SERP Clustering

SERP Clustering groups keywords based on what actually ranks in search results. Instead of guessing which queries belong together, you see clusters built from overlapping URLs in live SERPs.

Use this page as a guide for preparing your keyword set, running clustering, refining clusters and exporting results.

SERP Clustering helps you:

• Group related keywords into clusters based on overlapping SERP results
• See where user intent is shared or split across queries
• Adjust cluster strictness with an overlap threshold
• Reuse the same SERPs to re cluster without extra cost

The output is a set of clusters that later feeds:

• Topical Map
• Planning and brief work for individual pages

1. Open your project in Floyi.
2. In the left navigation, select SERP Clustering.
3. You will see a workspace with region settings, similarity controls and a table for clusters.

Most teams reach this screen after preparing a keyword list in Topical Research.

You can bring keywords into SERP Clustering in two ways:

• From Topical Research

  • Select the topics or rows you want, then send them into clustering from the Topical Research view

• From a file or manual list

  • Paste or import keywords if the UI supports it for your project

Good practice:

• Remove obvious noise and off scope queries first
• Keep sets focused around one domain area or pillar rather than your entire site in one run

The cleaner your starting set, the more useful your clusters will be.

At the top of SERP Clustering, choose where and how Floyi should fetch SERPs.

1. Country

   • Pick the main country you want to target, such as United States, United Kingdom or Australia

2. Language

   • Select the language that matches your content and audience

3. Optional location

   • Add a city or state if you need more local intent, for example:
     • “New York” for local services
     • A region you sell to inside a larger country

These settings control which SERPs Floyi fetches and which search index your clusters reflect.

Next, set how strict you want clusters to be.

Floyi uses a similarity or overlap slider. Higher values create smaller, tighter clusters. Lower values create broader clusters.

Typical behavior:

• Lower threshold e.g. 20 to 40

  • Fewer clusters
  • More keywords grouped together
  • Good for early exploration and macro themes

• Higher threshold e.g. 60 to 80

  • More clusters
  • Fewer keywords in each one
  • Good for detailed page level decisions

You can change this later and re cluster without paying for SERPs again, so you do not need the perfect value on the first pass.

When you are happy with the settings, run the initial job.

1. Confirm the keywords, country, language and overlap threshold.

2. Review the credit estimate. Costs depend on:

   • Number of keywords
   • SERP depth Floyi fetches per keyword

3. Click Fetch SERPs and cluster.

Floyi will:

• Fetch SERPs for each keyword
• Measure overlap between results
• Build clusters based on the overlap threshold

While this runs, you will see a status indicator. Once complete, cluster metrics and tables will appear.

Fetching SERPs and initial clustering uses credits. You only pay when new SERPs are fetched.

After the first run, you can adjust cluster shapes without paying for SERPs again.

1. Change the overlap or similarity threshold.
2. Click Re cluster or the equivalent action.

Floyi will:

• Reuse the stored SERP data
• Rebuild clusters with the new threshold

Re clustering is free. Use it to test:

• Tighter intent for page planning
• Looser groups for pillar overview, supporting pieces and hub pages

Search results change. When you want a fresh view:

1. Keep the same keyword list or adjust it as needed.
2. Click Fetch new SERPs.
3. Review the credit estimate and confirm.

Floyi will fetch new SERPs and rebuild clusters. This is useful when:

• It has been a while since the last fetch date
• A major algorithm or feature change affects your space
• You added many new keywords and want a consistent timestamp

Fetching new SERPs always uses credits. Re clustering with existing SERPs remains free.

After clustering, you will see a summary and a table of clusters.

Common metrics include:

• Analyzed keywords

  • Total number of keywords included in this run

• Clusters

  • Count of distinct clusters

• SERP date

  • The date when SERPs were last fetched for this run

Check the SERP date to understand how fresh your data is.

The cluster table typically shows:

• Cluster ID or number

• Cluster head term

  • A centroid keyword that best represents the group

• Keyword count in cluster

• Keywords

  • List of all queries assigned to this cluster

Depending on your plan and integrations, you may also see:

• Search volume
• CPC
• Competition score or difficulty

You can sort, filter and scroll through clusters to inspect them quickly.

To understand why queries are grouped together, inspect SERP details.

1. Click the info icon for a cluster or keyword.
2. A modal will show:
   • Top ranking URLs
   • Their positions for the head term
   • Overlap for that keyword and the cluster centroid

If the keyword and cluster head term are different:

• Floyi shows overlapping results so you can see which URLs rank for both
• This helps you decide whether they belong on the same page or need separate content

Use these modals to:

• Spot intent splits inside a cluster
• Find pages that already rank across many queries
• Identify competitors that dominate key clusters

If you notice off scope keywords in clusters:

1. Remove them from your keyword set in the cluster view or back in Topical Research, depending on how your project is wired.
2. Re run clustering with the cleaned list, either:
   • Re cluster using existing SERPs if nothing new is added
   • Fetch new SERPs if you changed the list significantly and want consistent data

Cleaning noisy queries improves cluster quality and later mapping.

When you want to work outside Floyi or share with others:

1. Click Export or Export to Excel.
2. Choose the format, usually XLSX.

Export