Resources
AI resources and guides for the three problems clients bring us
Most companies come to us because nobody finds them, the marketing spend is not paying back, or the systems behind the site cannot keep up. Each guide below explains one piece of that in plain language, then links to the service page that goes deeper.
Start here
Getting found
For when your Google traffic is flat and you are missing from the shortlist AI assistants give buyers. Start with AI search visibility.
AI search visibility (AEO and GEO)
How ChatGPT, Claude and Google's AI pick the companies they recommend, and what gets you cited.
Search engine optimization
The work that still moves Google rankings, and how it feeds AI answers at the same time.
SEO audit
What an audit checks, what it usually finds, and how to turn the findings into a fix list.
Content marketing
Writing pages that answer a buyer's question well enough to be quoted, not just indexed.
Local SEO
Getting found for searches in your area, including the map pack and 'near me' questions.
SEO reporting
Which numbers show whether search work is paying off, and which ones only look good.
Proving the ROI
For when budget goes out, leads come in, and nobody can say which half works. Start with analytics, because nothing else makes sense until the numbers do.
Analytics and conversion optimization
Measurement you can trust first, then testing. What to track so a result means something.
Paid media
Where ad budget leaks, how to find it, and how continuous tuning changes the return.
PPC management
Running search ads against pipeline and cost per customer rather than clicks.
Channel attribution
Working out which channel actually brought the customer when several touched them.
Marketing intelligence and forecasting
Using the data you already have to forecast demand and decide where the next dollar goes.
Email marketing
The channel with the clearest ROI, and how to run it so it earns rather than annoys.
Building the back end
For when the store, the site or the systems behind them are slow, manual and held together by a spreadsheet.
Ecommerce development
Stores built to convert, with the back end connected so orders, stock and data flow.
Backend development
The part of a site nobody sees: databases, logic and the integrations that keep it honest.
API and system integration
Connecting CRM, commerce, help desk and finance so data stops living in spreadsheets.
AI workflow automation
Which repetitive work is safe to automate, which is not, and how to tell the difference.
AI agents
What an agent can do on its own, where it should stop and ask a person, and how to log it.
Shopify
Running a Shopify store with AI doing the repeatable work and people watching the margin.
Leading AI inside the company
For leaders who have been told to adopt AI and want to do it without handing judgment to software.
AI readiness assessment
How to score each workflow for value, risk and readiness before spending on tools.
AI strategy and roadmap
Turning a list of ideas into a sequence with owners, budgets and decision points.
AI governance and responsible use
Policies, approval thresholds and audit trails, including when the EU AI Act applies.
Fractional AI leadership
What a part-time AI lead does, and when a company needs one rather than a vendor.
Workforce AI enablement
Training teams inside their own work, role by role, so the tools get used.
Change and adoption
Why AI rollouts stall after the pilot, and how to get a team to keep using what works.
Knowledge systems
Making company knowledge findable by people and usable by AI without leaking it.
By industry
The same three problems look different in each industry. These pages cover what changes and what does not.
