Tracking the Shopping SERPs.


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Now Google has begun rolling out the Organic listings for Google Shopping in the UK, we wanted to know how much of an impact this really has on the SERPs, and how much it will impact both Paid and Organic channels. 

Why do we care about this?

This is a huge introduction to Organic search for retail websites – no longer is the coveted Shopping performance purely for Paid channels! But that doesn’t mean Organic is just going to start flying, and as with anything Organic, there has to be some way the products are being ranked. It isn’t a free-for-all; there is a system. And that is a system we wan’t to monitor. 

First step? Track the landscape.

What are we tracking?

Google has already said the PLAs at the top of the main results page will remain as paid-only listings, which means the changes are happening on the Shopping tab itself. So, unlike our previous analysis on aspects like the map pack, we needed to extend our Luminr to assess the Shopping tab specifically instead of the main page.  

Because of that, we’re tracking the presence of Paid and Organic shopping listings, on the Shopping tab, to identify things like:

  • How frequently combination listings appear – Paid + Organic
  • How frequently a site appears in both types of listing
  • How frequently the same products appear in both types of listing 
  • Which websites dominate the results?
  • How does estimated CTR vary depending on if you appear in Paid or Organic listings?
  • How are the listings changing over time?
  • Are we seeing different sites in the Paid listings vs. the Organic?

All of this information then allows us to:

  1. Identify changes in real time and react accordingly
  2. Identify trends in listing performance and appearance, to factor into our performance forecasts and reporting
  3. Identify new competitors appearing across both Paid and Organic – just because their websites aren’t ranking on the first page of the main results, doesn’t mean they aren’t appearing at product level in the Shopping tab
  4. Spot trends in product performance and how that differs on the Shopping tab compared to other Paid listings, and how it compares to other Organic listings

So, how are we doing it?

In our admittedly preachy introductory post to SRE, we mentioned flexibility and integration being driving philosophies for its development. We’ve executed and analysed a further 260K searches since then. In this instance however we’re leaning towards flexibility, building out a specialised function to monitor the introduction of organic listings in Google Shopping. And from there, who knows where we might take it.. In the humble words of the immortal Michael Bolton:

Incredible thoughts, incredible minds
Too many great ideas inside
It’s a miracle my head can contain them
My spectacular brain
For all humankind
Changing how we think about space and time
Now it’s time to share them with the people, my brain is a genius

Incredible Thoughts, The Lonely Island

To achieve this we curated a list of the most important retail-centric search queries across our client base, prioritised by their ecommerce performance in Google Ads. Access to data like this is a huge advantage of product development from within an agency. In doing this we have an input data set of keywords we know have proven sustained interest and propensity to drive sales i.e. likely candidates [we assume] to trigger Google Shopping listings.

Over time we will be scaling up and out, expanding our set of search queries with the intention of covering more niche industries. This will help us to develop detailed benchmarks trickling down from broad retail industry expectations to more narrowly tailored markets.

Expansion won’t be limited to search queries. We will also be exploring different geographies, search operators and devices to help us generate insight to influence successful SEO strategies for Shopping.

Okay, so how are we doing this exactly? We work with SerpApi (10/10 product 💏) to collect raw SERP information across search engines. The special sauce is in how we apply data science to the raw results and automate this to deliver continuous insight a la dashboards, Slack alerts and insight decks. To give a small but vague taste of the secret recipe: it’s about quantifying and modelling the SERP as it appears to a human to derive trends and insights, such as attention commanded by different domains based on how much real estate they own and in what location/s [, location, location].

So, a lot of promises there but nothing tangible yet. While you sit there working on getting hyped we will make sure that we collect enough information to deliver on our promises. By reading this you have entered a binding agreement to return in a few weeks to read our follow-up. Thanks, bye!