AI Search Mastery

Design a defensible query universe (commercial vs informational vs branded mix) and the right sample size for credibility.

Run audits across all 5 AI engines: ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews, using a repeatable protocol.

Score four metrics: Share of Memory, Recommendation Rate, Citation Rate, and Misinformation Rate, on any brand in your category.

Apply the five tactics AI engines actually reward in 2026 (and recognise the three things that don't move the needle, despite the hype).

Build a third-party citation strategy: which 5 sources to influence in your category, how to do it ethically, where the line is.

Sequence moves into a 90-day execution plan with named owners, mechanisms, and budget reality-checks.

Translate visibility metrics into the four numbers your CMO actually cares about: pipeline, brand consideration, defence, growth.

Build a one-page board report template using your own audit data, designed for monthly or quarterly cadence.

Avoid the three reporting traps (vanity metrics, single-engine focus, no peer comparison) that quietly destroy stakeholder credibility.

Handle the three most common stakeholder objections head-on: "our SEO is fine," "AI search will commoditise," "we can't measure ROI.

Position AI search as additive to existing SEO and paid-media investment, not in competition with them.

Walk into any internal review with the data, the comparators, and the case studies that put the AI search question to bed.

Quantify AI search visibility in commercial language: pipeline impact, customer acquisition cost defence, share-of-category protection.

Use the right comparator (paid search CPC, content marketing yield, brand campaign reach) to make the £/$ value defensible.

Build a one-page commercial case the CFO can sign off without escalation.