Keyword platform
Precise AI Keyword LabelingFor SEO Campaigns
Mole automatically tags keywords by intent and relevance so your team spends less time on manual keyword categorization and more time building campaigns that perform.
Why generic keyword tools fall short
Most keyword tools dump a list and leave the organization to you. Mole's 2D AI keyword labeling automatically classifies every keyword by search intent and relevance in one pass, giving agencies and SEO teams a structured, campaign-ready taxonomy without the spreadsheet grind. It is not a black-box suggestion — your strategy drives the classification logic, and Mole executes it at machine speed.
01 · Core Mechanism
2D Labeling by Intent and Relevance
Mole scores every keyword across two axes simultaneously: search intent (informational, navigational, commercial, transactional) and relevance to your client's product or service, producing a structured map you can act on immediately.
- Intent and relevance scored together
- Campaign-ready keyword taxonomy
- No manual tagging required
02 · Campaign Organization
Group and Tag at Scale
Once labeled, keywords are automatically grouped into campaign buckets and tagged for easy filtering. Agencies managing multiple clients can keep every account organized without rebuilding their taxonomy from scratch each time.
- Multi-client keyword organization
- Filterable tag-based grouping
- Reusable campaign structures
03 · Keyword Intelligence
Richer Analysis Behind Every Label
Labels are not guesses. Mole grounds each classification in SERP analysis and keyword research data, so the intent and relevance tags you see reflect what is actually ranking and converting in search today.
- SERP-grounded classifications
- Research-backed relevance scoring
- Reflects live search behavior
04 · Discovery Layer
Extract Keywords From Real Conversations
Mole can pull keywords directly from sales-call transcripts and customer-facing materials, then auto-label them by intent. This surfaces the language your buyers actually use before it ever appears in a keyword tool.
- Transcript-based keyword extraction
- Auto-labeled on extraction
- Buyer language captured early
05 · Closed-Loop Tracking
Track Performance After You Label
Labeled and grouped keywords flow directly into Mole's rank tracking, so you can measure how each intent cluster performs across Google and AI engines like ChatGPT, Perplexity, and Claude from one dashboard.
- Intent-cluster rank tracking
- Google and AI engine coverage
- One unified dashboard
Common Questions
What teams ask before adopting AI keyword labeling
How does Mole's AI keyword labeling actually work?
Mole analyzes each keyword against SERP data and your client's product context, then assigns two labels: one for search intent (informational, navigational, commercial, or transactional) and one for relevance. The result is a 2D keyword map your team can filter, group, and act on immediately. You set the strategic direction; Mole handles the classification at scale.
Can AI labeling replace a human SEO strategist's judgment?
No, and that is by design. Mole is built on the principle that strategy, judgment, and client relationships stay with your team. The AI labeling automates and expedites the repetitive classification work so your strategists can focus on higher-order decisions. Think of it as handling roughly the execution layer while you own the strategy layer.
Does Mole support keyword labeling for multiple clients at once?
Yes. Mole operates with a dedicated, isolated AI agent per client, each with its own persistent memory. This means keyword taxonomies, intent labels, and campaign groupings are kept separate per account. Agencies can maintain consistent labeling logic across their entire book of business without cross-contamination between client workspaces.
What keyword sources does Mole pull from for labeling?
Mole can label keywords sourced from standard keyword research, SERP analysis, competitor research, and even sales-call transcripts. Pulling from transcripts is particularly useful for surfacing buyer language that never appears in traditional keyword tools. All sources feed into the same 2D labeling system so your taxonomy stays unified regardless of origin.
How does AI keyword labeling connect to the rest of the Mole platform?
Labeled keywords do not sit in isolation. Once classified and tagged, they feed into Mole's rank tracking across Google and AI engines like ChatGPT, Perplexity, and Claude, and can inform content generation, landing page creation, and campaign planning. The keyword platform is a unified command center, not a standalone report you export and abandon.
See AI Keyword Labeling in Action
Book a demo to see how Mole automatically classifies keywords by intent and relevance so your team can build better campaigns faster.