What is schema markup?
Schema markup, from Schema.org, is a form of microdata that can enhance your website’s attributes. Google uses structured data on the web to understand the content of a page further. The most popular search engines (Google, Yahoo, Bing, and Yandex) began to create Schema.org sometime around 2011.
Schema markup is especially important for modern SEO following the Hummingbird, RankBrain, and EAT algorithm updates in more recent times. Providing more context to search engines to interpret a page further can be especially helpful when the page is ambiguous or potentially thin on content.
From Schema.org, “Most webmasters are familiar with HTML tags on their pages. Usually, HTML tags tell the browser how to display the information included in the tag. For example, <h1>Avatar</h1> tells the browser to display the text string “Avatar” in a heading 1 format. However, the HTML tag doesn’t give any information about what that text string means – “Avatar” could refer to the hugely successful 3D movie, or it could refer to a type of profile picture—and this can make it more difficult for search engines to display relevant content to a user intelligently.”
Can Schema Markup Improve My Local Rankings?
There is currently no supported finding that schema markup or structured data markup directly impacts local search rankings. Despite this, numerous case studies have stated that although it may not directly impact your rankings, schema markup can cause your website’s results to receive rich results. These rich results (featured snippet, rich snippet, knowledge, and graph) can lead to increased CTRs, a major benefit of marking up your local business website. Getting more click-throughs to your owned organic results is pivotal in generating leads and website conversions.
What is Schema & Structured Data Used for?
The most common types of schema markup are the following:
- Organizations
- Local Business
- Events
- Products
- Articles
- Recipes
- Reviews
- Videos
Although these are the most commonly found, there are several different ways that you can use structure your pages by leveraging schema.org markup. Check out the full list of supported Schema.org markups on their website.
How Do You Implement Schema Markup?
To start implementing schema markup for your website, you must decide on the method by which you will add them to your site. There are three ways that schema.org markup can be added:
- JSON-LD (Google Suggested) – JSON-LD annotates elements on a page, structuring the data, which can then be used by search engines to disambiguate elements and establish facts surrounding entities, which is then associated with creating a more organized, better web overall.
- Microdata – Microdata is a set of tags that aims to make annotating HTML elements with machine-readable tags much easier. Microdata is a great place for beginners because it’s easy to use.
- RFDa – RDFa is an acronym for Resource Description Framework in Attributes. Essentially, RDFa is an extension to HTML5 designed to aid users in marking up structured data.
The most commonly used method is using JOSN-LD. Additionally, Google has repeatedly stated that JSON-LD is their preferred method for structured data. Due to this, we also encourage doing the same. There appears to be more support documentation surrounding JSON-LD, making it easier to troubleshoot when you’re having issues getting your markup to validate. For instance, Jus Turf uses JSON-LD to leverage its local business markup successfully. We’ll use Jus Turf as our prime example.
Implementing Local Business Schema Markup with JSON-LD
To implement local business markup, use the template below to help you follow this brief tutorial. Before starting, we recommend you review this list of local business types, as your markup will need to be modified accordingly using the template below. Jus Turf, for example, would select “HomeAndConstructionBusiness” as their business type as they are an artificial grass supplier and artificial lawn designer.
Local Business Types:
| Local Business Type | Specific Local Business Type |
| AnimalShelter | |
| Apartment | |
| AutomotiveBusiness | Auto Body Shop, Auto Dealer, Auto Parts Store, Auto Rental, Auto Repair, Auto wash, Gas Station, Motorcycle Dealer, Motorcycle Repair |
| ChildCare | |
| Dentist | |
| DryCleaningorLaundry | |
| EmergencyService | Fire Station, Hospital, PoliceStation |
| EntertainmentBusiness | AdultEntertainment, AmusementPark, ArtGallery, Casino, ComedyClub, MovieTheater, NightClub |
| Financial Service | AccountingService, AutomatedTeller, BankOrCreditUnion, InsuranceAgency |
| FoodEstablishment | Bakery, BarOrPub, Brewery, CafeOrCoffeeShop, Distillery, FastFoodRestaurant, IceCreamShop, Restaurant, Winery |
| GovernmentOffice | |
| PostOffice | |
| HealthAndBeautyBusiness | BeautySalon, DaySpa, HairSalon, HealthClub, NailSalon, TattooParlor |
| HomeAndConstructionBusiness | Electrician, GeneralContractor, HVACBusiness, HousePainter, Locksmith, MovingCompany, Plumber, RoofingContractor |
| InternetCafe | |
| LegalService | |
| Notary | |
| Attorney | |
| Library | |
| LodgingBusiness | BedAndBreakfast, Campground, Hostel, Hotel, Motel, Resort |
| Medical Business | CommunityHealth, Dentist, Dermatology, DietNutrition, Emergency, Geriatric, Gynecologic, MedicalClinic, Midwifery, Nursing, Obstetric, Oncologic, Optician, Optometric, Otalryngologic, Pediatric, Pharmacy, Physician, Physiotherapy, PlasticSurgery, Podiatric, PrimaryCare, Psychiatric, PublicHealth |
| ProfessionalService | |
| RadioStation | |
| RealEstateAgent | |
| RecyclingCenter | |
| SelfStorage | |
| ShoppingCenter | |
| SportsActivityLocation | BowlingAlley, ExerciseGym, GolfCourse, HealthClub, PublicSwimmingPool, SkiResort, SportsClub, StadiumOrArena, TennisComplex |
| Store | AutoPartsStore, BikeStore, BookStore, ClothingStore, ComputerStore, ConvenienceStore, DepartmentStore, ElectronicsStore, Florist, FurnitureStore, GardenStore, GroceryStore, HardwareStore, HobbyShop, HomeGoodsStore, JewelryStore, LiquidStore, MensClothingStore, MobilePhoneStore, MovieRentalStore, MusicStore, OfficeEquipmentStore, OutletStore, PawnShop, PetStore, ShoeStore, SportingGoodsStore, TireShop, ToyStore, WholesaleStore |
| TelevisionStation | |
| TouristInformationCenter | |
| TravelAgency |
You can leverage schema.org markup for your local business using the template below and the updated local business types from above.
—–
{
“@context”: “https://schema.org”,
“@type”: “Restaurant,”
“image”: [
“https://example.com/photos/1×1/photo.jpg”,
“https://example.com/photos/4×3/photo.jpg”,
“https://example.com/photos/16×9/photo.jpg”
],
“@id”: “http://davessteakhouse.example.com”,
“name”: “Dave’s Steak House,”
“address”: {
“@type”: “PostalAddress,”
“streetAddress”: “148 W 51st St”,
“addressLocality”: “New York”,
“addressRegion”: “NY”,
“postalCode”: “10019”,
“addressCountry”: “US”
},
“review”: {
“@type”: “Review”,
“reviewRating”: {
“@type”: “Rating”,
“ratingValue”: “4”,
“bestRating”: “5”
},
“author”: {
“@type”: “Person”,
“name”: “Lillian Ruiz”
}
},
“geo”: {
“@type”: “GeoCoordinates”,
“latitude”: 40.761293,
“longitude”: -73.982294
},
“url”: “http://www.example.com/restaurant-locations/manhattan”,
“telephone”: “+12122459600”,
“servesCuisine”: “American”,
“openingHoursSpecification”: [
{
“@type”: “OpeningHoursSpecification”,
“dayOfWeek”: [
“Monday”,
“Tuesday”
],
“opens”: “11:30”,
“closes”: “22:00”
},
{
“@type”: “OpeningHoursSpecification”,
“dayOfWeek”: [
“Wednesday”,
“Thursday”,
“Friday”
],
“opens”: “11:30”,
“closes”: “23:00”
},
{
“@type”: “OpeningHoursSpecification”,
“dayOfWeek”: “Saturday”,
“opens”: “16:00”,
“closes”: “23:00”
},
{
“@type”: “OpeningHoursSpecification”,
“dayOfWeek”: “Sunday”,
“opens”: “16:00”,
“closes”: “22:00”
}
],
“menu”: “http://www.example.com/menu”,
“acceptsReservations”: “True”
}
How To Validate Your Schema Markup
After implementing your structured data or schema markup, you’ll want to check whether it is successfully validating and can be read by search engines. We’ll need to use Google’s structured data markup testing tool.
Once you verify that the results are validating using the structured data testing tool, you can also dive into the errors and warnings to figure out what might need to be fixed. The largest concern we will have when looking at the tester is ERRORS. In most cases, warnings are for “recommended” elements but not required, such as the one shown below from Jus Turf’s schema markup. As a result, warnings can generally be ignored, but they should be addressed if you have the information needed. In the example above, it is recommended that we set a “priceRange” for our restaurant, which we’ve chosen not to include.
If you’re looking for further assistance on your structured data markup for local businesses, we recommend reading more from Google’s official documentation.
About the Author
Katelyn Herr is an SEO Associate at New Dimension Marketing & Research, a San Diego, CA digital marketing agency. She specializes in web content writing and is passionate about social media marketing to help grow small businesses. Her goal is maximizing ROI for clients and helping them stand out from competitors.
