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How Do You Do Keyword Research for an Ecommerce Website?
A practical framework for finding, evaluating and prioritising the searches that can drive product, collection and content visibility.
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IN SHORTEcommerce keyword research is the process of identifying the language potential customers use when searching for products, categories, solutions and information, then judging which searches are commercially relevant enough to deserve a page or SEO priority. The goal is not to collect the largest keyword list. It is to understand demand, intent and opportunity well enough to decide what your store should target and where.
For an ecommerce site, keyword research sits between commercial strategy and site architecture. It influences which collections should exist, how product pages are described, which supporting guides are worth creating and which pages deserve the strongest internal links.
A useful keyword set therefore needs more than search volume. It should show what the searcher appears to want, how closely the query matches the catalogue, what type of page Google tends to reward, how competitive the results are and what commercial value the query could have for the business.
What is ecommerce keyword research?
Ecommerce keyword research is the structured process of discovering and evaluating search queries connected to the products you sell and the problems those products solve. It includes high-volume category terms, specific product searches, attributes such as size or material, brand and model searches, comparisons, use cases, questions and seasonal demand.
The output should become a prioritised keyword universe rather than a random export from a keyword tool. Each useful term or theme should eventually have a clear role: target an existing page, justify a new page, support a wider topic cluster or be deliberately ignored because it does not fit the business.
KEY DISTINCTION: Keyword research finds and evaluates search demand. Keyword mapping, covered in Article 11, decides which specific product, collection or content page should target each theme.
Why is ecommerce keyword research different from general keyword research?
| Ecommerce consideration | Why it matters |
|---|---|
| Commercial intent | Many valuable searches are close to a purchase, so relevance to the catalogue matters as much as raw volume. |
| Page type | A keyword may belong on a product page, collection page, buying guide, comparison page or informational article. |
| Catalogue depth | A large store can contain thousands of attributes, variants, brands and subcategories that create distinct search opportunities. |
| Stock and margin | A keyword can look attractive in a tool but be a poor priority if the store cannot support the demand profitably or consistently. |
| Seasonality | Demand can move sharply around gifting periods, weather, events, launches and category-specific buying cycles. |
| Cannibalisation risk | Creating too many near-identical pages for closely related terms can make the site compete with itself. |
Start with the business and catalogue, not the keyword tool
Before opening Keyword Planner, Ubersuggest or any other research platform, build a clear inventory of what the business actually sells and what it wants to grow. This prevents the research drifting towards high-volume terms that sound attractive but do not fit the commercial offer.
- List the primary product categories and subcategories.
- Identify brands, models, product types, materials, sizes, colours and other meaningful attributes.
- Note profitable or strategically important ranges.
- Identify seasonal products and categories with supply constraints.
- List customer problems, use cases and buying questions heard by support or sales teams.
- Note geographic limits, delivery restrictions or markets the store does and does not serve.
- Identify categories the business plans to expand rather than only what exists today.
The main types of ecommerce keywords
| Keyword type | Example | Likely page type |
|---|---|---|
| Broad category | running shoes | Collection/category |
| Subcategory | men’s trail running shoes | Collection/subcategory |
| Product/model | Nike Pegasus 41 | Product or brand/model landing page |
| Attribute/modifier | waterproof trail running shoes | Collection/filter landing page if justified |
| Problem/use case | running shoes for flat feet | Collection, guide or hybrid landing page |
| Comparison | trail shoes vs road running shoes | Guide/comparison content |
| Informational | how often should you replace running shoes | Guide/article |
| Brand + product | Brooks running shoes | Brand collection |
| Transactional modifier | buy running shoes online | Commercial category page if natural and relevant |
How do you identify search intent?
Search intent is the likely goal behind the query. For ecommerce SEO, intent determines both whether a keyword is useful and what type of page should target it. A page can be highly optimised around the words in a query and still struggle if it is the wrong page type for what searchers appear to want.
| Intent | Typical query | Best starting point |
|---|---|---|
| Transactional | buy waterproof walking boots | Product/collection page |
| Commercial investigation | best walking boots for wide feet | Buying guide or strong category page |
| Navigational | Salomon UK | Brand/site destination |
| Informational | how to clean walking boots | Guide/article |
| Local | running shop near me | Local landing page / Google Business Profile context |
Check the actual search results before assigning intent. If Google mostly shows category pages, product listings or shopping-led results, that is a strong clue that a commercial page is expected. If the results are dominated by guides, comparisons and advice, forcing a collection page to target the term may be the wrong fit.
Where should ecommerce keyword ideas come from?
1. Google Search Console
For an established store, Search Console is one of the best starting points because it shows real queries for which the site already appeared in Google Search. The Performance report can be segmented by query, page, country and device, with metrics including clicks, impressions, CTR and average position.
Use it to find:
- queries already generating clicks and sales-supporting traffic
- high-impression queries where the current page is underperforming
- new modifiers and wording customers use that are missing from page copy
- queries where the wrong page appears to be ranking
- brand vs non-brand demand
- country-specific wording differences where international data exists
SEARCH CONSOLE LIMITATION: Search Console does not expose every query. Some queries are anonymised for privacy and the interface only stores/displays a limited set of rows, so treat it as a powerful source of real demand rather than a complete keyword database.
2. Google Keyword Planner
Keyword Planner can generate ideas from seed terms or a website and provides estimates such as average monthly searches and advertising competition/cost data. Although it is built for Google Ads, the ideas can help SEO research when interpreted carefully.
Use search-volume data as a directional signal rather than a promise. Google notes that very low-volume terms may not be discoverable or forecastable, and the figures are estimates designed for advertising planning.
3. Google Trends
Google Trends is useful for comparing wording, spotting seasonality, checking regional differences and identifying rising related searches. Its values are normalised relative interest scores rather than absolute monthly search volumes.
This makes Trends especially useful for questions such as:
- Is “walking boots” more seasonal than “walking shoes”?
- Which of two common product descriptions is gaining interest?
- Does demand differ materially between the UK and another target market?
- Is a rising product term a short spike or part of a sustained trend?
4. Your own onsite search and customer language
Internal site-search data, customer service tickets, reviews, sales calls and merchandising teams often reveal commercially useful wording that generic keyword databases miss. Customers may describe products by problem, fit, use case, feature or nickname rather than the taxonomy used internally by the business.
5. Competitor and SERP research
Review competitors that consistently appear for commercially important searches. The aim is not to copy their keyword lists. Look for category structures, recurring modifiers, content gaps and page types that reveal how the market is being served.
Also review the search results themselves for related searches, People Also Ask-style questions, shopping results, brands, marketplaces and specialist retailers. The composition of the SERP helps explain both intent and competition.
6. Third-party keyword tools
Platforms such as Ubersuggest, AnswerThePublic, Semrush and Ahrefs can broaden the research with keyword ideas, competitor data and difficulty-style metrics. These metrics are useful for comparison within a tool, but they are proprietary estimates rather than Google ranking scores.
How much should search volume matter?
Search volume matters, but it should not be the only prioritisation metric. A lower-volume query can be commercially stronger when it closely matches a high-value product or reveals specific purchase intent.
| Query | Illustrative volume pattern | Commercial fit | Likely priority |
|---|---|---|---|
| shoes | Very high | Too broad | Low for a specialist store |
| running shoes | High | Strong category fit | High |
| waterproof trail running shoes | Lower | Very specific commercial fit | Potentially high |
| best trail shoes for winter | Lower | Commercial research intent | Strong content/category opportunity |
| how are running shoes made | Variable | Informational and distant from purchase | Depends on content strategy |
DO NOT DISCARD LOW-VOLUME TERMS AUTOMATICALLY: Specific ecommerce searches often have lower measured volume individually but can be valuable as a cluster. Product attributes, model names and long-tail buying queries can also convert more efficiently because the searcher has already narrowed the requirement.
What are long-tail ecommerce keywords?
Long-tail keywords are more specific searches, often containing several qualifiers. They are not necessarily obscure; they are simply narrower than the head term. Examples include “women’s waterproof trail shoes size 6” or “best beard shampoo for flaky skin”.
Long-tail searches can reveal useful attributes and intent even when each exact phrase has modest volume. Rather than building a separate page for every wording variation, group semantically similar searches into one useful theme where they share the same intent and page type.
How do you research collection-page keywords?
Collection pages usually target product-category demand. Research should start broad, then identify meaningful subcategories and modifiers that deserve either dedicated collections or stronger optimisation within an existing collection.
- Core product type: “running shoes”
- Audience: “women’s running shoes”
- Use case: “trail running shoes”
- Feature: “waterproof running shoes”
- Fit/problem: “running shoes for wide feet”
- Brand: “Brooks running shoes”
- Price/value modifier where commercially appropriate
Do not create a collection for every filter combination. A new indexable collection should have clear search demand, useful product coverage, a stable catalogue and enough distinction from neighbouring pages.
How do you research product-page keywords?
Product-page research is narrower. The primary targets normally include the exact product name, model, brand, important variant or attribute terms and relevant descriptive language customers use for that specific item.
For a product page, prioritise accuracy over keyword breadth. Trying to make one product rank for a broad category term can weaken relevance and create overlap with the collection page that should own the category query.
How do informational keywords support ecommerce?
Informational searches can build discovery earlier in the buying journey and strengthen topical coverage around commercial categories. Useful content should solve a real question while creating a logical path towards relevant products or collections.
| Informational theme | Commercial connection |
|---|---|
| How to choose trail running shoes | Supports trail running shoe collections |
| How to measure your foot for running shoes | Supports footwear product selection |
| Running shoe cushioning explained | Supports feature-led collections and product comparisons |
| When to replace running shoes | Supports repeat purchase and product discovery |
The content should not exist solely to contain keywords. It should genuinely help the customer make a better decision and provide natural internal links to the commercial pages that can solve the next part of the journey.
How do you use competitor keyword research without copying competitors?
Competitor data is most useful for identifying gaps and patterns. A competitor ranking for a term does not mean your site should target it. Ask whether your catalogue, expertise and page type can satisfy the same intent better or differently.
- Find commercially relevant keywords where several competitors rank but you have no suitable page.
- Identify categories competitors have split more logically than your current architecture.
- Look for modifiers that appear repeatedly across successful product and collection pages.
- Compare content depth and SERP intent before deciding that a ranking gap is a keyword gap.
- Exclude competitor terms that depend on products, locations or services you do not offer.
How should keywords be grouped?
Keyword grouping prevents the research becoming thousands of disconnected phrases. Group terms by shared intent, product family and likely landing page. Closely related wording can normally live within one keyword cluster rather than requiring separate pages.
| Cluster | Example terms | Likely owner |
|---|---|---|
| Trail running shoes | trail shoes; trail running trainers; off road running shoes | Trail running collection |
| Waterproof trail shoes | waterproof trail shoes; Gore-Tex trail shoes; waterproof off-road shoes | Dedicated collection if demand/catalogue justify it |
| Trail shoe sizing | how should trail shoes fit; trail shoe sizing; size up trail running shoes | Guide/article |
| Specific model | Salomon Speedcross 6; Speedcross 6 men; Salomon Speedcross size 9 | Product page |
How do you prioritise ecommerce keywords?
A practical prioritisation model should combine search opportunity with business reality. A simple score can use five factors rather than relying on search volume alone.
| Factor | Question to ask | Suggested importance |
|---|---|---|
| Commercial relevance | Does the query closely match products or categories we want to sell? | Very high |
| Search intent fit | Do we have or can we create the right page type? | Very high |
| Demand | Is there meaningful evidence of search interest? | High |
| Competition/opportunity | Can this site realistically compete with the current results? | High |
| Business value | Are margin, stock, repeat purchase or strategic importance strong? | High |
| Seasonality/timing | Is demand concentrated in a specific period? | Contextual |
A KEYWORD IS NOT AN SEO STRATEGY: The final decision should be made at theme and page level. A commercially valuable collection supported by twenty related queries is more useful than twenty keywords scattered across twenty competing pages.
A practical ecommerce keyword research workflow
1. Define the commercial scope
Clarify markets, products, priorities and exclusions before researching.
2. Build seed lists from the catalogue
Use categories, products, brands, features, problems and customer language.
3. Export Search Console queries
Identify existing visibility, quick wins and unexpected wording.
4. Expand with keyword tools
Use Keyword Planner and third-party tools to broaden themes and estimate demand.
5. Check Trends and seasonality
Compare wording, regions and timing where relevant.
6. Review the live SERPs
Confirm intent, page type and competitive landscape for priority themes.
7. Research competitors
Identify genuine gaps rather than copying every ranking term.
8. Clean and cluster the data
Merge duplicates and group terms by common intent/page type.
9. Score commercial priority
Combine relevance, intent, demand, competition and business value.
10. Pass the clusters into keyword mapping
Assign each priority cluster to an existing or planned page in Article 11.
What should the keyword research deliverable contain?
For a usable ecommerce SEO project, the deliverable should contain enough information to make page and content decisions. At minimum, include:
- Keyword or keyword cluster
- Primary search intent
- Suggested page type
- Estimated demand or relative demand signal
- Current ranking/visibility where available
- Commercial relevance or business priority
- Competition/opportunity notes
- Seasonality or regional notes
- Recommended action: optimise existing page, create new page, merge, ignore or investigate
Common ecommerce keyword research mistakes
- Chasing the highest search-volume terms regardless of commercial fit.
- Creating one page for every keyword variation instead of clustering shared intent.
- Ignoring the type of pages Google already ranks for the query.
- Using keyword difficulty scores as if they were Google metrics.
- Treating Keyword Planner or third-party volume estimates as exact demand.
- Ignoring Search Console data from the site’s existing visibility.
- Ignoring stock, margin, location or delivery realities.
- Researching only product terms and missing category, problem, comparison and informational demand.
- Creating indexable filter pages without enough demand or unique value.
- Failing to update the research as products, customer language and search behaviour change.
How often should ecommerce keyword research be updated?
A full keyword strategy does not need rebuilding every month, but it should not be treated as permanent. Review it when the catalogue changes materially, new categories launch, a migration or redesign changes site structure, competitors or search behaviour shift, or Search Console shows new demand that the existing page set does not serve.
Seasonal categories should be reviewed before the demand peak rather than after it. Google Trends and historical Search Console data are particularly useful for timing these reviews.
How keyword research leads into keyword mapping
Once the research has been cleaned into meaningful clusters, the next decision is ownership: which URL should target each theme? That is where keyword mapping begins.
Article 11 covers how to map keywords to products, collections and content without creating cannibalisation or forcing several pages to compete for the same intent.
NEXT IN THE CLUSTER: Article 11: How Do You Map Keywords to Products, Collections and Content?
Frequently asked questions
Ecommerce keyword research FAQs
What is the best keyword research tool for ecommerce SEO?
There is no single best tool. Search Console provides real query data from your site, Keyword Planner helps expand ideas and estimate demand, Google Trends adds seasonality and regional context, and third-party tools can broaden competitor and keyword research.
Should I always target the keyword with the highest search volume?
No. Commercial relevance, search intent, page fit, competition, stock and business value can make a lower-volume keyword more useful than a broad high-volume term.
How many keywords should an ecommerce page target?
Think in terms of one primary intent and a cluster of closely related searches rather than a fixed keyword count. A page can naturally rank for many variations when they describe the same need.
Are zero-volume keywords worth targeting?
Sometimes. Tools can miss very specific or new searches, and Search Console may reveal real impressions for phrases with little or no third-party volume. Use commercial relevance and evidence from related demand rather than a hard zero-volume rule.
Should product pages and collection pages target the same keywords?
Usually they should have different primary roles. Broad product-category searches normally fit collections, while exact product, model and variant searches fit product pages.
How do I know whether a keyword needs a new page?
Check whether the intent is materially different from existing pages, whether the catalogue can support the theme, whether Google rewards a distinct page type and whether creating the page would add useful value rather than duplication.
Can AI tools replace keyword research tools?
AI can help brainstorm, classify and cluster ideas, but it should not be treated as a source of verified search volume or live SERP evidence. Validate important decisions with Search Console, search results, Trends, keyword datasets and commercial data.
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