Chapter 1 - Most Common Mistakes with eCommerce SEO

1. Not aligning navigation link labels with shopper search language

Ecommerce sites need to ensure that menu navigation is aligned with the shopper decision hierarchy and uses appropriate customer-friendly labels. It’s common for businesses to use internal language when defining product categories and menu labels but this can create a miss-alignment with customers if the labels don’t describe products in a way they’re expecting.

This can lead to two problems:

  1. Query coverage gaps for organic search as page content doesn’t include the most relevant keywords that shoppers use when searching
  2. Page engagement metric drops when customers can’t find what they’re looking for on landing pages, reducing the quality signal.

There’s a useful case study from Mars UK, who worked with a leading online grocer to get customer insights on how shoppers searched for pet food. They discovered that there were subtle differences in language between how products were labelled on the digital shelf vs. how shoppers searched for the same products (for example “pate” vs. “tray” for tinned food).

What did this change?

  • Digital shelf re-labelled to align with shopper language – faster time to product
  • Product titles optimised to include shopper language – improved organic search visibility
  • Enriched product attributes – improved visibility in the ecommerce store through smart filters and on-site search query matching.

Results were measured mainly using a keyword ranking tool and Google Analytics but ecommerce teams can also test proposed changes to site navigation menus and filter labels using a tool like Treejack which enables goal completion tests on specific user tasks.

Summary of treejack
James Gurd

James Gurd

eCommerce strategy and Replatforming Consultant

James is an independent ecommerce strategy and replatforming consultant with more than 16 years’ experience working with some big names and companies. He helps organisations deliver ecommerce growth based on realistic plans and budgets and specialises in ecommerce replatforming, guiding organisations through the complexities of a new platform build or replatforming project, as a technology/solution agnostic independent consultant. He’s the co-founder of the popular #EcomChat Twitter networking group and the Re:platform podcast.

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Table of Contents

Top tips:

  • Cross-reference SEO keyword research with your online product catalogue hierarchy and labels
  • Ensure key categories are aligned with the volume-based query language
  • Sense check filter labels on product list pages and update if labels aren’t aligned with shopper search language
  • Enrich product pages with attribute data to enable coverage of relevant related keywords.

2. Not optimising pages for mobile speed and checking Google’s new Web Vitals metrics

Page speed impacts ranking, that’s been known since 2018. Ecommerce teams need to keep an eye on how Google measures page speed because you might think your site is fast, yet you don’t satisfy Google’s benchmarks.

Many sites still focus on creating beautiful brand experiences and page optimisation and performance consideration are left to the last minute. That’s the wrong approach – you should involve developers and SEOs from the beginning, do UX and design decisions that are balanced with ecommerce and performance requirements. It’s about finding a balance; an SEO perfect page that looks rubbish and doesn’t convert isn’t a success, neither is a stunning design that customers love but fails to rank and loses you traffic.

Install the Google Chrome Web Vitals extension and enable when you’re working on any new landing page or updates to existing pages. Does the page get a green light? If not, before panic sets in, compare to your main SERPs competitors – are you ahead? If you are, then the cost/effort of improving your web vitals scores might not be justified. Speak to your developers to find out what can be done to shave time of the load e.g. defer non-essential scripts, reduce image sizes.


Use Chrome’s developer tools to get a more detailed breakdown, and focus on mobile first.


Even if you can’t get a full green traffic light set initially, this gives you the benchmark against which to evaluate improvements and also assess the impact of page changes.

Top tips:

  • Install the Google Web Vitals browser extension in Chrome and run it for key landing pages
  • Re-check Web Vitals when pages are updated and after major releases.

3. Not maximising use of filtered pages for long tail search

Smart filters improve product findability and help shoppers make selection decisions. For most ecommerce sites, when a filter is applied, an additional parameter is added to the URL, effectively creating a unique URL. Let’s use the Activewear Accessories for Women category page on Farfetch as an example:

Default URL:

Now filter by colour = blue

Updated URL:

So what does this mean?

These links are all crawlable by search engine bots. This means that if you don’t use indexation controls, you’ll end up with a large number of potentially low value URLs with duplicate or very similar content, all fighting against each other to win the SERPs battle. This simply dilutes your SEO strength.

A simple catch-all solution is to ensure URL parameters added by faceted navigation filters are excluded from the index, through a combination of approaches including:

  • Setting a noindex meta tag
  • Appending parameters after a # so they’re not read
  • Using the robots.txt (though it’s advisable to do this via Google Search Console)

Controlling the URLs submitted to the search index is important for SEO. However, blocking all URLS created by filters isn’t necessarily an optimal solution and may hamper your long tail visibility.


Consider the Farfetch example. The main category page needs to be visible for the big volume head and mid tail terms like ‘womens activewear’ and ‘workout clothes for women’. However, there are also many lower volume related queries that apply to a subset of the products in the activewear category, for example ‘activewear tops’.

If you only have a single category URL trying to rank for all relevant query variations within the ‘activewear for women’ cluster, it will struggle to win the battle against competitors who have created custom URLs for the in-demand queries. For example ‘fila activewear’ has a 10x smaller search volume than ‘womens activewear’ but would benefit from a unique indexable URL so that the on-page content is contextually relevant and the content gives a strong relevance signal than a full category dump where Fila is only part of the range.

The secondary benefit is for your merchandising teams. They’ll thank you for giving them unique pages to run focused merchandising campaigns, rather than trying to find generic merchandising rules that work for a broad range of products and shoppers. For example, with the Farfetch page filtered by the ‘Fila’ brand, the ecommerce merchandiser can create custom Fila banners and promotions eligible only for that brand range within that category.

4. Not maximising structured data potential

We are now in the era of the semantic web. Structured data is a standardised way to provide information about your page and classifying its content; for example for a product page review, how many reviews, what is each rating, what is the content of each review, when was the review submitted etc.

Marking up pages is an important way to help search engines better understand page content and boost your chances of getting rich snippets in SERPs to help you stand out visually from other listings.

  • Below are the most frequently used structured data types for ecommerce:
  • Product
  • Review
  • Organisation
  • Sitelinks searchbox
  • Breadcrumb
  • Itemlist for category pages
  • Article for blogs
  • How-to
  • FAQ
  • Q&A
  • Person
  • Local business

Depending on the content you publish and the products you sell, there may be other relevant structured data types to consider. For example, online grocery sites like Morrisons provide recipe ideas to their customers, and Recipe is a supported data type for markup. We recommend going to and doing a thorough assessment of which data types are relevant for each key page on your website.

What difference does this make to my brand in SERPs?

Structured data can help give you:

  • Placement in valuable SERPs real-estate
  • Visual differentiation
  • Social proof and authority signals

The screenshot below from Google UK for the query ‘how to cook spaghetti bolognese’ shows the answer box ‘Recipes’ visual content. This type of SERP result typically gets a better CTR (click through rate) than standard organic listings below.


The screenshot below from Google UK shows an organic listing with a breadcrumb trail showing for ASOS whereas competing listings don’t have this additional set of links. 


5. Non-optimised breadcrumbs

Breadcrumbs serve two important purposes:

  • Provide shoppers with a clear indication of where they are in the site = UX play
  • Inform search engines of relationships between pages and the page hierarchy = SEO play

Product pages (when viewed in aggregate) often represent the majority of pageviews, especially for large catalogue retailers. Facilitating journeys between product pages and also between products and category pages higher up in the site structure, helps users navigate your site and also sends useful site structure and hierarchy to search engines when they crawl.

However, these links aren’t always printed to the front-end website, therefore aren’t visible to shoppers. Or they’re not made clickable, so don’t support internal linking structures. Furthermore, not all sites feature a clickable breadcrumb on mobile yet for most retailers, mobile is >60% of traffic.

The example below shows an absolute category path optimised breadcrumb on the Product Detail Page (PDP) for, with the mobile design different to desktop to ensure critical page content isn’t obscured or pushed further down the page.


Top tips:

  • Create a consistent category path structure for PDP breadcrumbs
  • Make them visible to shoppers on the website
  • Make them clickable for internal linking benefit
  • Track interactions via web analytics
  • Add breadcrumb markup
  • Validate markup with Google.

Screenshot: validation of structured data


6. Overlooking Q&A search in product content optimisation

Shopper search behaviour when foraging for information is constantly evolving and the mobile shift, including a spike in the use of voice-enabled search, is resulting in more complex queries and question-based searches.

The traditional approach to ecommerce product content creation is to focus on the functional ecommerce side:

  • What’s the name?
  • What does it look like?
  • How much is it?
  • What’s the product description and spec?
  • What does it go well with?
  • What are the delivery and returns options?
  • Does it have reviews?

However, this misses out on answering specific questions shoppers might have that help them determine product suitability. For example, Samsung recognised that for its home appliances there was a significant search demand for questions relating to appliance noise, safety, reliability, etc. Its retail partners weren’t answering these questions via their ecommerce product pages, enabling Samsung to create bespoke content to service this search demand and push this via its D2C site, boosting its own SEO visibility.

Use keyword research tools that enable you to filter Q&A searches. Most SEO research tools like enable this and Answerthepublic is a useful visualisation tool, with a limited free version to test and a Pro version with enhanced features like alerts to new questions on any brand name or topic. Authoritas have a FAQ tool that provides user with related list of questions that consumers are asking that you could (and probably should) be answering.


Some ecommerces sites use insights from Q&A search analysis to enrich product data, such as adding new product attributes and then enable these pages to be indexed with optimised meta data. For example, John Lewis has a useful attribute filter for ‘Defrost type’.

John Lewis Filter

Top tips:

  • Use keyword research tools to identify question-based searches related to your product categories/brands
  • Export data to Excel (or equivalent) and then filter to aggregate queries based on commonality
  • Assess keyword groupings for search volume and level of competition
  • Prioritise low competition/high volume queries
  • Append Q&A blocks to key product pages and/or create new content hub pages that answer query groups and link shoppers to relevant products.
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