How to Find Long Tail Keywords with Low SEO Difficulty
·10 min read
Long tail keywords are specific, multi-word search phrases that typically attract lower search volume but face significantly less competition. When you focus on keywords with low SEO difficulty scores, you unlock faster ranking opportunities and more qualified traffic. An ecommerce keyword research tool mines real search demand data and scores each keyword by both intent and difficulty, turning your research into a ready-to-publish content plan.
Understanding keyword difficulty and search intent
Keyword difficulty measures how hard it is to rank for a specific search term on the first page of Google. Most tools calculate this score by analyzing the authority and topical relevance of the pages currently ranking in the top 10 search results. A keyword with a difficulty score below 30 is generally considered low difficulty, though this threshold varies by your own domain rating and backlink profile.
Search intent reveals what users actually want when they type a query. A transactional query like "buy organic coffee beans" indicates purchase readiness. An informational intent keyword like "how to brew cold brew coffee" attracts readers seeking knowledge. For ecommerce brands, targeting long tail keywords with transactional intent and low keyword difficulty creates a winning combination: fewer competing pages, clearer buyer signals, and faster ranking potential.
The relationship between search volume and difficulty is not linear. A keyword with 200 monthly searches might have a difficulty score of 15, while a 300-search keyword could score 45. The content quality and link authority of the top 10 results matters more than volume alone. This is why an ecommerce keyword research tool separates true difficulty from raw volume figures.
Methods for finding long tail keywords with low difficulty
Competitor mining and keyword clustering. Start by identifying 5 to 10 direct competitors in your space. Enter their domain into your research tool and extract the keywords they rank for in positions 6 through 30, where they hold visible organic impressions but may not yet dominate. These positions reveal keywords with moderate difficulty that competitors have already validated. Filter for keywords with fewer than 500 monthly searches, as long tail terrain typically begins below this threshold.
Use keyword clustering to group related long tail terms together. Terms like "organic coffee beans Canada," "fair trade coffee Canada," and "single origin coffee Canada" cluster around a geographic and topical hub. By identifying these clusters, you avoid wasting content on redundant terms and build topical authority instead. Semantic hubs let you write one comprehensive guide and support it with internal linking to product detail pages and collection pages, multiplying the value of each piece.
Search suggestion mining and YouTube autocomplete. Google's search suggestions, Amazon search bars, YouTube autocomplete, and eBay search suggestions all reveal real user queries with real search demand. Type a seed keyword into YouTube's search box and note the auto-suggestions that appear. These reflect actual user behavior and searches happen frequently enough to trigger autocomplete, yet many of them carry low keyword difficulty because they are newer or more specific than traditional head terms.
Record 50 to 100 suggestions across these platforms. Many will be long tail keywords you never would have found through conventional research. The advantage is that these come directly from user behavior rather than algorithmic ranking data. When you combine them with a keyword research tool, you verify their search volume and difficulty, then decide which merit content investment.
Long tail keyword generators and bulk analysis. A dedicated ecommerce keyword research tool accelerates the process by allowing bulk uploads of competitor keywords or seed terms. You can upload 1,000 keywords at once and receive difficulty and volume data for each. Most tools also offer bulk export functionality so you can load results into a spreadsheet, sort by difficulty ascending, and immediately identify your easiest wins.
Filter your results using these criteria: keyword difficulty below 25, search volume between 50 and 500 monthly searches, and transactional intent (indicated by words like "buy," "price," "deals," "review," or your product category name). This combination typically yields 30 to 100 genuinely low-competition opportunities per competitor domain analysis.
Scoring keywords for ecommerce opportunity
Not all low difficulty keywords deserve equal attention. Create a simple scoring matrix that rates each candidate on three axes: search volume (higher is better, but floor at 50 searches per month), keyword difficulty (lower is better), and commercial intent (highest priority). A keyword with 80 monthly searches, a difficulty of 12, and explicit buying signals scores higher than a 120-search informational keyword with a difficulty of 18.
Examine the current top 10 search results for your target keyword. If the top 3 results are all authoritative domains (domain rating above 50) or content mills, the difficulty score may underestimate the real barrier. Conversely, if the top 10 pages are thin, outdated, or poorly optimized, you can often rank faster than the raw score suggests. Use this human assessment to adjust your priority ranking.
Document your long tail keyword selections in a content plan that maps each keyword to a product detail page, collection page, or blog post type. This transforms raw keyword data into an actionable roadmap. For example, a Shopify store selling yoga mats might target "eco-friendly yoga mat for beginners" on a product comparison page, and "how to choose a yoga mat thickness" on a blog post designed to capture informational intent and funnel readers toward the product pages via internal linking.
Building content and internal linking around long tail wins
Once you identify low difficulty long tail keywords, content structure determines whether you actually rank. Each keyword should map to a specific page type. Transactional long tail keywords like "cotton pillow cases queen size organic" suit product detail pages. Informational long tail keywords like "best fabrics for sensitive skin" belong on blog posts with internal links pointing to relevant product pages.
Internal linking with anchor text directly naming your target keyword is the most underutilized tactic in ecommerce SEO. When you write a blog post about fabric care, embed a natural link with anchor text "organic cotton pillow cases" pointing to your product page. This signals topical relevance and distributes link authority from your content hub toward product pages that convert.
Build a topical map that shows how your long tail keywords relate to one another and to your core product categories. If you have 15 long tail keywords related to pillow materials, feature them in a central pillar article that also links to a detailed collection page, product detail pages, and buying guides. This architecture is called a semantic hub, and it compounds your ranking power by showing Google that your site owns the entire topic.
Your XML sitemap should include all product detail pages, collection pages, and content pages targeting long tail keywords. Submit it to Google Search Console to improve crawl budget efficiency. A clear site structure with short crawl depth from the homepage to money pages ensures Google indexes your low difficulty keyword targets quickly.
Measuring and refining your long tail strategy
Monitor your long tail keywords using Google Search Console data. Focus on organic impressions and click-through rate rather than position alone. A keyword with 50 monthly impressions but a 0.5% click-through rate indicates poor title tag or meta description performance, even if you rank in position 4 or 5. Rewrite the title and snippet to mention the specific benefit or product type.
Revisit your long tail keyword research quarterly. Search demand and competitive landscape shift constantly. A keyword with 15 difficulty today might spike to 35 within four months as larger competitors publish content. Conversely, new long tail angles emerge as product trends shift and user behavior changes. Quarterly updates keep your content plan aligned with actual search demand and difficulty.
Long tail keywords are not a one-time win. They require the same content quality, structured data markup, and Core Web Vitals optimization as any other keyword. Ensure your product pages include JSON-LD schema for product pricing, availability, and reviews. Use an XML sitemap with proper structured data so search results can display your price, stock status, and star rating. These SERP features increase click-through rate on low volume keywords where every click matters to conversion rate.
For a full overview of how to execute ecommerce keyword research at scale, see our guide on the ecommerce keyword research tool.
FAQ ecommerce keyword research tool
What search volume is considered long tail?
Long tail keywords typically receive fewer than 500 monthly searches. The exact threshold depends on your industry and market. In broader categories like "clothing," a 400-search keyword is long tail. In narrow niches like "fishing tackle for saltwater catfish," a 60-search keyword might be midrange. The defining characteristic is specificity rather than an absolute volume number. Most long tail keywords cluster between 10 and 300 monthly searches, with many valuable ecommerce long tail terms receiving only 20 to 80 searches monthly but showing explicit buying intent.
How low is low enough for keyword difficulty in ecommerce?
For ecommerce sites with domain rating below 30, target keywords with a difficulty score below 20. If your domain rating sits between 30 and 50, aim for keywords below 25 difficulty. Established ecommerce sites with domain rating above 50 can compete on keywords up to difficulty 35. Remember that keyword difficulty is relative to your own authority. A 25-difficulty keyword might be unachievable if you have zero backlinks, but highly winnable if you have 50 referring domains. Always compare the top 10 ranking pages to your own backlink and domain authority before committing resources.
Can long tail keywords convert better than short tail keywords?
Yes, long tail keywords typically show higher conversion rates because they signal clearer purchase intent. A user searching "yoga mat" is browsing. A user searching "antimicrobial yoga mat 6mm thickness" is comparing specific options and close to purchase. However, long tail conversion advantage only materializes if your page matches the search intent precisely. A product detail page optimized for "yoga mat" might convert at 0.8%, while the same page targeting "yoga mat" could convert at 2.1%. The long tail keyword reduces traffic volume but increases per-visit conversion probability.
How do I find long tail keywords my competitors haven't targeted?
Use competitor keyword mining to identify all keywords they rank for, then cross-reference those with keywords in YouTube autocomplete and Amazon search suggestions that do not appear in competitor data. The gap represents untapped long tail angles. You can also use topical mapping to identify long tail keyword variations around successful competitor keywords. If a competitor ranks for "organic coffee beans," search for "organic coffee beans without pesticides," "fair trade organic coffee beans," and "shade grown organic coffee beans" to find related long tail variants they may have missed.
What is the relationship between keyword difficulty and competition?
Keyword difficulty measures the strength of pages currently ranking, not the total number of people targeting that keyword. A 15-difficulty keyword might have fewer than 10 content pieces targeting it directly, while a 40-difficulty keyword might have 500 pages competing. Lower difficulty keywords generally face less active competition from SEO professionals and paid advertisers. This means you can often rank faster and the cost per click in paid search is lower. However, low difficulty does not guarantee low-value keywords, which is why search volume and transactional intent must inform your selection alongside difficulty.
Should I target long tail keywords with zero search volume?
Avoid keywords with reported zero search volume in your keyword research tool, as they often indicate no real demand or insufficient search frequency for the tool to measure. However, if you find keywords with estimated 10 to 30 monthly searches that fit your product perfectly and carry low difficulty, testing one or two is justified. Publish content on these micro-long-tail keywords to capture early demand as product categories evolve. Once you rank, Google Search Console will show actual search impressions and help you refine your understanding of what users are searching for in your niche.
How many long tail keywords should I target per month?
A sustainable pace depends on your team size and content capacity. A solo ecommerce operator might publish one blog post and one optimized product page targeting long tail keywords per week, yielding 8 to 10 new targets monthly. A team of two to three content creators can handle 20 to 30 new long tail targets monthly. Quality always outweighs quantity. One well-optimized page targeting a 50-search-volume long tail keyword will deliver more cumulative traffic and conversion value than five pages with thin content on the same topic. Focus on publishing the best page Google has seen for each long tail keyword you target.
Can I use generative AI to write content for long tail keywords?
Yes, generative AI can accelerate content production for long tail keywords, especially informational and comparison content. However, AI-generated content alone often lacks the topical authority, specificity, and human expertise that Google rewards. Use retrieval-augmented generation to provide your AI system with data about your products, competitor benchmarks, and user reviews before generating drafts. Then apply human-in-the-loop editing to add original data points, case studies, and expert commentary. This approach yields content that ranks better than either pure AI or pure human writing, while reducing production time by 40 to 60%.
