Keywords List for SEO: How to Develop One (Tips from Reddit)

Keywords List for SEO: How to Develop One (Tips from Reddit)

Note: This article summarizes and synthesizes a Reddit discussion on developing a keywords list for SEO and adds expert commentary and practical steps. It paraphrases community tips and goes beyond the thread with advanced strategies.

Why a keywords list for SEO matters

A solid keywords list is the foundation of content strategy, on-page optimization, PPC targeting, and technical SEO. Reddit users in the thread agreed that a good list does more than capture volume — it maps intent, informs content types, and links keywords to business outcomes.

Reddit consensus: core principles people agreed on

• Start with seed keywords: Everyone recommended beginning with a handful of obvious terms tied to your product, service, or niche.
• Use tools to expand: Keyword Planner, Ahrefs, SEMrush, Moz, Ubersuggest, and free sources like Google Autocomplete and People Also Ask were commonly suggested for scaling the list.
• Prioritize intent over volume: Search intent (informational, navigational, transactional) was repeatedly flagged as more important than raw volume.
• Leverage your own data: Google Search Console, site search logs, and analytics were widely recommended to find existing queries that already drive impressions or clicks.
• Group and map: Users emphasized clustering keywords by topic and mapping them to specific pages or content types rather than treating each keyword independently.

Areas of disagreement and nuance

While the broad approach is common, Redditors had several debates worth noting:

• Size of the list: Some advocate for massive lists (tens of thousands) to capture long-tail opportunities; others warn that overly large lists create noise and recommend a lean, prioritized set.
• Tools vs. manual research: Several contributors trusted tools heavily, while others stressed manual SERP research, competitor analysis, and reading online communities to capture conversational language.
• LSI and semantic keywords: Some users recommended using latent semantic indexing (LSI) terms; others said focusing on entities and topical relevance is more practical than hunting for “LSI” keywords.
• Local vs. global focus: SEOs working local niches emphasized location modifiers and Google My Business signals; broader-market SEOs suggested prioritizing by global search intent and SERP features.

Concrete tips pulled from the thread

• Start with customer language: mine support tickets, reviews, and forum threads to capture how people phrase problems.
• Use Google Search Console first: export queries already showing impressions — these are low-hanging fruit.
• Combine multiple tools: cross-reference volume, difficulty, and CPC data to create a fuller picture.
• Check SERP features: look for featured snippets, People Also Ask, shopping panels — these change how you approach a keyword.
• Group keywords into topic clusters and map them to a content type (blog post, guide, product page, FAQ).
• Filter by conversion intent: mark which keywords signal purchase intent versus research intent and prioritize accordingly.
• Automate repetitive tasks: use CSVs, APIs, and templates for importing/exporting data between tools if you manage large lists.
• Iterate and prune: monthly or quarterly reviews to remove irrelevant terms and add new opportunities.

Step-by-step process to build your keywords list for SEO

Below is a practical workflow that synthesizes Reddit suggestions and industry best practices.

1. Define goals and buyer stages

• Decide whether your priority is traffic, leads, or sales.
• Label keywords by funnel stage: Awareness, Consideration, Decision.

2. Seed keyword generation

• Brainstorm 10–20 core terms tied to your product/service.
• Pull customer-facing language from reviews, support tickets, sales calls, and community forums.

3. Expand using tools and SERP mining

• Run seeds through tools: Keyword Planner, Ahrefs, SEMrush, Moz, Ubersuggest, AnswerThePublic.
• Use Google Autocomplete and “Searches related to” for conversational variants.
• Manually inspect SERPs for each target keyword to note intent and SERP features.

4. Add first-party data

• Export queries from Google Search Console and merge with the list.
• Use site search and analytics to find internal search terms visitors use.

5. Score and prioritize

Create columns for: volume, difficulty, CPC (optional), intent, current rank (if any), and business value. Then calculate an opportunity score to prioritize.

6. Cluster and map to content

• Group similar keywords into clusters (by topic and intent).
• Map each cluster to the best content format and a target URL (or new content idea).

7. Execute, track, and refine

• Produce content using the target keywords and semantic variations.
• Track rankings, impressions, and conversions to refine prioritization.
• Regularly prune low-potential keywords and add emerging queries.

Expert Insight: Creating an opportunity score

Redditors often recommended heuristics; here’s a reproducible scoring model you can use to rank keywords objectively:

• Opportunity Score = (Estimated Monthly Traffic Potential * Conversion Intent Weight) / Difficulty
• Estimated Monthly Traffic Potential = volume * expected CTR (use position-based CTR models).
• Conversion Intent Weight = 1.0 for transactional, 0.6 for consideration, 0.3 for informational (adjust to your business).
• Difficulty = tool-provided difficulty score or a composite of backlink/authority metrics.

This lets you compare very different keywords on a consistent scale and prioritize those with the best business upside.

Expert Insight: Scale with semantic clustering and embeddings

Beyond basic clustering, use semantic embeddings (via tools or libraries) to group keywords by meaning, not just shared tokens. This reduces duplication and helps you design content hubs:

• Generate vector embeddings for each keyword phrase (OpenAI, spaCy, or other models).
• Use clustering (k-means, hierarchical) to discover topical groups that human review can validate.
• Map clusters to pillar pages and supporting content to capture topical authority and internal linking benefits.

This approach outperforms simple keyword matching because it accounts for synonyms, user intent nuances, and semantic relationships.

Tips for common scenarios

• Small local business: Prioritize local modifiers, GMB optimization, and low-difficulty long-tail keywords tied to neighborhoods or service+location queries.
• Large ecommerce site: Focus on product-level terms, category-level intent, negative keyword lists for paid search, and use log files to spot SKU-specific queries.
• Content-heavy blogs: Create pillar pages and cluster content around high-value topics; use GSC to expand coverage of topics where you already rank.

Common pitfalls to avoid

• Chasing high volume keywords without regard for intent — they often convert poorly.
• Building a list without mapping to content or business goals — results in orphaned keywords that never impact metrics.
• Relying on a single tool — cross-check data to avoid blind spots.
• Ignoring seasonal trends — use historical data to plan content calendars around peaks.

Final Takeaway

Developing a practical keywords list for SEO is a mix of data-driven expansion, intent-focused prioritization, and consistent maintenance. Reddit users largely agree on starting with seed keywords, using a variety of tools, and leveraging first-party data like Google Search Console. The real advantage comes from clustering keywords by topic/intent, mapping them to specific content, and using objective scoring to prioritize work. Layer in semantic techniques and automation to scale without sacrificing relevance.

Read the full Reddit discussion here.