Business Intelligence
One version of the numbers, available when decisions get made.
Cloud, Data & Reliability
Most companies have data and no answers
The problem is rarely a lack of tracking. It is tracking that was set up ad hoc, means different things in different tools, and cannot answer the question leadership actually asks.
- Engagement
- Implementation project then optional retainer
- Typical timeline
- 4–8 weeks
- Delivered across
- All 50 US states
Overview
Analytics implementations accumulate. A tag added for a campaign, an event named inconsistently, a conversion counted twice, a filter someone added and forgot. Eventually numbers disagree between platforms, nobody trusts any of them, and decisions get made on instinct while the dashboards go unopened.
We rebuild measurement from the question backward. What decisions do you need to make, what metrics inform them, what events produce those metrics, and what naming convention keeps it coherent as the site changes. Then implement with server-side tagging where it improves accuracy, and validate rigorously before anyone relies on it.
Privacy is now part of the engineering. Consent management, data minimization, CCPA and state privacy compliance, and honest handling of the gaps left by tracking prevention. Modeled data is fine when it is labeled as modeled and everyone understands its limits.
- Numbers that reconcile across platforms
- One sourceNumbers that reconcile across platforms
- Tagging for accuracy and page speed
- Server-sideTagging for accuracy and page speed
- Dashboards built around real questions
- Decision-ledDashboards built around real questions
Business benefits
What analytics changes for you
The reasons this work earns its budget, stated as outcomes rather than features.
Designed around decisions
A measurement plan built from the questions you need answered, so tracking exists for a reason rather than by accumulation.
Consistent event taxonomy
Documented naming and parameter conventions so data stays coherent as the site evolves and teams change.
Server-side tagging
Improves data accuracy against tracking prevention while removing client-side weight, which helps performance too.
Attribution beyond last click
Multi-touch and incrementality context so channel budget decisions rest on contribution rather than whoever was last.
Offline conversions connected
CRM outcomes fed back to ad platforms so optimization targets closed revenue rather than form submissions.
Privacy compliant
Consent management, data minimization and documented retention aligned to CCPA/CPRA and other state privacy laws.
Problems solved
If any of this sounds familiar
These are the situations clients describe in the first conversation, and what we do about each.
“Our platforms all report different numbers.”
A measurement audit that finds the causes — attribution windows, deduplication, filter differences — then reconciles them and documents why residual differences exist.
“We cannot tell which channels actually drive revenue.”
Attribution modeling with CRM integration and incrementality testing, which frequently reorders the apparent channel ranking substantially.
“Nobody looks at our dashboards.”
Rebuild around specific recurring decisions with clear ownership, delivered where people already work rather than in another tool.
“Our tracking broke after a redesign and nobody noticed.”
Automated tracking validation and alerting, plus a documented plan so tracking is part of the release checklist.
Our process
How we deliver it
Each stage has a defined output, so you always know what you are getting and when.
- 01
Measurement planning
Define decisions, metrics, events and naming conventions in a documented plan before any implementation begins.
- 02
Audit
Review current implementation for accuracy, duplication, gaps and configuration issues across all platforms.
- 03
Implementation
Tag manager and server-side configuration, event tracking, ecommerce and conversion setup, with consent handling.
- 04
Validation
End-to-end testing across devices and scenarios, plus reconciliation against platform and backend data.
- 05
Reporting
Dashboards built around decisions, with training and documentation so the team can extend them.
Technologies used
The tools behind the work
Chosen for maintainability and hiring depth rather than novelty. We will justify any choice on request, and we avoid technology that makes you dependent on us.
- GA4
- Google Tag Manager
- BigQuery
- Looker Studio
- Segment
- PostHog
- Mixpanel
- HubSpot
Industries served
Where this work lands most often
Sector context changes what good looks like. These are the industries where we have delivered this service repeatedly.
Why Mova
What working with us on analytics is like
The same commitments apply to every engagement, regardless of size or service.
A defined first step
We scope a fixed-price starting point so you can evaluate us on analytics before committing to a program.
Senior people, named
The team you meet is the team that delivers. You will know exactly who is accountable.
You own the output
Code, accounts, files and documentation are yours from day one, with no lock-in of any kind.
Measured, then reported
We baseline before starting and report against it honestly — including the months that fall short.
Questions
Analytics: common questions
The questions we are asked most about analytics, answered directly.
Different attribution windows, models, deduplication and consent handling. Some difference is inherent and expected. We reconcile what can be reconciled and document why the remainder differs so nobody keeps relitigating it.
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Next step
Ready to talk about analytics?
Thirty minutes with someone who has delivered this work. We will tell you what it would take, roughly what it would cost, and whether Mova is the right fit.
No pitch deck. A 30-minute conversation about what you are trying to achieve.