How To Get A 30% Increase In CTR With Structured Markup
As documented by case studies in the U.S. and abroad, retail firms can get up to a 30 percent increase in organic traffic by using structured markup like Schema Microdata, GoodRelations and Google Rich Snippets, etc. This begs the question: why aren’t more retailers using structured markup? Implementing structured data requires the skill of adding […]
As documented by case studies in the U.S. and abroad, retail firms can get up to a 30 percent increase in organic traffic by using structured markup like Schema Microdata, GoodRelations and Google Rich Snippets, etc. This begs the question: why aren’t more retailers using structured markup?
Implementing structured data requires the skill of adding a few extra lines to the HTML code of your site. Once implemented, you will immediately feed Google and hundreds of mobile and recommender applications with all the information consumers are looking for when they shop for your products. Your detailed information is displayed right in search results, as shown in the before and after examples below.
Many retailers aren’t aware that only about 5 percent of their potential customers will see their offers in the SERPs when they shop. That means 95 percent will never get beyond a brief description of their products and services as shown in the first example above without structured markup.
Below are a few illustrations showing how retailers have used structured markup for improved search results.
- Dutch car insurance website Independer.nl realized an increase of 28 percent in SEO search share (CTR).
- The implementation of Rich Snippets by Autoverzekering resulted in more revenue with higher returns.
- Yfrog added GoodRelations markup and within five days, its Rich Snippets were showing up in Google results.
- Volkswagen UK demonstrates car features and component information with GoodRelations achieving excellent results.
- Renault UK uses GoodRelations to get better rankings for its merchandise shop.
- Peek & Cloppenburg uses structured markup for publishing information on all its European stores in addition to the brands available in the stores.
- CSN Stores is uses structured markup for rich displays of all its 2,000,000 item pages.
- Arzneimittel.de, one of Germany’s leading mail order pharmacies, uses GoodRelations in RDFa on all of their 250,000 item pages.
Google recommends GoodRelations and supports Schema.org Microdata to send structured information for Google Rich Snippets to Google. Additionally, Bing and Yahoo support Microdata and recommend GoodRelations for sending structured data to display in their SERPs.
Best Buy used Microdata, RDFa to increase Doorbuster sales on Black Friday.
Lead Web Development Engineer at BestBuy Jay Myers started working with schema.org last June. Myers recommends participating in a schema.org workshop. This type of workshop would be useful for retailers before implementing structured markup on their websites.
To gain wide adoption, semantic markup must be easy to implement, and it’s important for the search engines to support multiple syntaxes. With the support for schema.org by Google, Bing and Yahoo announced in June, it was assumed that Microdata markup would eventually emerge as a standard. However, that has not been the case as other markup languages are also supported and used with excellent results, namely GoodRelations.
Expect a bit of a learning curve when you start using structured data. It’s not that the markup is so difficult; it requires a mindset for delivering human readable code while visualizing what a machine might get out of the rich markup.
Your developers may find Microdata syntax straightforward to implement; but the challenge is keeping the code pristine to ensure that machines can parse it and create accurate RDF triples. Also, with a number of different coders, it can be hard to maintain more stringent markup standards.
Despite the initial learning curve in implementing structured markup, the rewards are that consumers will benefit from your descriptive data being visible in search results. In ecommerce, reviews are important for your customers in assisting them to make informed purchasing decisions.
While there are challenges in implementation and it takes a little extra time, retailers will find it is very beneficial for creating loyalty and increased conversions.
Content Management System With Microdata Support
WebNodes AS came out with a Content Management System that provides Microdata support. Version 3.7 of the WebNodes CMS is said to be the world’s first CMS with fully integrated and dynamic Schema support. Starting now, all content classes and properties in WebNodes can be mapped to corresponding types and properties in Schema.org dynamically.
WebNodes uses dynamic mapping for adding Microdata to the HTML of your web pages. As a result, all major search engines will immediately understand the meaning of your content, improving your search results listings dramatically. Tests show a 30 percent increase in organic search engine traffic for websites using Microdata or other technologies like GoodRelations RDFa.
Another important feature of Version 3.7 is that the WebNodes CMS now fully supports load balancing in a number of different configurations. To quote from the company’s press release:
“Load balancing makes it possible to distribute traffic between different servers, making it possible to use WebNodes on sites with extremely heavy traffic. In addition to supporting regular load balancing where different instances of the CMS are running on different servers, many of the performance critical parts of WebNodes has been componentized, so you can split the performance critical components of a single instance on multiple servers as well.”
In conclusion, it’s time for ecommerce merchants to embrace structured markup to get ahead of the competition. Retailers can now get a CMS with fully integrated and dynamic Schema support. What’s not to like about a 30 percent increase in organic CTR?
Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.
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