I use the Keyword Magic Tool to generate Bulk Low-Competition Keywords With Semrush Keyword Magic Tool because it turns one seed idea into thousands of keyword possibilities. The tool taps into Semrush’s massive database — over 25.4 billion keywords across 142 geo databases — and extracts related terms, long-tail questions, match types, and SERP features so I can find the right low-competition, profitable keywords for my site.
Table of Contents
- How do I start generating bulk keyword ideas with the Keyword Magic Tool?
- Why should I focus on question and long-tail keywords?
- What are the differences between broad, phrase, exact, and related match types?
- How do I filter millions of keywords down to a workable list?
- How do I find long-tail keywords by word count and SERP features?
- How do groups and subgroups help me organize bulk keywords?
- What does the keyword table tell me and how do I use it?
- How do I turn bulk keyword data into ranking momentum?
- How many keywords can Semrush Keyword Magic return for a single seed?
How do I start generating bulk keyword ideas with the Keyword Magic Tool?
Start by entering a seed keyword and choosing the target country. Within seconds the tool returns a huge list: broad match, phrase match, exact match, related, and question formats. For a single seed like “weight loss” I’ve seen results jump from a few hundred thousand to over 700,000 keyword ideas when I use all matches. That raw scale is where the value lies: Bulk Low-Competition Keywords With Semrush Keyword Magic Tool becomes possible because of Semrush’s database size and responsive filtering.
Why should I focus on question and long-tail keywords?
Question keywords are powerful for quick wins. They often surface long-tail terms with clearer intent, lower competition, and extra opportunities like featured snippets or People Also Ask. I treat question keywords as content prompts: answer the question precisely and you can capture multiple SERP features and build topical authority. When you need fast ranking momentum, question-type long-tail keywords are often where I start.
What are the differences between broad, phrase, exact, and related match types?
Broad match returns the largest set — any variations of the seed keyword in any order. Phrase match returns the seed phrase in various orders and excludes some inflections. Exact match returns the keyword exactly as typed. Related uses the top URLs for the seed keyword and finds other keywords tied to those SERP results, often surfacing alternative phrasings, misspellings, or industry synonyms. I frequently use Related to uncover terms I wouldn’t have thought of and then open those keywords in Keyword Overview to expand again.
How do I filter millions of keywords down to a workable list?
Filters are essential. I typically pare results by:
- Volume — set a minimum monthly search threshold (for example, remove anything under a comfort level such as 99 searches).
- Keyword difficulty — target an upper ceiling (0–50) so I’m not competing for ultra-competitive terms right away.
- Intent — choose informational, commercial, navigational, or transactional based on the page I want to build.
- CPC — include keywords with a nonzero CPC if I want to prioritize commercial value.
- Include / Exclude words — force words to appear (all or any) or remove noisy terms like years (2023) from the list.
How do I find long-tail keywords by word count and SERP features?
Use the advanced filters. Word count helps me favor longer queries that usually have lower competition and clearer intent. I also filter by SERP features — featured snippets, image packs, video carousels, People Also Ask — to aim for multiple visibility opportunities beyond organic rankings. Combining word count and SERP-feature filters often delivers focused lists of low-competition long-tail phrases I can target right away.
How do groups and subgroups help me organize bulk keywords?
The tool auto-generates groups by common words and phrases. Clicking a group drills into subgroups (for example weight → recipe → juice) and produces highly focused keyword sets. This is a great way to discover topical clusters and plan content categories. I then save the best terms to Keyword Manager for tracking or export them to CSV or Excel for planning.
What does the keyword table tell me and how do I use it?
The table shows each keyword, intent, monthly volume, trend, keyword difficulty, CPC, SERP features, number of results, and last update. I sort by volume, difficulty, or trend to prioritize keywords. I use the update metrics function to refresh outdated data, hide columns I don’t need, and export selected keywords. Saving lists into Keyword Manager (2,000 items per list) lets me build campaigns and track progress.
How do I turn bulk keyword data into ranking momentum?
The strategy I follow:
- Filter the massive dataset down to low-to-medium difficulty long-tail questions and phrases.
- Create content that answers questions clearly and targets SERP features where possible.
- Save keyword lists and track them so you can expand into higher-difficulty keywords later after building authority.
Bulk Low-Competition Keywords With Semrush Keyword Magic Tool is about repeated exploration: start broad, use related match to discover alternatives, apply tight filters, and then save and act on the best clusters.
How many keywords can Semrush Keyword Magic return for a single seed?
A single seed can return hundreds of thousands of keyword ideas. In my examples the tool moved from a few hundred thousand to over 700,000 keyword ideas when using all match types and the full database.
Should I always avoid high-volume, high-competition keywords?
Not always. High-competition keywords are valuable but take time and authority to rank for. I start with low-competition, profitable long-tail keywords to get initial momentum, then scale to medium and high-difficulty targets as authority grows.
Can I export keyword lists?
Yes. You can export selected keywords or the entire list to Excel, CSV, or CSV semicolon. You can also save up to 2,000 items per list in Keyword Manager.
Which filters do I use first?
I begin with volume and keyword difficulty, then add intent and SERP feature filters. Finally I use include/exclude and word count to refine to long-tail, question-style queries.
