.

Microdata Generator – Generate a preformatted Schema.org snippet for your business in one step. Just replace the NAP information on your site with the Schema.org snippet and you’ve started your journey into structured data.

Citation Finder by Moz – A comprehensive list of industry-specific citation sources for local listings

Small Business Listing Scan – A scanning tool for checking on your listings on the top 50 or so local listings directories. Check for inconsistencies, errors, missing or bad data easily, from one page.

Rich Snippets Testing Tool – Check the impementation of your Schema.org, RDF-a, and JSON-LD markup here. Quickly spot syntax or content errors so search engines can read your structured data easily.