SEO audit services · Diagnosis + roadmap + handoff
An evidence-led SEO audit covering technical, content, authority, analytics, competitors and AI search—with priorities, developer tickets and an implementation roadmap.
Written and reviewed by Aditya Aman, Founder and SEO Strategist
Last updated July 28, 2026 · Research reviewed against the live SERP
A TheProjectSEO audit is an evidence-backed diagnosis of the technical, content, page, authority, competitor, analytics, conversion, and AI-search conditions affecting qualified organic visibility. The deliverable is not a generic site-health export. Each material finding states what was observed, how it was tested, which pages or templates are affected, why it matters, how confident we are, what should change, who needs to act, and how the fix will be validated.
Evidence, not theatre
The public numbers below are approved project snapshots used to demonstrate source context and measurement discipline. An audit sample will be added only after confidential data is removed and every finding, screenshot, date, and permission is approved.
These are point-in-time measurements from screenshots supplied by the project owner, not promises or typical-client averages. Search and AI-response datasets use different collection methods and should not be added together.
Reserved for evidence, affected cohort, priority, recommendation, owner, and acceptance criteria.
Delivery system
Redacted audit finding
01 · Now
Prove the constraint
02 · Next
Release the change
03 · Scale
Measure and repeat
Reserved for a redacted priority board or released-fix validation with date and method.
Delivery system
Roadmap and validation sample
01 · Now
Prove the constraint
02 · Next
Release the change
03 · Scale
Measure and repeat
Scope and deliverables
Modules are selected for the site and business question. The audit connects them so technical, content, authority, and measurement findings do not contradict one another.
01
Discovery, crawling, rendering, index selection, consolidation, templates, internal architecture, performance, and change risk.
02
How well existing pages satisfy distinct search jobs, demonstrate expertise and evidence, remain current, and lead to useful action.
03
The independent signals and consistent facts that help search systems and customers verify the organization and its claims.
04
What currently earns visibility for the target audience and where the business has credible, differentiated opportunity.
05
Whether search performance and customer outcomes are captured consistently enough to make decisions.
06
A controlled review of how important questions are answered across agreed AI platforms and which sources shape the result.
Find the causes, risks, and opportunities your next SEO roadmap should address.
A comprehensive audit starts with the decision the organization needs to make. “Find every SEO issue” is not a useful boundary; the audit should explain current performance, material constraints, priority opportunities, and the safest route to improvement.
01 · Diagnose
The team needs to separate technical access, page relevance, quality, cannibalization, authority, demand, algorithm, season, tracking, and conversion causes.
Example searches
Conversion event: validated root-cause hypotheses and evidence requirements
02 · Prioritize
Stakeholders need to compare many possible technical, content, page, link, and measurement actions against value, confidence, effort, dependency, and risk.
Example searches
Conversion event: sequenced roadmap, owner, timing, and acceptance criteria
03 · Protect
A redesign, replatform, domain change, information-architecture change, merger, or international expansion may alter URLs and signals that already create value.
Example searches
Conversion event: preservation requirements, pre-launch tests, and monitoring plan
04 · Validate
Leaders may need a second opinion on agency work, content plans, attribution, link risk, AI-search claims, or whether a reported win connects to business outcomes.
Example searches
Conversion event: independent findings, data limitations, decision options, and governance
The audit fails when it optimizes for issue count or presentation volume instead of evidence, decisions, ownership, and a feasible route to production.
Automated crawlers can flag missing fields and unusual states without proving that they affect valuable pages, search behavior, users, or business outcomes.
Our response
We reproduce the issue, segment affected URLs and templates, inspect source systems and search evidence, estimate exposure, and record confidence and exceptions.
Thousands of duplicate titles, canonical conflicts, thin pages, or broken links may result from one template, feed, CMS, or lifecycle rule.
Our response
Findings are grouped into causes and systems. The roadmap prioritizes the change that resolves the recurring pattern, with examples and safeguards for edge cases.
A flat list makes it impossible to balance commercial value, user risk, search exposure, implementation effort, team dependency, and confidence.
Our response
Each recommendation is scored and sequenced. Critical protection, high-confidence growth, enabling work, tests, monitoring, and low-value hygiene are distinguished.
Teams leave the walkthrough understanding the issue but without developer tickets, page lists, owners, acceptance criteria, a release order, or a way to validate impact.
Our response
The deliverable includes an implementation backlog, affected cohorts, specifications, stakeholder actions, validation plan, and an agreed decision and follow-up session.
An AI-search audit should be reproducible enough to guide work. A screenshot of one flattering ChatGPT answer is not a baseline. The prompt, platform, model or mode where known, market, date, answer, sources, competitors, and facts must be recorded.
AI outputs are probabilistic, product behavior changes, and third-party visibility tools use different prompts and scoring methods. An audit describes observed conditions and controllable source gaps; it cannot prove a universal ranking factor or guarantee a citation.
Explore our AI search optimization serviceDefine a stable set of informational, category, comparison, provider, local, product, and branded validation prompts tied to real customer stages.
Output: prompt inventory, test conditions, answer captures, and competitor observations
Map the company and third-party domains and pages repeatedly cited or used to frame important answers.
Output: source graph, cited-page patterns, gaps, and correction opportunities
Compare generated claims with the approved organization, person, product, service, location, price-boundary, and evidence facts.
Output: accuracy log, entity contradictions, claim owners, and priority corrections
Review crawler controls, renderability, canonical ownership, direct answers, sourcing, structured visible facts, internal links, and corroboration.
Output: AI-search backlog integrated with technical, content, and authority priorities
The sequence protects against premature tool output. We first define the business question and systems, then collect and triangulate evidence before building the roadmap.
Agree on sites, markets, products, audiences, business questions, recent changes, constraints, stakeholders, data sources, outcomes, and excluded work.
Delivered: audit charter, access list, stakeholder plan, assumptions, and success criteria
Collect crawl, rendering, index, search, analytics, content, link, competitor, platform, release, and conversion evidence with date ranges and definitions.
Delivered: evidence inventory, baseline views, data-quality issues, and sampling plan
Test hypotheses across representative URLs, templates, queries, markets, devices, and customer stages; distinguish correlation, symptom, and likely cause.
Delivered: finding register with evidence, affected cohorts, confidence, and exceptions
Score findings by value, exposure, confidence, risk, effort, dependency, recurrence, and reversibility; design feasible target states with owners.
Delivered: sequenced roadmap, developer tickets, page decisions, and decision options
Present the diagnosis at the right level for leadership, marketing, content, product, engineering, analytics, and agency partners; resolve questions and ownership.
Delivered: executive deck, working session, updated decisions, and assigned backlog
Review what shipped, validate acceptance criteria, compare affected cohorts with the baseline, record external changes, and adjust the roadmap.
Delivered: implementation review, validation results, exceptions, and next decisions
Different stakeholders need different levels of detail, but they should all trace back to the same evidence and recommendation ID.
| Page system | Search job | Example assets | Business signal |
|---|---|---|---|
| Executive diagnosis | What is happening and what decision matters? | performance narrative, major causes, risks, opportunities, and choices | plain language, evidence, materiality, uncertainty, and recommended direction |
| Finding register | What exactly was observed? | finding ID, category, evidence, affected cohort, impact, confidence | reproducible test, examples, scope, exceptions, and source files |
| Implementation backlog | What must each team do? | owner, recommendation, priority, dependency, effort, acceptance, validation | specific expected behavior, affected patterns, edge cases, and release order |
| Page and URL decisions | Which assets should change? | keep, improve, create, merge, redirect, archive, delete, or monitor | URL list, intent owner, evidence, destination, content requirement, and risk |
| Measurement and follow-up | How will we know the work shipped and mattered? | baseline, cohort, event, search metric, commercial stage, checkpoint | source, definition, owner, cadence, limitation, and next decision |
The immediate success of an audit is decision quality and implementation readiness. Search and commercial outcomes are evaluated later against the cohorts affected by shipped changes.
An audit itself does not change the website. Outcome timing depends on implementation, release quality, crawling and reprocessing, demand, competition, authority, algorithms, content, seasonality, and attribution. We distinguish recommendation, shipment, technical validation, visibility, and business impact.
Material findings have reproducible tests, affected cohorts, examples, sources, confidence, exceptions, and a clear causal hypothesis.
Verified with: finding register and supporting evidence files
Priority work has an agreed outcome, owner, dependency, sequence, acceptance criteria, and explicit decision to ship, test, defer, or reject.
Verified with: roadmap, decision log, and project system
Recommendations accepted, released, and validated across representative pages and templates without material regression.
Verified with: tickets, release records, crawler, Search Console, and QA evidence
Index, impressions, clicks, landing pages, and query visibility for the pages and templates affected by implemented work.
Verified with: Google Search Console, Bing Webmaster Tools, and annotated cohorts
Qualified actions, leads, product usage, bookings, orders, pipeline, or revenue for affected landing-page and customer cohorts.
Verified with: approved analytics and business systems with attribution limitations
The strongest fit is a team that needs an independent, implementation-ready diagnosis and can provide the access and stakeholders needed to test it.
FAQ
Continue planning
Deep crawl, render, index, template, performance, migration, and implementation work.
Independent strategy, prioritization, stakeholder guidance, and ongoing decision support.
How evidence, confidence, prioritization, review, implementation, and measurement work.
Engagement models, starting investment, scope variables, and fit.
Share your website, business questions, recent changes, markets, platforms, stakeholders, and available data. We will define an audit scope that produces implementable decisions.