Find Low Competition Keywords: Proven Methods from Reddit

Introduction — based on Reddit discussions

This guide synthesizes and expands on a popular Reddit thread where SEO practitioners shared real tactics to find low competition keywords. I paraphrased the community’s consensus, highlighted the disagreements, and added expert-level workflows to make this a practical, repeatable process you can use today.

Reddit consensus: the core takeaways

Don’t trust KD as the only metric. Most Redditors agreed keyword difficulty scores (Ahrefs/SEMrush/KWFinder) are helpful but imperfect. They treat KD as a filter, not a decision-maker.
Look at real SERPs. Manual SERP analysis — checking top 10 results for freshness, content depth, and backlink profiles — was recommended as the decisive step.
Long-tail & intent-first approach. Low competition often lives in long-tail, question-based queries or niche modifiers (“for beginners”, “near me”, “2025”), not one-word seeds.
Use multiple sources for seed ideas. Forums (including Reddit), YouTube, Amazon, Google PAA (People Also Ask), and Google Search Console were cited as high-quality seed sources.
Volume vs. opportunity trade-off. Low volume keywords can still be valuable if intent is commercial or fits a funnel stage. Several commenters preferred targeting many low-volume keywords inside a niche cluster.

Where Redditors disagreed

Minimum volume threshold. Some said ignore keywords with <50 monthly searches; others routinely published content for queries under 20 searches if topical authority could be built.
Backlinks vs. content depth. A faction insisted backlinks are the primary barrier to entry; others argued weak content or outdated pages are the more exploitable weakness.
Tools vs. manual research. Some users leaned on paid tools and APIs to scale keyword discovery; others favored manual discovery through forums and SERPs to avoid tool bias.

Practical, Reddit-backed process to find low competition keywords

Below is a step-by-step workflow that synthesizes community tips and adds an expert decision layer to help you prioritize the best opportunities.

1) Build seed lists from diverse sources

Forums & social: extract questions and phrasing from Reddit, Quora, and niche communities.
Google: use Autocomplete, “People Also Ask”, Related Searches, and “searches related to” at the bottom of SERPs.
Content platforms: Amazon, YouTube, and Etsy (for product phrases) are gold mines for buyer language and niche modifiers.
Your own data: Google Search Console and Google Analytics to surface queries already getting impressions but low clicks.

2) Expand with keyword tools

Feed seeds into one or more keyword tools (Ahrefs, SEMrush, Moz, KWFinder, Ubersuggest, Keyword Planner). Expand to get related queries, question variations, and metrics like volume, CPC, and KD.

3) Filter smartly — not just by KD

Set a loose KD filter (example: KD < 20) to reduce noise, but keep exceptions that look promising.
Filter volume pragmatically: for niche sites, volume > 10–20 may be acceptable; for broader sites, aim for 50+.
Use CPC as a proxy for commercial intent — higher CPC often signals buyer intent and revenue potential.

4) SERP quality check (the Redditors’ decisive step)

Open the top 10 results for each candidate keyword and evaluate:

Content depth: Are top pages thin or generic?
Freshness: Are the results old or outdated?
Backlinks & authority: Do ranking pages have low referring domains?
Format match: Does the SERP show a featured snippet, videos, forum posts, or product listings? A SERP dominated by low-authority forum results often means opportunity.

5) Prioritize by traffic potential and strategic fit

Rank candidates using a simple score: search volume x intent multiplier / average top-10 referring domains. Prioritize queries where you can produce a better match for intent than the current results.

Specific tips shared on Reddit (and why they work)

Use “site:” and “intitle:” operators to find content gaps (e.g., site:example.com “topic”). Useful to discover where competitors missed a topic angle.
Target PAA and featured snippet formats — write concise, structured answers to capture snippets that dramatically boost click-through rates.
Search engine timeline filters (Tools > Any time) to find outdated posts you can outrank with updated content.
Leverage local modifiers (“near me”, city names) for lower competition and high conversion in local niches.
Answer niche subquestions — many Redditors recommended mining the “Why” and “How” versions of a query for easier wins.

Expert Insight: What KD scores miss (and how to replace them)

Keyword Difficulty scores compress many signals into one number, which is convenient but risky. KD typically weights backlinks heavily. However, competition is multidimensional:

Content relevance: How well do current pages satisfy the search intent?
Topical authority: Are the competing sites recognized authorities in the niche?
SERP features: If the SERP is dominated by video or shopping results, organic text results will have different dynamics.
User experience & E-E-A-T: Pages with poor UX or weak expertise are easier to outrank over time.

Replace blind KD reliance with a quick scoring rubric: rate top 10 pages on backlinks (0–5), content depth (0–5), freshness (0–3), and intent match (0–5). Sum the values — lower totals indicate easier opportunities. This systematic approach is what many experienced Redditors implicitly used when they said “look at the SERP”.

Expert Insight: Scaling discovery into a repeatable system

If you need to scale beyond manual checks, build a lightweight pipeline:

Collect seeds from GSC, forums, and Autocomplete into a spreadsheet.
Use a keyword tool API (Ahrefs/SEMrush) to bulk expand and pull metrics (volume, KD, CPC).
Write a script to fetch top-10 SERP URLs and scrape simple signals: domain authority, number of referring domains, publish date, word count.
Score and rank candidates automatically using the rubric above, then export a quarterly content plan of prioritized keywords.

This approach combines Reddit’s manual instincts with automation so you can act on more opportunities faster.

Content strategy once you have low-competition keywords

Create intent-aligned content: If a query is transactional, use product/comparison pages; if informational, write comprehensive how-to guides that answer the question in both short and long forms.
Cluster related long-tails: Instead of one-off posts, build topic clusters and pillar pages to concentrate internal links and topical authority.
Target SERP features: Use lists, tables, step-by-step instructions, and schema to win snippets and PAA boxes.
Build a small backlink plan: Rather than chasing high-authority links for every article, promote via niche communities, relevant forums, and internal linking to raise authority systematically.
Monitor & iterate: Use GSC and analytics to track ranking movement and expand on pages that show initial traction.

Checklist: Quick filters you can use right now

Seed from Reddit threads and GSC queries.
Expand with a keyword tool and keep modifiers like “how”, “vs”, “for”, “near me”.
Filter KD loosely (e.g., <20) and volume threshold by niche.
Manually review SERP for content depth, backlinks, and format.
Score the opportunity and prioritize by intent-weighted traffic potential.

Final Takeaway

Reddit users converged on a practical truth: tools help you find candidates, but human SERP analysis and intent understanding win rankings. To find low competition keywords consistently, combine diverse seed sources (forums, GSC, Autocomplete), use tools to expand and filter, and apply a reproducible SERP-quality rubric to prioritize. Build content that matches intent, aim for SERP features, and scale with lightweight automation when you have to.

Read the full Reddit discussion here.