How can you find and filter related keywords from existing topics or keywords?

To find related keywords from existing topics, start by choosing seed keywords based on your products, services, or customer questions. Then use keyword tools to explore related subtopics, questions, and specific needs. When filtering, first check whether each term’s meaning and search intent fit your business, then compare search volume, ranking difficulty, and trends. Do not simply choose the terms with the highest search volume or assume that every suggestion a tool provides is worth targeting.

Define seed keywords around customer needs

Seed keywords are the starting point for further research and need not be limited to product names. Semrush’s research guide recommends first considering what problems your business solves and how potential customers might search. For example, a technology publication could start with technology news, product reviews, and buying guides, research related terms for each, and then narrow the scope using topic groups and subgroups.

If you already have a clear topic, you can expand it into specific questions. An Ahrefs tutorial by yesharris uses “wisdom teeth” as an example, suggesting terms such as “what to eat after wisdom tooth removal,” “how long does pain last after wisdom tooth removal,” and “wisdom tooth inflammation.” These terms help you plan content around the problems readers actually want to solve, rather than a single noun.

At Procrustes, we turn the questions that matter to clients into articles, with ongoing content planning, writing, and updates.

Expand your candidate list with questions and recurring patterns

Besides browsing related terms, look for combinations that appear repeatedly in the results. Ahrefs’ 2026 guide explains that after entering relevant terms in Keywords Explorer, you can switch to Questions in the Matching terms report to find question-based queries.

Another guide uses English weight-loss terms as an example, identifying the pattern “person’s name + weight loss” and then applying a word-count filter to find terms related to people. This approach comes from a specific English-language example and does not mean the same word-count criteria should apply to Chinese keywords. The key is to identify patterns relevant to the topic before deciding on filtering criteria.

Remove irrelevant terms before comparing data

• Business relevance: Semrush’s florist example notes that “flowers miley cyrus” refers to a song rather than a search for flowers to buy. Even a term containing your seed keyword may attract the wrong audience.
• Whether you can meet the need: A 2018 article by awoo uses “how to make cheesecake / cheesecake recipe” to illustrate that clear search intent alone is not enough; you also need to confirm that your service can meet the underlying need.
• Search volume and difficulty: Compare both rather than ranking terms solely by search volume. You can give lower priority to overly broad, highly competitive terms and explore more specific subtopics instead.
• Search trends: In addition to average monthly search volume, observe changes in interest to inform further research and content scheduling.

Use search results to confirm your content direction

Beyond the data, examine what kinds of content dominate the search results. In a 2021 Semrush case study, an agency found that nine of the top ten results for “liverwurst sandwich” were recipes, making a recipe a content option worth considering. This was an observation at the time; today’s results may differ.

After selecting candidate terms, compare them with your existing pages. If a term’s search intent differs from the needs an existing page addresses, separate content may be appropriate. If a term fits naturally into an existing page and the page can answer the question behind the query, prioritize updating that page. You do not need a new article for every related term you find.