Query Refinements: How Google Helps Users Find Products Faster via @sejournal, @Kevin_Indig

Shopping SERPs person been looking much similar a feed than ranked results for a portion now. In December, I wrote astir the integration of Google’s buying tab into the main results for buying queries in e-commerce shifts. The effect is simply a marketplace that looks much similar Amazon than web hunt results.

SERP features and query refinements play a large relation successful this transition. They nonstop users from unrefined searches to uncovering products arsenic rapidly arsenic possible, having an outsized interaction connected clicks and revenue.

In this heavy dive, I analyzed +28,000 buying SERPs to recognize however query refinements enactment and however e-commerce sites tin usage them.

It’s a spot aboriginal for buying season, but I’m penning a batch of e-commerce due to the fact that astir shops request immoderate clip to marque changes connected their tract (especially the large ones). So, if you privation a fruitful 2024, present is the clip to get the enactment connected the roadmap.

This portion builds connected 2 analyses I’ve published previously:

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What Are Query Refinements

Query Refinements are “pills” astatine the apical of the hunt results that assistance users refine their search. In essence, query refinements are merchandise filters.

First announced at Google Search On 2022, Google explained that refinements (and filters connected desktop) travel real-time hunt trends (bolding mine):

Whole leafage buying filters connected Search are present dynamic and adapt based connected real-time Search trends. So if you’re buying for jeans, you mightiness spot filters for “wide leg” and “bootcut” due to the fact that those are the fashionable denim styles close present — but those whitethorn alteration implicit time, depending connected what’s trending.1

Examples of Query Refinements. (Image Credit: Kevin Indig)

The intent of query refinements is to bring users from the “messy middle” to conversion arsenic rapidly arsenic imaginable arsenic they literally refine the query. When you click connected a pill, Google sends users to different SERP, conscionable similar erstwhile users click the merchandise filters connected the left.

To recognize however query refinements enactment and however e-commerce sites tin usage them to their advantage, I dug up immoderate data.

How Query Refinements Work

I analyzed 28,286 buying keywords (US, desktop) with seoClarity and recovered that query refinements:

• follow chiseled patterns sites tin usage for keyword targeting.
• lead to hunt queries without hunt volume.
• trigger caller AI Overviews connected mobile.

Common Refinements

I analyzed which refinements travel up astir often successful “position” one, 2 and three. Think astir presumption 1 successful this discourse arsenic the archetypal refinement from the left, which is the astir visible.

Most refinements specify gender. The word “women” comes up astir often successful the apical 3, but “men” comes up astir often successful the archetypal refinement. 45% of query refinements notation 1 sex astatine slightest once, 61.4% if you see kids. It makes sense: earlier diving into merchandise attributes similar colour oregon size, you privation to marque definite a merchandise is “for you.”

The astir communal query refinements. (Image Credit: Kevin Indig)

The 2nd astir communal radical of refinements is location. Ten percent of the apical 3 refinements see “nearby,” which is overmuch much disposable connected mobile. Google shows maps by default connected mobile devices, arsenic mobile instrumentality users are much apt to beryllium connected the go.

The 3rd radical is attributes astir queries that see “for” oregon “with”, wherever users effort to specify usage cases (9.8%), and the 4th is terms (9% of refinements see the word “sale”).

Query refinements person a precocious overlap with merchandise filters connected desktops and often diagnostic the archetypal fewer filters arsenic refinements. Product filters don’t beryllium connected mobile, apt due to the fact that users mightiness expect the filter sidebar connected desktop, but it doesn’t marque consciousness connected mobile.

Product filters (desktop) and query refinements thin to person precocious overlap. (Image Credit: Kevin Indig)

The sorting and visibility of refinements are antithetic connected mobile and desktop. Due to the quality successful bigger surface size, mobile hunt results amusement ~4 refinements connected load, portion desktop tin amusement implicit 10.

Since query refinements are based connected realtime searches, they besides overlap heavy with autosuggest.

(Image Credit: Kevin Indig)

Interesting Findings

Three insights from the information amazed me:

First, Google keeps refinements strictly focused connected merchandise attributes but not idiosyncratic intents. I expected searchers to beryllium funny successful opinions and reviews connected Reddit, but neither “Reddit” nor “reviews” came up arsenic a refinement a azygous time.

Two, query refinements precisely lucifer the query, meaning you won’t find synonyms oregon intimately related presumption successful them. As a result, brands don’t look successful refinements, either.

Three, astir query refinements don’t person hunt measurement oregon a CPC. Only 10,696 / 27,262 keywords successful the archetypal refinement person hunt measurement (median = 70), and lone 6,514 / 27,262 keywords person a CPC. Since query refinements are based connected hunt behavior, we tin reason that hunt measurement and different keyword planner information are precise constricted metrics.

AI Overview Refinements

Of course, I came across AI Overviews (AIOs) successful my research. For the queries I analyzed, mobile results returned AIOs but desktop doesn’t. An illustration is brown mascara.

Brown mascara connected desktop, nary showing an AIO. (Image Credit: Kevin Indig)

Brown mascara connected mobile, triggering an AIO. (Image Credit: Kevin Indig)

You apt spotted the AIO tabs connected the screenshot above, which look independently of refinements and explicate communal merchandise attributes.

(Image Credit: Kevin Indig)

Notice however the AIO provides further guidance and accusation successful tabs (see screenshot below).

(Image Credit: Kevin Indig)

At this point, it’s unclear whether citations successful AIO tabs are bully due to the fact that they thrust postulation to reappraisal articles oregon atrocious due to the fact that they springiness the reply away.

(Image Credit: Kevin Indig)

For different queries, similar “air compressor”, I was capable to spot refinements in the AI Overview alternatively of supra it. Clicking an AIO refinement leads to different hunt with the refinement successful the query. For example, connected the SERP for “air compressor”, one refinement is “for coating cars”. Clicking it leads to different SERP for the query “air compressor for coating cars” (with different AIO and tabs but nary refinement). Notice that I was logged into the SGE beta, which means those features mightiness not yet beryllium unrecorded for each user.

(Image Credit: Kevin Indig)

5 Lessons

5 cardinal lessons surfaced from my investigation of implicit 28,000 buying queries:

• You should make circumstantial merchandise and class pages for men/women/kids erstwhile it matters for products (e.g. fashion).
• Mine query refinements and autosuggest to find applicable query variations for your keyword probe (for example, seoClarity tin bash this).
• Monitor ranks by query refinement to thrust your decisions astir facetted indexing (like Nike or Target). Refinements showing antithetic URLs are an indicator of gathering circumstantial facets.
• You request to place searcher involvement beyond hunt volume. The information that much than fractional of queries don’t person hunt volume, but query refinements are optimized for hunt behaviour shows that you mightiness miss a batch of opportunities by limiting yourself to queries that person hunt volume. Instead, leverage onsite hunt data, surveys and qualitative probe to heighten keyword targeting.
• Monitor and comparison clicks from desktop and mobile results to recognize the interaction of merchandise filters (desktop) and AIOs (mobile).