Discovery baseline
Defined question and platform sample with an observation baseline
When buyers use AI-assisted search to compare options, your business needs accurate, accessible information that stands up to scrutiny. I review how your brand and priority topics are represented, identify evidence gaps, and build a practical improvement plan grounded in SEO.
An illustration of the approach, not a live audit.
For established businesses with a differentiated offer, subject-matter expertise, and buyers who research complex decisions. Suitable for teams that want a measured AI-search programme rather than a promise to appear in every generated answer.
Defined question and platform sample with an observation baseline
Brand information, source evidence, and technical-readiness gap review
Prioritised content and authority recommendations with owners
Repeatable reporting framework separating visibility observations from business outcomes
Choose an area to explore the work and what you receive.
When buyers use AI-assisted search to compare options, your business needs accurate, accessible information that stands up to scrutiny. I review how your brand and priority topics are represented, identify evidence gaps, and build a practical improvement plan grounded in SEO.
Concept illustration · no client performance dataDefine a representative set of buying questions, markets, and platforms. Record observed brand mentions, cited sources, dates, and context to create a repeatable baseline—not a universal AI visibility score.
Review crawl and index eligibility, important brand and product information, author or business identity, and the sources that support commercial claims. Identify inaccurate, inconsistent, or difficult-to-find information.
Concept illustration · no client performance dataReview crawl and index eligibility, important brand and product information, author or business identity, and the sources that support commercial claims. Identify inaccurate, inconsistent, or difficult-to-find information.
Prioritise improvements to useful comparison content, expert explanations, original evidence, and relevant external references. Coordinate with your content, product, and communications teams so claims remain accurate.
Concept illustration · no client performance dataPrioritise improvements to useful comparison content, expert explanations, original evidence, and relevant external references. Coordinate with your content, product, and communications teams so claims remain accurate.
Repeat the agreed observations and review identifiable referral traffic and qualified actions where available. Separate mentions, citations, visits, and conversions, and document the limits of each dataset.
Concept illustration · no client performance dataRepeat the agreed observations and review identifiable referral traffic and qualified actions where available. Separate mentions, citations, visits, and conversions, and document the limits of each dataset.
We agree the scope and responsibilities first, then move from investigation to implementation and review.
Understand your business, your audience, and the problem you want to solve.
Agree what matters most and the work that fits your resources.
Deliver the agreed recommendations and coordinate the necessary changes.
Check the work, interpret the evidence, and decide the next useful action.
A missing brand mention does not reveal one simple ranking factor. I compare the question, the sources used, your actual offer, and the available evidence before recommending work. The useful output is a defensible set of priorities, not a claim that a prompt test proves how an entire platform behaves.
Review my professional experienceAI-assisted comparisons describe a company inconsistently and rely on outdated product details.
Audit the source information, correct owned facts, and improve the evidence on priority product and comparison pages.
Repeat the defined observation set and review accuracy, citations, and identifiable referrals without assuming causality.
An illustrative comparison of the approach. These examples describe improvements to the work, not promised performance results.
Define platforms, markets, question sample, observation cadence, access, and implementation responsibilities. Monitoring subscriptions, original research, content production, and digital PR may require separate scope. Google AI features still rely on SEO foundations; no special AI file guarantees eligibility.
Track the agreed sample of mentions and citations, source accuracy, relevant referral sessions where identifiable, and downstream actions where measurable. Generated answers vary by platform, context, and time; observed coverage is not a census of all answers or proof of revenue impact.
My 7+ years in SEO and digital marketing inform how I investigate, prioritise, and communicate the work. You work directly with the person responsible for the recommendations.
Start with the business objective and the economics behind it. The proposal sets out priority work, dependencies, fees, and how we will assess progress. Where evidence is incomplete, assumptions remain visible.
Agree the backlog, implementation owner, review cadence, and approval process. Recommendations include the reasoning and practical handoffs your writers, developers, or account team need.
Use my CV and experience summaries to assess role fit, responsibility, and how I approach the work. My SEO leadership background includes Kazix and Yoddha Lab; the portfolio distinguishes CV-based experience from verified client case studies.
View background & CVA diagnostic project, implementation sprint, or ongoing partnership should each have a written scope, named owners, a review schedule, and a clear approach to additional work. Fees depend on complexity, delivery responsibility, and the agreed scope.
The toolset depends on your site, access, and the agreed scope.
GEO covers the broader discovery picture: brand representation, source evidence, technical readiness, and observations across an agreed AI-search sample. AEO focuses more narrowly on making specific buyer questions well answered on your site. The work can overlap and is scoped together to avoid duplicate effort.
No. Platforms select and generate their own responses. I can improve the quality and accessibility of your information and report observed changes, but I cannot guarantee selection, wording, citation frequency, or placement.
No. It builds on useful content, a discoverable website, and credible business information. For Google AI search, conventional SEO remains foundational.
A documented baseline, a review of information and evidence gaps, and a prioritised plan with implementation owners. We agree the observation sample and reporting limits before treating changes as meaningful.
You work directly with Barshad. We agree any developer, writer, or internal-team responsibilities as part of the scope.
After reviewing your requirements, we agree the priority work, deliverables, dependencies, timeline, and fees before starting.
No. Rankings, demand, competition, platform changes, and implementation affect results. I commit to clear work, transparent priorities, and evidence-led review.
Yes. Share your existing workflow and available resources so we can agree ownership, handoffs, and the support your team needs.
A review of crawlable content, clear business information, original evidence and observable AI-search visibility.
Use available Search Console generative-AI reporting and documented observations, keeping visibility separate from enquiries or revenue. No inclusion guarantee.
Agree the business objective, baseline, access, implementation owner and review period. Prioritise by likely impact, effort, dependencies and business relevance.
Approach informed by Google’s guidance on generative search.
Share your website and the challenge you want to solve. Let’s start with a useful conversation.