Ecommerce keyword research differs from keyword research for a blog or a service business in one important way: the output is a site structure, not a list of articles. The keywords you find decide which categories exist, what they are called, how products are named and where guides fit. Get the map right and every page has a clear job. Get it wrong and your pages compete with each other.
This guide covers where to find ecommerce keywords, how to group them, how to map them to page types and how to decide what to work on first.
What Is Ecommerce Keyword Research?
Ecommerce keyword research is the process of finding the searches shoppers use for the products you sell and deciding which category, product or guide page each one belongs on. Online store searches fall into a few recognizable patterns, and each pattern belongs on a different page type.
| Search pattern | Example | Best page type |
|---|---|---|
| Broad category | linen shirts | Top-level category |
| Category plus attribute | white linen shirts men | Subcategory or curated collection |
| Brand or model | [brand] [model] trail runner | Product page |
| Comparison | merino vs cotton base layer | Guide or comparison article |
| How-to or research | how to wash a linen shirt | Guide linked to the category |
| Use case or audience | beach wedding guest dresses | Curated collection |
The mistake we see most is trying to make a category page rank for a research query, or a blog post rank for a buying query. Google usually shows one type of page for each query, and you have to match it.
Where to Find Ecommerce Keywords
- Google Search Console. Your own queries, including ones you already rank for on page two. This is the most reliable data you have.
- Google Keyword Planner. Free with a Google Ads account. The volume ranges are broad without active spend, but it is good for discovering variations.
- Ahrefs or Semrush. Volume and difficulty estimates, and above all the keywords your competitors' category pages rank for.
- Google autocomplete and People Also Ask. Show the modifiers real shoppers type.
- Amazon and marketplace search bars. Autocomplete on marketplaces reveals attribute and use-case modifiers that often carry strong purchase intent.
- Competitor navigation. Look at how the leading stores in your niche organize their categories and filters.
- Your own site search. GA4 records internal searches through the view_search_results event when enhanced measurement is on. These are the words your visitors actually use.
- Customer emails, reviews and returns notes. They show how buyers describe products, problems and fit in their own words.
How Do You Do Keyword Research for Ecommerce?
You do keyword research for ecommerce properly in seven steps: start from your catalog, expand the seed terms, clean the list, classify intent, group keywords by shared results, map each group to one URL, and prioritize by demand and margin.
- Start from your catalog. List every product type, key attribute (material, color, size range, style), brand and use case you sell. These become your seed terms.
- Expand the seeds. Run each seed through your keyword tool and autocomplete to collect variations, then export everything into one sheet.
- Clean the list. Remove terms for products you do not sell, navigational searches for other stores, and anything irrelevant to your market.
- Classify intent. Tag each keyword as category, product, comparison or informational. When unsure, search it and look at what Google shows: product grids, single products or articles.
- Group by shared results. Keywords that return mostly the same top ten URLs belong on the same page. "Men's linen shirts" and "linen shirts for men" should be one page, not two. Tools such as Ahrefs, Semrush or dedicated clustering tools can speed this up.
- Map each group to one URL. Assign every cluster to an existing page or a page you need to create, and record the primary keyword and secondary keywords for it.
- Prioritize. Score each cluster on search demand, how hard the results look, margin on the products involved and stock depth. A modest keyword on a high-margin line you always have in stock can be worth more than a bigger one on a product you sell at thin margins.
How Can You Use AI for Ecommerce Keyword Research?
Use AI to speed up the brainstorming, labeling and grouping steps, and never as the source of search volume or difficulty. Large language models such as ChatGPT, Claude or Gemini are good at suggesting modifiers for a product type, tagging a long keyword list by intent, and proposing a first draft of clusters. They are poor at numbers: they will produce plausible search volumes that no tool measured. Take every AI suggestion back to Search Console, Keyword Planner, Ahrefs or Semrush for real data, and check the live results page before mapping a cluster to a URL. AI saves hours on a large catalog, but a person still has to decide which page each cluster belongs to.
Building the Keyword Map
The keyword map is a single sheet with one row per page. Useful columns are: URL, page type, primary keyword, secondary keywords, current position, monthly searches, priority and status. It becomes the reference for everyone who writes copy, names products or changes navigation.
When a new product line launches, add it to the map before creating pages. That one habit prevents most cannibalization problems, because you can see instantly whether an existing page already targets the term.
Modifiers Worth Tracking
Modifiers are the words added to a category term, and they reveal how shoppers narrow their choices:
- Attribute: color, material, size, fit, pattern.
- Audience: men's, women's, kids', plus size, petite.
- Use or occasion: for travel, for the beach, for work, wedding.
- Quality or value: best, premium, affordable, cheap.
- Location or delivery: near me, next day delivery, made in the USA.
When one modifier appears across many categories with real volume, it may justify a filter-based landing page. Our guide to faceted navigation SEO explains how to make selected filter combinations indexable without flooding the index.
Turning Keywords Into Pages
Once the map is done, each page needs the keyword in the places that count: the title tag, the H1, the opening copy and the URL where practical. Product pages also need descriptions written around the words buyers use, which our guide to product description SEO covers in detail. The ecommerce SEO checklist lists the rest of the on-page and technical work.
Common Ecommerce Keyword Research Mistakes
- Chasing only head terms. Broad terms like "dresses" are dominated by large retailers. Specific clusters convert better and are more achievable.
- Two pages for one cluster. Separate pages for near-identical terms split links and confuse search engines.
- Ignoring the results page. If Google shows only articles for a query, a category page will struggle to rank for it.
- Trusting volume estimates blindly. Tool numbers are estimates. Use them to compare terms, and check Search Console impressions once pages are live.
- Researching once. Search behavior shifts with trends and seasons. Revisit the map at least twice a year.
Help With Keyword Research for an Ecommerce Site
Keyword research for a large catalog is time-consuming, which is why we built niche research into AM Jarvis, the SaaS suite our founder co-builds for Shopify and WooCommerce stores. We use it alongside Ahrefs, Semrush and Search Console on client work.
If you want the full map built for you and turned into category and product pages, our ecommerce SEO services include keyword research, mapping and implementation. You can also ask for a free audit to see where your current structure leaves gaps. More guides are on the 95 Solutions blog.