Multilingual Keyword Research for E-commerce: A Practical Method

Most Shopify merchants expanding internationally make the same expensive mistake: they translate their existing English keywords instead of researching how people actually search in each target language. These are not the same thing — and the gap between them is where international traffic gets lost.

This guide walks you through a repeatable, market-by-market process for multilingual keyword research that produces real, rankable terms rather than literal translations of your English SEO strategy.

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Why "Translate Your Keywords" Is the Wrong Starting Point

A direct keyword translation assumes that search behavior maps cleanly across languages. It rarely does. A French shopper searching for running shoes might use "chaussures de running" or "baskets de sport" — but if you only optimized for the direct translation of "running shoes," you'd miss "chaussures de trail" entirely, which may have far higher commercial intent in a French market dominated by outdoor enthusiasts.

The same product, different country, different vocabulary, different intent. Multilingual keyword research means starting fresh in each market, using the translated content as your foundation but letting local search data guide what you actually optimize for.

For a broader look at how this fits into a full international SEO strategy, see Shopify Multilingual SEO: How to Rank in Every Language.

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Step 1: Define Your Markets Before Your Keywords

Before opening any keyword tool, answer these two questions for each market:

• What language do people search in? In Switzerland, that might be German, French, or Italian — sometimes all three for the same store.
• Which search engine dominates? This is a step many guides skip entirely. Google is not the default everywhere:
  • South Korea: Naver holds roughly 60% of search market share. Naver's keyword tool (Naver DataLab) is your primary source, not Google Keyword Planner.
  • Russia and CIS countries: Yandex remains dominant in Russia; Yandex Wordstat is the authoritative keyword volume tool for those markets.
  • China: Baidu controls the mainland market. Baidu Index provides trend data, though access for non-Chinese businesses is constrained. If China is your target, budget for a local SEO partner.
  • Czech Republic, Poland: Google dominates, but local forums and product review platforms shape vocabulary in ways that pure volume data misses.

Skipping this step and defaulting to Google data for Korean or Russian markets will produce keyword lists that are partially or entirely wrong for those audiences.

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Step 2: Use the Right Tools — and Know Their Limitations

Google Keyword Planner

GKP lets you filter by country and language, but its language filter is notoriously unreliable for non-English markets. In practice, it often surfaces volume data that blends linguistic variants, mistranslates intent, or returns sparse results for lower-volume languages. Treat GKP as a rough directional signal in non-English markets, not a primary source.

One common workaround is appending &gl=FR&hl=fr to Google Search URLs to localize results by country and interface language. This helps — but &hl= alone does not fully replicate what a user with a French residential IP sees. Search results are personalized by location at a network level, not just by header parameter. For genuinely localized SERP data, a residential proxy service or a VPN with a local exit node in the target country is more reliable than URL parameters.

Ahrefs and Semrush (Recommended Primary Tools)

For non-English markets, Ahrefs Keywords Explorer and Semrush's Keyword Magic Tool with country-level filtering are substantially more reliable than GKP. Both pull from clickstream data rather than Google's own interface, which produces more accurate volume estimates for languages like Dutch, Polish, Swedish, and Portuguese. Set the database to the specific country (e.g., FR for France rather than a global French filter) to get the most relevant results.

Market-Specific Tools

Market	Primary Tool
South Korea	Naver DataLab, Naver Keyword Tool
Russia/CIS	Yandex Wordstat
China (Baidu)	Baidu Index, local SEO partner
Germany, France, Spain	Ahrefs/Semrush country databases
Japan	Google JP + Ubersuggest JP

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Step 3: Build Seed Keywords from Native Sources

Don't start with your English keyword list. Start with:

1. Competitor product pages in the target language — find local competitors via Ahrefs Site Explorer, filter organic keywords by country, and pull their top-ranking product and category terms.
2. Amazon or local marketplace autocomplete — Amazon.fr, Amazon.de, Bol.com (Netherlands), Allegro (Poland), and Rakuten (Japan) all surface real buyer vocabulary. Type your product category into the search bar and screenshot every autocomplete suggestion.
3. Google Search Console data — if you already have any traffic from a target country, GSC will show you the actual queries people used, which is more valuable than any modeled volume estimate.
4. Google Autocomplete in the target language — open an incognito window, set your browser language to the target locale, and systematically type your product name with every letter of the alphabet appended. This surfaces long-tail terms that volume tools undercount.

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Step 4: Validate Search Intent by SERP Type

A keyword with 2,000 monthly searches in German is worthless if the SERP is dominated by news articles or Wikipedia when you're selling a product. For every candidate keyword, manually check the first-page SERP in the target locale:

• Transactional SERPs (product pages, shop carousels, ads): strong commercial signal, worth targeting with product and collection pages.
• Informational SERPs (blog posts, guides): target with translated articles or buying guides, not product pages.
• Mixed SERPs: often the most competitive; consider whether a blog post with an embedded product link is the right content type.

For Shopify specifically, collection pages tend to rank well for broad category terms in any language. See How to Translate Shopify Collections (and Why It Matters for SEO) for guidance on optimizing those pages once you have your keyword targets.

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Step 5: Prioritize with a Scored Matrix — A Real Example

Generic prioritization frameworks tell you to score by volume, difficulty, and relevance. Here's what that looks like applied to a specific case: a Shopify store selling natural skincare products expanding into the German market.

Five candidate keywords were scored on three dimensions (1–5 scale each), with relevance weighted at 2x because mistargeted traffic converts at near zero in e-commerce:

Keyword (DE)	Monthly Volume (Ahrefs DE)	Volume Score	KD Score	Relevance Score (×2)	Total /20
naturkosmetik kaufen	8,100	5	2 (KD 61)	5 × 2 = 10	17
vegane gesichtscreme	2,400	4	4 (KD 38)	5 × 2 = 10	18
bio hautpflege	5,400	4	2 (KD 58)	4 × 2 = 8	14
gesichtscreme ohne parfum	880	2	5 (KD 22)	5 × 2 = 10	17
naturkosmetik set geschenk	590	2	5 (KD 19)	4 × 2 = 8	15

Result: "vegane gesichtscreme" scores highest because it has meaningful volume, achievable difficulty, and precise transactional intent that matches the product catalog. "bio hautpflege" — despite higher volume — scores lower because the broad informational intent makes it harder to compete with editorial content ranking for that term.

This matrix won't work mechanically across all categories, but the principle holds: in multilingual e-commerce, relevance weight should be higher than in monolingual research because you have less margin for ranking on traffic that won't convert due to intent mismatch.

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Step 6: Map Keywords to Content Types and Translate Accurately

Once you have prioritized keywords per market, map each to a specific Shopify content type:

• High-intent, specific product terms → product page title and meta description
• Category terms → collection page H1 and meta
• Informational long-tail → blog posts or FAQ pages

The critical final step is ensuring your translations actually use these keywords — not synonyms, not approximate translations, but the exact phrases your research identified. This is where a glossary becomes essential: lock in the exact local term for your key product category so that every translated product description, collection page, and meta field uses consistent terminology.

StoreLingo's built-in glossary feature lets you pin these terms so they're preserved consistently across all AI-translated content — meaning the keyword work you did in Step 3 isn't undone by a translation that substitutes a different regional variant of the same word. For guidance on getting the full translation workflow right, The Complete Shopify Translation Checklist for Going Multilingual covers every content type you'll need to optimize.

Add StoreLingo on the Shopify App Store →

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Step 7: Set Up Tracking Before You Publish

Keyword research has no feedback loop unless you can measure ranking movement per language. Before publishing translated pages:

1. Add each target market as a separate property in Google Search Console (or verify your Shopify Markets subfolders/subdomains are being crawled correctly — see Hreflang on Shopify: The Complete Guide to International SEO Tags for the technical setup).
2. Create a keyword tracking project in Ahrefs or Semrush with country set to each target market.
3. Note your baseline rankings at launch date.

Expect a 6–12 week lag before multilingual pages accumulate ranking data. Pages that aren't indexed at all usually indicate a hreflang or sitemap issue, not a content problem.

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FAQ

Can I do multilingual keyword research without speaking the language? Yes, but you need to compensate for the gap systematically. Use Ahrefs or Semrush with country-specific databases to pull actual ranking pages, then run those competitor URLs through a site content analysis to extract recurring terms. For validation, hire a native-speaking freelancer via Upwork or Contra and give them a structured brief: ask them to review your top 10 candidate keywords and flag any that feel unnatural, carry unintended connotations, or are regional variants that wouldn't be used by your target demographic. A 1-hour brief review costs $20–50 and prevents months of ranking on the wrong terms.

How often should I refresh my multilingual keyword research? Refresh core category keywords annually and monitor for seasonal shifts quarterly using Google Trends filtered by country. More urgently, re-run research any time you add a new product category or expand into a new market — search vocabulary for new product types (e.g., emerging wellness ingredients, new device categories) shifts faster than established categories and last year's data may already be stale.

Should I target the same keywords across all languages, or treat each market independently? Treat each market independently. Even languages with high overlap — like European Spanish and Latin American Spanish — show meaningful divergence in e-commerce vocabulary, brand familiarity, and search intent. A keyword that drives strong commercial traffic in Spain may be informational in Mexico, or simply unused. The only shared input across markets should be your product category definitions; the keyword research itself should start from zero in each locale.