Marketing Analytics Services: Tracking, Dashboards and Insights
Marketing analytics services and consulting for small and growing businesses in three parts: conversion tracking and data pipelines you can trust, marketing dashboards and a data agent you can ask, and marketing data analysis that says what to do next.
Why marketing data
goes wrong
You can't trust the numbers
GA4, the ad platforms and the CRM show three different totals, and every meeting starts with an argument about which one is right.
You can't see which campaigns bring customers
Platforms count clicks and form fills. Which campaigns produce paying customers and revenue stays a guess.
Tracking breaks and nobody notices
A consent banner, a site release, iOS or a booking engine quietly drops conversions, and the ad platforms keep optimising on the gap.
Reporting eats the week
Someone pulls numbers from five tools by hand, and the report arrives too late to change anything.
Build it once.
Keep it right. Use it.
Each part stands on its own. Most clients start with the tracking audit, because every dashboard, agent and analysis depends on it.
Tracking setup & data pipelines
Tracking rebuilt properly, once: validated, documented and in your own accounts.
- Tracking audit: what's missing, duplicated or mis-mapped, ranked by money at stake
- Measurement plan: events, conversions and definitions, with an owner for each number
- GA4 and Google Tag Manager rebuilt, with server-side tracking on your own domain
- Meta Conversions API and Google enhanced conversions, deduplicated
- Consent Mode v2, tested in each consent state
- CRM and offline conversions: leads and revenue sent back to the ad platforms
- GA4 to BigQuery, with ad spend and CRM data joined in modelled tables
- A test record, documentation and handover
Marketing dashboards & data agent
One version of the numbers, and answers when you ask, not another dashboard nobody opens.
- Marketing dashboards in Looker Studio or your BI tool, on one set of definitions
- Paid, organic, CRM and revenue in one funnel view
- A weekly summary in plain language: what moved, why, and what needs a decision
- A data agent, your AI data analyst in Slack: ask a question, get the number and the query behind it
- Answers built on verified queries and written metric definitions
- Known-answer tests re-run after every change, so the agent stays right
Marketing data analysis & insights
Not more charts: what to change next, and what it's likely to bring back.
- Funnel and drop-off analysis: where visitors and leads are lost
- Marketing attribution: channel and campaign return measured against real sales, not platform self-report
- Lead quality: which sources produce customers
- Cohorts, retention and customer lifetime value
- Conversion-rate analysis, A/B test design and readout
- Forecasts and predictive models when the data supports them
- A monthly insight session with ranked recommendations
Agents do the work.
Specialists decide.
// what the agents do
- Check tracking and flag missing, duplicated or mis-mapped conversions
- Keep BigQuery pipelines and models running
- Answer questions about your data in plain language, from verified queries
- Draft the weekly summary
// what the specialist decides
- Designs the measurement plan and the metric definitions
- Approves every tag, model and definition change
- Signs off the numbers and recommendations that go to the business
Where we've done it
Our own site runs the same setup: Consent Mode v2, server-side GTM on a first-party domain, and GA4 exported to BigQuery.
End-to-end analytics for an online lender: a 32-event tracking spec, GA4 and GTM rebuilt, server events by Measurement Protocol, BigQuery modelled in Dataform, and an open-source Evidence board the client uses as its report, with a data agent piloted on top.
AI agents audited and rebuilt measurement across GTM, GA4 and BigQuery: 40+ assets deployed under a human-approval gate, the full 9-step booking funnel instrumented, 3 mis-mapped steps caught before they corrupted the data.
Sales and marketing data unified into one governed warehouse: 3-layer attribution down to click level and all ad spend reconciled against real sales, with incremental models cutting analytics costs by ~96%. The SEO operation now runs AI-first: agents connected to Ahrefs over MCP do the recurring analysis and monitoring.
A German online store for cold-pressed dog food: GA4 e-commerce tracking, a BigQuery data pipeline and reporting boards, Google Ads and SEO. Organic visits grew from about 300 to about 3,000 a month.
Questions we get asked
What do marketing analytics services include?
Three parts: conversion tracking and data pipelines (GA4, Google Tag Manager, server-side tracking, BigQuery), marketing dashboards with a data agent you can ask, and marketing data analysis with recommendations. Each part stands on its own.
Do we have to take all three parts?
No. Dashboards and analysis are only as good as the tracking under them, so we check the tracking first, in the free audit.
What is server-side tracking, and do we need it?
Server-side tracking sends events through your own domain and server instead of straight from the browser, so ad blockers and browser limits drop fewer conversions and you control what each platform receives. If you spend seriously on ads, it usually pays back; we check it in the audit.
What is a data agent, and can it give wrong answers?
An AI data analyst connected to your data that answers questions like 'which campaign brought the most customers last month?'. It answers from queries we have verified and metric definitions we have written down, and shows the query behind each number. A set of known-answer questions is re-run after every change to catch drift.
Why don't GA4, the ad platforms and our CRM agree?
They count different things: platforms credit themselves, GA4 loses users who decline consent, and the CRM only sees what reached sales. We document the gaps and reconcile them in BigQuery for marketing attribution you can defend.
What happens after the setup?
Tracking breaks over time: site releases, new consent rules, platform changes. We can keep it checked and fixed as part of the monthly work, or you take the documented setup and run it yourselves.
Who owns the setup and the data?
You do: the containers, the data, the models and the dashboards live in your accounts.
Get a proposal
Tell us what you want to grow. We reply within 24 hours with what we'd look at first.