AI SEO & Growth

AI Analytics and Reporting

Tracking that is actually correct, and a monthly report that reads like a decision memo: what moved, the most likely reason, and the two or three things worth doing next. Not a wall of charts.

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AI Analytics and Reporting

Most analytics dashboards do not lead to a decision

Teams have plenty of data and very little direction. Tracking is often half broken, reports are a screenshot of a dashboard, and nobody is sure what caused a number to move or what to change. Useful reporting starts with trustworthy tracking, then does the interpretation: connecting a change to a likely cause and turning it into a next step.

What we build

  • A tracking audit and fix: events, conversions, and filtering that can be trusted
  • A clear measurement plan tied to the outcomes that matter to the business
  • A monthly report in plain language: what changed, the likely why, and what to do
  • Dashboards for the few numbers worth watching between reports
  • Automated anomaly checks that compare each metric against its own recent baseline and flag a move outside the normal range, not an arbitrary percentage cutoff
  • Attribution kept honest about what it can and cannot tell you

How the work runs

  1. 1

    Audit the tracking

    2–4 days

    We check what is being measured, fix what is broken, and remove noise like internal traffic and bots.

  2. 2

    Agree the metrics

    1–2 days

    A short list of metrics is tied to real business outcomes, so reporting stays focused.

  3. 3

    Automate the gathering

    3–5 days

    Data is pulled together automatically so time goes into interpretation, not copy and paste.

  4. 4

    Interpret monthly

    Ongoing, monthly

    Each month we write what changed, the most likely cause, and a ranked list of actions.

  5. 5

    Review and adjust

    Ongoing, monthly

    We check whether last month actions helped, then adjust the plan.

How we work

How we deliver

  1. 1

    Discovery & Scoping

    1-3 days

    We start by understanding the actual problem and your existing systems, not just the brief.

  2. 2

    Architecture & Plan

    2-4 days

    We map the technical approach and integration points before any code gets written.

  3. 3

    Build

    1-8 weeks, scoped to your project

    AI-augmented development that moves fast without skipping review.

  4. 4

    Test & Launch

    2-3 days

    Real testing against real scenarios before it touches a live user.

  5. 5

    Tune & Support

    Ongoing

    We monitor and refine in the weeks after launch. This isn't a handoff and disappear.

What you get out of it

  • Tracking you can trust before you make decisions on it
  • A report that ends with actions, not just charts
  • Early warning when traffic or conversions move sharply
  • Less time spent assembling data, more spent acting on it

Questions we get about this

Most commonly Google Analytics 4 and Google Search Console, with Looker Studio for dashboards. We can also work with server-side tracking and privacy-focused tools if that is your setup.

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Ready to scope ai analytics and reporting?

Send us the details of your setup: the tools, the volume, the workflow. We'll come back with an honest assessment and a fixed quote.

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