Keyword Clustering: SERP vs Semantic

Updated October 7, 2026

What Is Keyword Clustering?

Keyword clustering groups keywords that one page can rank for. Instead of writing a page per keyword, you write a page per cluster. This avoids pages competing with each other and lets each page cover a topic completely.

SERP vs Semantic Clustering

As an example, "cast iron skillet care" and "how to season a cast iron pan" share words but may return different results, so they might deserve different pages. SERP clustering would show that; semantic clustering might merge them.

Search Intent and Clustering

Search intent is the goal behind a search: learning, comparing, buying or going somewhere specific. Keywords in one cluster should share an intent. If a cluster mixes "best X" (comparing) with "how to use X" (learning), split it.

• Informational: how-to, what-is and why questions.
• Commercial: best, versus, review and alternatives.
• Transactional: pricing, buy, coupon.
• Navigational: brand or login searches.

From Clusters to Pages

1. Cluster your filtered keyword list.
2. Name each cluster by its main keyword; that becomes the page's focus.
3. Use the other keywords as subheadings and questions on the page.
4. Merge tiny clusters with the same intent; split clusters with mixed intent.
5. Arrange the pages into hubs with a topical map.

Tools That Cluster Keywords

Many tools now offer clustering, either as a feature or as their main product. LowFruits includes both SERP and semantic clustering, so you can group keywords using the results data you already extracted while checking for weak spots. All-in-one suites such as Semrush also offer clustering features. See how to use LowFruits for its clustering step.