Long tail SEO: long-tail keyword strategy for e-commerce

Long tail SEO refers to the strategy of ranking for long, specific search queries with individually low search volume, but whose combined total represents the majority of search traffic. For an e-commerce store, this is the difference between targeting "shoes" (impossible to rank for, global competition) and "women's waterproof running sneakers size 7 black" (highly targeted, limited competition, high purchase intent). The long tail is often the most effective and accessible SEO strategy for independent e-commerce stores.

The long tail distribution: 80% of traffic comes from specific queries

The concept of the long tail was popularised by Chris Anderson in his book "The Long Tail" (2006) in reference to niche markets. Applied to SEO, it describes the distribution of search volumes: a few hundred generic queries ("shoes", "dress", "bicycle") each concentrate millions of monthly searches, but represent less than 20% of all searches. The remaining 80% come from hundreds of thousands of specific queries — with individual volumes of 10 to 500 searches/month but a much higher purchase intent.

For an e-commerce store, long tail queries offer several decisive advantages. Competition is low: major platforms (Amazon, eBay, Walmart) rarely optimise their product pages for ultra-specific queries. The conversion rate is high: someone searching for "adult electric bike 25km/h with pannier bag" is in an advanced buying phase. And these queries are scalable: a store with 500 products can target thousands of long tail queries with no direct competition.

The 4 types of long tail queries in e-commerce

Specific product queries: include the exact model, colour, size or reference. Example: "Nike Air Max 90 men's white black size 10". Maximum conversion, low competition.
Purchase intent queries: include intent modifiers. Example: "best automatic bean-to-cup coffee machine 2026", "electric scooter comparison adult 30km range". Moderate competition, strong commercial intent.
Comparison queries: "[product A] vs [product B]", "alternative to [product]" or "[product] review". Targeted by comparison pages or e-commerce blog articles.
Problem/solution queries: "how to choose [product]", "what size for [product]", "[product] suitable for [use]". Targeted by editorial content that then leads to product pages.

How to identify relevant long tail keywords

Identifying long tail keywords relies on several complementary sources. Standard keyword research tools (Google Keyword Planner, Ahrefs, SEMrush, Ubersuggest) let you explore variations of a main query and measure their volume. Google's autocomplete is a goldmine: start typing your main product in the search bar to reveal the variations most searched by real users.

Google Search Console is probably the most valuable tool: in the Performance > Queries section, it lists all the queries for which your site has already been displayed. Specific queries with a good number of impressions but a mediocre position (between 8 and 30) are the best candidates for optimisation — you are already visible, you just need to improve the relevant pages to reach the top positions.

The 3-word rule

In practice, the boundary between short tail and long tail often lies at 3 words. A 1–2 word query is generally short tail (high volume, strong competition, vague intent). From 3 words onwards, you enter the long tail: volume drops but intent sharpens. At 4–5 words, this is sometimes referred to as "very long tail" with near-transactional intent.

Applying the long tail strategy to a PrestaShop store

In practice, long tail SEO in e-commerce is deployed across three types of pages. Product pages are the most natural ground: the title and meta description should include the precise specifications (colour, size, material, use case) that buyers use in their searches. Category pages with filters allow you to create static pages optimised for specific combinations ("navy blue evening dresses size 12") that match high-volume long tail searches.

Editorial content (buying guides, comparisons, blog articles) captures the long tail informational queries that precede a purchase. A bicycle store that publishes "complete guide to choosing an electric bike in 2026" can attract several thousand qualified monthly visitors on queries that product pages alone would never reach.

🎯

Purchase intent

Long tail queries are 3 to 5× more likely to convert into a purchase than generic queries.

📉

Low competition

Large e-commerce players rarely optimise for ultra-specific queries: an opportunity for independent stores.

📈

Cumulative volume

Thousands of queries at 50 searches/month represent more total traffic than a few queries at 1,000/month.

The long tail in Google Images

Google Images is a particularly exploitable long tail channel for e-commerce. Users formulate very specific and visual queries there: "women's ankle boot block heel brown leather autumn", "industrial style coffee table wood and metal". Optimising alt texts, file names and structured data for product images allows you to capture this high-commercial-intent traffic from Google Images.

Lexiik contributes to this strategy in two ways. By serving images from a high-performance CDN, product pages achieve better performance (LCP in particular), which supports better overall rankings — including on long tail queries. And images served with stable URLs and correct cache headers are better indexed in Google Images.

Boost your product image SEO