Content & Strategy
Keyword Research
Beyond search volume and keyword difficulty. Topic mapping that covers Google query patterns, AI Search conversational queries, SERP feature opportunities, and the entity research most keyword tools skip. Built for content teams who need direction, not just data.
Deliverables
Keyword research and clustering
Topic-organised keyword universe per content area, with search volumes, difficulty scoring, and intent classification. The foundation that traditional research provides, done well.
AI Search query pattern analysis
The layer most keyword research skips. Conversational queries, question patterns, and intent-rich phrasings that shoppers and researchers actually use when asking ChatGPT, Claude, and Perplexity.
SERP feature mapping
Per-query analysis of what surfaces appear: AI Overviews, featured snippets, People Also Ask, knowledge panels, product carousels. Citation opportunities marked clearly.
Entity research and topic priorities
Beyond keywords: which entities, topics, and concepts your audience cares about. Mapped to your content goals and aligned with how AI engines build understanding of subject expertise.
Content opportunity prioritisation
Every topic ranked by traffic potential, competition, and citation opportunity. Documented sequence so your content team knows what to write first, second, third.
Documented framework
Written guide for your team to continue the research approach internally. The patterns, the tools, the prompts, the validation steps. Built so you can repeat the work without me.
Process
Discovery call
Thirty minutes. We walk through your content goals, your audience, your competitors, and the topic areas in scope. By the end I know whether the research is exploratory (new territory) or refinement (improving an existing content programme).
Topic and entity foundation
One week. Mapping the core entities and topic universe per content area: products, problems, concepts, and the relationships between them. The structure that everything else hangs off.
Query universe mapping
Two weeks. Building the full query inventory across both Google patterns (volume-driven, intent-classified) and AI Search patterns (conversational, question-form, citation-rich). Two surfaces, one map.
SERP feature and citation analysis
One week. Per-query analysis of which SERP features appear, which AI engines currently cite this topic, and where the gaps are. Documented so you can see exactly which queries to prioritise for which outcome.
Prioritisation and handover
Content opportunity matrix ranked by traffic potential, competition, and citation opportunity. Documented framework so your team can continue the research approach internally going forward.
Packages
Focused Research
From £1,500
One topic area, mapped properly
2 weeks
- Keyword research and clustering across one defined topic area
- AI Search query pattern analysis for that area
- SERP feature mapping per query
- Entity research and topic priorities
- Documented prioritisation matrix
Comprehensive Research Package
From £3,500
Full content territory mapping
4 to 6 weeks
- Everything in the focused research
- Multiple topic areas mapped together (typically 3 to 6)
- Competitor query universe and gap analysis
- Citation opportunity audit across AI engines
- Content opportunity prioritisation with traffic estimates
- Documented framework for ongoing internal research
Ongoing Quarterly Research
From £500/month
Refreshed direction as the landscape shifts
Quarterly cadence
- Quarterly keyword universe refresh per active topic area
- AI Search query pattern trend tracking
- New SERP feature emergence per topic
- Quarterly opportunity reviews with priority updates
- Direct email access for ad-hoc research questions
Case Studies
Halewood Editorial
Editorial topic map covering Google and AI surfaces
Editorial publication needed direction across six content categories. Built topic clusters mapping Google volume queries alongside AI Search conversational patterns per category. Output gave their writing team a 12-month editorial roadmap with priority signals for each piece.
Outcome:
Cendric
B2B SaaS topic mapping for product-led content
B2B SaaS was producing content that ranked but did not convert. Reset the research from the entity layer up: which problems their buyers actually research, which queries lead to evaluation, which AI Search patterns generate vendor recommendations. Their content team rebuilt their editorial calendar from the output.
Outcome:
Brixley & Co
Category launch research for a DTC brand
DTC lifestyle brand launching a new product category needed keyword research before content production began. Built the topic universe covering search intent across discovery, evaluation, and purchase queries. Identified citation gaps where AI engines had no good recommendation source yet.
Outcome:
FAQs
How is your keyword research different from what Semrush or Ahrefs gives me?
The tools are part of the work; they are not the work. Semrush and Ahrefs surface keywords your competitors rank for, with volumes and difficulty scores. They do not surface the conversational AI Search queries your audience actually uses on ChatGPT, Claude, or Perplexity. They do not map citation opportunities. They do not build the entity foundation underneath the keywords. The deliverable is research, not a tool export.
Do you cover AI Search queries?
That is the differentiator. AI Search query patterns are longer, more conversational, and intent-rich. They look more like real questions than search syntax. The research process specifically maps these patterns alongside traditional Google queries, using AI Search citation analysis to identify which topics currently generate citations and where the gaps are.
What is the difference between keyword and entity research?
Keywords are queries. Entities are the things those queries are about: products, brands, concepts, people, problems. Modern search and AI engines understand content through entities, not just keywords. Entity research maps which concepts your audience cares about and how they relate to each other - the foundation that keyword targeting hangs off.
How long does keyword research take?
Focused research for one topic area: two weeks. Comprehensive multi-topic research: four to six weeks. The work scales with the number of topic areas in scope and the depth of competitor and citation analysis required. We agree the scope during the discovery call.
Will the research be obsolete in six months?
Partially. Search volumes shift, SERP features change, AI Search citation patterns evolve. The keyword universe and entity foundation stay durable for 12 to 24 months. The query patterns and SERP feature data benefit from quarterly refreshes. The framework I deliver lets your team continue the work internally.
Can I do this myself with tools?
Yes, partially. The tool-driven layer (volumes, difficulty, competitor keywords) is well-served by Semrush, Ahrefs, or similar. The entity research, AI Search query mapping, SERP feature analysis, and citation opportunity work is harder to do well without specific experience. Many teams hire for the second layer and keep the first layer in-house.
Do you do keyword research per market for international brands?
Yes, often alongside the International SEO service. Each market needs its own research because query patterns, SERP features, and citation opportunities differ by language and region. We scope per-market research during discovery so the volumes you are paying for match the markets that matter.
Do you research competitor keywords?
Yes, as part of the comprehensive package. Competitor query universe mapping shows which topics your competitors rank for, which AI engines cite them, and which gaps they have. Useful for both attack (where to compete) and defence (where they could take share from you).