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BrightonSEO eCommerce Summit: Let's talk Product Schema

21 June 2018 14:56

It was fantastic to be at the first BrightonSEO eCommerceSEO Summit yesterday. Katherine shared about 'The Importance of Understanding Product Schema & What this means for SEOs'.

 

What is Product Schema? 

Before we can start talking about Product Schema, let's set the scene with Structured Data. Structured data is about providing explicit clues about the meaning of a page to search engines.  It is a standardised format for providing information about a page and classifying the page content. For example, on a recipe page, what are the ingredients, the cooking time and temperature, the calories, and so on. Structured data uses schema.org for this format.

Product Schema refers to structured data specifically for a product. Imagine you are trying to describe a product page to someone who is visually impaired – the elements you would describe, i.e. 'title', 'description', 'price', are all structured data tags.

Here are some useful links: 

How is Structured Data implemented in practice ? 

Integrating Schema.org structured data does not have to be intrusive or difficult. For standard markup this is coded using in-page markup (JSON-LD, Microdata or RDFa). For Smart Search, it is necessary to work with GS1 for the verticals they have identified (Apparel/Food&Beverage) and if you'd like to find out more, contact GS1 here 

MICRODATA: Microdata is a web standard used “to annotate content with specific machine-readable labels.” Effectively, it places short bits of markup inline with other HTML to better describe the associated HTML content.

JSON-LD: JSON-LD has advantages over microdata, including being separate — i.e., inside of a script tag nested in the document head — from the HTML markup.

Again, here are some more useful links:

You can test you Structured Data markup using the Google Structured Data testing tool, along with other tools below: 

Structured Data is great, but what does this mean for products? 

Schema refers to a site-wide markup. However, when we are talking about 'product schema' we're just focusing on the markup for a product. Helpfully schema.org gives an array of ways to tag a ‘property’: https://schema.org/Product.

However, this is not entirely complete for products and you are currently limited in how you articulate a product's attributes. GS1 are developing SmartSearch for products which help articulate product attributes. This is currently incomplete (only available for food/beverage and apparel) but they are seeking to expand this. For more information about SmartSearch click here

Does Structured Data help increase sales?

All this effort to implement structured data begs the question, does it make a difference to your website sales? After all that's what we all care about. Sadly, there is no concrete study which shows that implementing Structured Data increases sales. Remember it is not currently part of any search engine algorithm but more a helpful tool that helps signal relevancy.

But it is this improved relevancy which then leads to increased traffic and sales.

Interestingly, when implementing Smart Search, GS1 ask organisations to measure the three following KPI's:

KPI 1: Relevant Search Improvements 

While GS1 do not promise general page rank improvements, pages with structured data are easier to index helping them to appear higher for relevant searches. 

KPI 2: Increased Sales Per Click-Through From Search Engines 

Increased relevance means that consumers are more likely to find what they searched for, and therefore are more likely to purchase. 

KPI 3: Reduced Returns 

Who would have thought that by improving the quality of product data,  you could reduce returns!? The theory is that if consumers trust what they are going to have delivered, this in turn should lead to a reduction in returns with the reason, 'this product was not what I wanted/thought I was getting'.

It's exciting to think that Structured Data could have implications for the rest of your organisation such as your logistics and fulfilment.  

What about Structured Data for multi-channel sales? 

When talking about Structured Data, the conversation tends to be restricted to how this works on a website. However, there seems to be a general move online to ensure product data is clean. For channels (such as eBay) Structured Data refers to ensuring data is categorised, clean and validated. 

In eBay's own words, “Structured data is a big topic that is driving many projects here at eBay, and the short answer is: Knowing exactly what products are on sale helps us make a better marketplace for everyone

https://sellercentre.ebay.co.uk/business/news/product-identifiers-questions-answered 

While your company's eBay presence may not be within your remit, or you may not even sell on eBay (!), it is interesting that there is a web-wide movement pushing for cleaner, more structured data to ensure product validity. 

What does the future look like for Structured Data? 

1) Increased dependency for quick voice search…  

With voice search set to account for 50% of all searches made by 2020, it will be interesting to see the part that structured data plays in enabling quick searches. Believe it or not, two million blog posts alone are published every day, so how are search engines to handle the increase in content to continue to provide relevant search results? 

Within Structured Data, we may see a rise in the use of ‘Howto’ tags to help enable this. We are already seeing a reliance on tagging (seen in Recipes schema) and perhaps there will be further extensions around other specific instructions i.e. common FAQs.  

2) Extension of Smart Search for verticals 

Currently GS1 SmartSearch only documents attributes for Beverages/Food & Apparel. However, in the future we may see this expand into other verticals such as DIY, Homeware, or other Durables. Hopefully, we'll see this expansion accelerated by future partnering with businesses/platforms (remember it was a collaboration with Tesco that led to the increase in vocabulary for Food/Beverage!)

3) Question answering…? 

This is linked to the rise of voice search, as there seems to be a move online to get answers to questions easily.  Last year Google released a paper, ‘Knowledge Based Trust: Estimating the Trustworthiness of Web Sources' saying that Structured Data might come from a number of different types of resources that can be identified using processes such as “markup language tag detection, formatting instructions, file identifiers, etc.”. 

This means they may start creating a query template and indexing answers from multiple sources to provide answers to question queries. Almost like a wikipedia of FAQs, built from Structured Data! This could be a while off, but it would be interesting to see if this happens. 

To close

To close, we started with the aim of understanding product schema and what this means for our sales and traffic. We touched on how this works multi-channel while looking at how to implement this and then some future predictions. All in all, a very whistle-stop tour of product schema but if I hope this was a helpful overview.

If you have any further comments or questions about the talk, it would be great to get these below or get in touch with the team here