Map every keyword in your category. Know which clusters are worth building for.
The Keyword Universe expands your category into a clustered, three-tier map of real search demand — the whole picture, not a shortlist — with every cluster rated for brand fit so the order to work in is obvious. The clusters you approve become the topics Seerly tracks, which makes this the decision every other number depends on.
Total Search Volume
1.24M
Monthly, across the universe
Total Keywords
18,432
All tiers
Topic Clusters
46
Named keyword groups
Seed Keyword Groups
128
Expansion roots
On-target keywords
14,905
81% of the universe
| Cluster | Keywords | Monthly searches | Priority |
|---|---|---|---|
Trail running shoeslong-tail | 1,284 | 214,000 | On brand |
Marathon training planslong-tail | 903 | 132,000 | Mostly on brand |
Running shoe fit & sizinglong-tail | 862 | 96,400 | On brand |
Carbon plate racing shoeslong-tail | 517 | 74,900 | On brand |
Trail nutrition & hydration | 344 | 41,200 | Mostly on brand |
Hiking boots | 288 | 58,700 | Mostly off brand |
Inside a cluster
Three tiers, not a flat list
Every cluster opens into a tree. Head terms expand into modifiers, and modifiers into the long-tail phrasings people actually type — each row carrying its own volume, competition tier, and difficulty.
Keyword Playground
Test an idea without touching your universe
Run the same clustering engine on anything — a competitor’s URL, a list of seed terms, a category you are considering. Results are disposable, so you can ask the question before you commit to it.
Shallow mode clusters the input set without long-tail expansion, for when you want a read in minutes rather than a full map. Past runs are kept so you can compare.
How the universe is built
Volume alone is not a strategy
Scope the run
Point Seerly at a site and a target country. That scoping is what keeps search volumes and competition figures meaningful for the market you actually sell into.
Expand and cluster
Seed terms expand into a three-tier tree, each keyword carrying real search volume, competition tier, CPC, and difficulty. Related keywords group into topic clusters.
Rate the brand fit
Every cluster is rated on brand, mostly on brand, or mostly off brand, and that rating is the priority column. A huge cluster with nothing to do with you no longer outranks a smaller one that is core to your business.
Audited keyword by keyword, not cluster by cluster. A single misread term drops one keyword instead of removing an entire theme from your map.
Downstream
This is not a report. It is the input to everything else.
Most keyword tools hand you an export and stop. In Seerly the universe sits upstream: the topics you track are created from its clusters, and everything measured after that inherits the decision.
The topics you track
Approve a set of clusters during setup and Seerly creates your discovery topics from them, each arriving with its anchor keywords. Add a topic later and it suggests names from the same cluster list, so the vocabulary stays consistent.
Inherits: topics and anchor keywords
What gets monitored
Those topics determine which prompts are sent to AI engines every run. Visibility, sentiment, and citation tracking all measure against that set — so the universe decides the questions, and the rest of Seerly reports the answers.
Inherits: the prompts behind every metric
Content briefs
Keyword strategy, target keywords, and recommendations in the content wizard resolve from cluster heads rather than a separate keyword list. A brief is built from the same map you approved, not a parallel one.
Inherits: target keywords and briefs
Agent suggestions
The onboarding agent and the keyword recommendation surface read the same universe as the wizard. When an agent proposes work, it is drawing on the map you signed off on rather than researching from scratch.
Inherits: the recommendation source
Which is why scoping the run matters more than it looks. A universe built for the wrong country, or padded with adjacent-industry noise, does not just produce a messy keyword list — it seeds the wrong topics, so your visibility, sentiment and citation numbers end up measuring a market you do not sell into. Getting this right once is what makes the rest of the platform trustworthy.
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See how businesses are turning AI search visibility into real customers
“Seerly completely changed the game for us! We started getting actual paid customers from AI traffic, and it happened so much faster than we expected. The platform showed us exactly where we were invisible to AI engines and gave us a clear playbook to fix it. Within weeks, the results were tangible. Honestly, it's been a game-changer for our growth.”
Frequently asked questions
Everything you need to know about the Keyword Universe and Playground
The Keyword Universe is the full map of search demand around your brand — every keyword Seerly can find for your category, expanded into a tree, grouped into topic clusters, and rated for how well each cluster fits your brand.
It starts from your site and target country. Seerly expands seed terms into a three-tier tree, pulls real search metrics for each keyword, clusters them into topics, then scores every cluster for how well it fits your brand.
- Total search volume and total keywords across the universe
- Topic clusters and the seed keyword groups behind them
- On-target keyword count, so you can see signal against noise
- Per-keyword search volume, competition tier, CPC, and difficulty
Two differences: the universe is built as a hierarchy rather than a flat list, and it is ordered by brand fit rather than by volume alone.
A flat export of 18,000 keywords is not a strategy. Seerly groups them into topic clusters, expands each into long-tail children, and marks every cluster on brand, mostly on brand, or mostly off brand. You still see the whole category — mostly off-brand clusters included, because adjacent demand is often worth knowing about — but the ranking tells you where to start. Only clusters with no plausible relevance are dropped, and that is noise removal rather than strategy.
Turn clusters into contentSearch runs in two modes. Label search matches cluster names; deep search looks inside every keyword in every cluster and reports how many matched.
- Live match counts on both the cluster and keyword views as you type
- A notice when matches exist but your volume or long-tail filters are hiding them, so an empty result is never ambiguous
- Numbered pagination rather than an endless "load more"
- A card grid or a sortable dense table, whichever you prefer — the choice is remembered
The Playground runs the same clustering engine on any input you like, without touching your project universe. Give it a set of seed keywords or a single URL and it returns clustered results you can throw away.
It is for the questions you ask before committing: what does a competitor rank for, what does a new category look like, is this product line worth building content around. Full mode expands into long-tail; shallow mode just clusters the input set when you only need a fast read.
- Seed from a keyword list or a URL
- Full or shallow mode, an optional brand brief, and a target country
- Live progress as it expands, clusters, and explores long-tail
- A history of previous runs to compare against
The universe sits upstream of most of Seerly. The clusters you approve are turned into the discovery topics your project tracks, each one carrying its anchor keywords across with it.
- Topics are created from the cluster labels you approve, and adding a topic later suggests names from the same list
- Those topics decide which prompts get sent to AI engines, so visibility, sentiment, and citation tracking all measure against them
- The content wizard resolves keyword strategy, target keywords, and recommendations from cluster heads
- The onboarding agent and the recommendation surface read the same universe as the wizard
That is why the brand rating and the country scoping matter more than they look. A universe built for the wrong market does not just make a messy keyword list — it seeds the wrong topics, and every metric downstream then describes a market you do not sell into.
How prompt sets are builtThe universe is built on demand rather than on a fixed schedule. You trigger a run, optionally scoping it to a specific site URL and country, and watch it progress.
Re-running rebuilds the map against current search data. Because a rebuild can change the cluster count, the view keeps you oriented rather than stranding you on a page that no longer exists.
See what each plan includesReady to map
your keyword universe?
Expand your category into a clustered map of real search demand, with every cluster rated for brand fit so you know where to start.