Do we need a data warehouse?

Not always. Smaller stacks can be unified with direct connections. Where volume, multiple brands or several CRMs are involved, a warehouse pays for itself quickly.

How long does implementation take?

Measurement audit and tracking take three to four weeks. Unification, attribution and dashboards typically complete inside eight to ten weeks.

Will this work with our existing CRM?

Yes. We integrate with mainstream CRMs and most bespoke systems that expose an API.

What attribution model do you use?

Usually a blended view: multi-touch for channel contribution, reconciled against finance and sanity-checked with incrementality testing where budget allows.

Is this compliant with privacy regulation?

Yes. Consent management, server-side tagging and data minimisation are implemented as standard, with regional requirements configured.

Who maintains the dashboards?

We do under a managed agreement, including tracking validation, new metric additions and quality monitoring.

Can non-technical staff use the reporting?

That is the point. Dashboards are role-specific and plain-language, with definitions documented for every metric.

What if our historical data is unreliable?

We establish a clean baseline from implementation forward and clearly mark the boundary rather than pretending old data is comparable.

Do you support offline and phone conversions?

Yes, through call tracking, CRM stage imports and offline conversion uploads back into the ad platforms.

How accurate is the forecasting?

Accuracy improves with data history. Most clients reach dependable directional forecasting within two quarters of clean measurement.

Can this integrate with our automation agents?

Yes. Agent activity, resolution rates and hours saved are reported in the same layer as marketing and sales performance.

Do we own the data and dashboards?

Entirely. Warehouse, dashboards, models and documentation are built in your accounts and remain yours.

Analytics & Growth Intelligence

Decisions built on evidence, not opinion

Most companies have plenty of data and no clarity. We unify marketing, sales and operational data into a single attribution and reporting layer, then apply AI analysis so the insight arrives before the quarter ends, not after it.

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One

Source of truth

Revenue

Attributed to source

Predictive

Pipeline forecasting

System map

Live

Analytics & Growth Intelligence

01Measurement plan and tracking
02Data unification layer
03Multi-touch attribution
04Executive dashboards
05AI insight and anomaly alerts
06Forecasting and planning

OutcomeMeasurable, compounding growth

What is quietly costing you growth

The patterns we see before every analytics & growth intelligence engagement, and the revenue they hold back.

Numbers that never reconcile

The ad platforms, analytics and CRM report three different truths, so every review meeting starts by arguing about the data.

No visibility of what actually drives revenue

Channel reporting stops at the lead, so budget is allocated by last-click habit rather than closed-won contribution.

Manual reporting consuming days

Analysts rebuild the same spreadsheet monthly, and the insight arrives too late to change anything.

Vanity metrics on the dashboard

Impressions and sessions are reported to a board that needs pipeline, cost per opportunity and payback.

Problems discovered too late

A broken form or collapsed campaign runs for three weeks before anyone notices in the monthly report.

Fragmented, untrusted data

Inconsistent tracking, missing UTMs and duplicate records make even good analysis indefensible.

One connected system instead of a stack of deliverables

We build the measurement layer first, then the intelligence on top of it. Clean tracking, unified data, honest attribution, role-specific dashboards and AI analysis that surfaces the insight rather than waiting to be asked.

Trustworthy foundations

A documented measurement plan, server-side tracking, consistent taxonomy and validated data quality.

Revenue-grade attribution

Multi-touch models connecting first touch to closed-won, reconciled against finance.

AI-driven intelligence

Anomaly detection, cohort analysis and narrative insight generation, delivered proactively to owners.

Workflow

1
Measurement audit
2
Tracking implementation
3
Data unification
4
Dashboards and attribution
5
Insight and forecasting cadence

Everything inside the engagement

Scoped as a system with clear owners, review gates and outputs you keep.

Measurement strategy

A documented plan defining metrics, events, definitions and ownership across marketing, sales and operations.

Tracking implementation

GA4, server-side tagging, consent management, event schemas and UTM governance implemented properly.

Data unification

A warehouse layer joining ads, web, CRM, product and finance data into one consistent model.

Attribution modelling

Multi-touch attribution tracing revenue back to source, campaign, creative and content.

Executive dashboards

Live, role-specific dashboards for board, marketing, sales and operations, no spreadsheet assembly.

Campaign & channel reporting

Performance by channel, campaign and creative measured on pipeline contribution, not clicks.

Funnel & cohort analysis

Stage conversion, velocity, drop-off and cohort behaviour over time.

Forecasting

Predictive pipeline and revenue modelling with scenario planning for budget decisions.

Anomaly alerting

Automated detection of tracking failures, conversion drops and spend anomalies within hours.

AI insight briefings

Weekly generated analysis explaining what changed, why, and what to do about it.

The AiGnifier Growth Operating System™

Our process from discovery to scale

Eight disciplined stages. Every engagement runs the same operating method, so progress is predictable and auditable.

Discover

Audit the current state: market, competitors, funnel, data and internal workflows. Evidence before opinion.

Define

Fix the strategy, positioning, audience, success metrics and the commercial case for every workstream.

Design

Architect the system: narrative, experience, creative and the AI workflows that will run it day to day.

Deploy

Build and launch with governance, QA and human review gates. Nothing ships without an owner and a metric.

Drive

Activate demand. Campaigns, agents and distribution run in production against agreed pipeline targets.

Measure

One attribution layer for traffic, pipeline, conversion, cost and hours saved. No vanity metrics.

Optimize

Continuous improvement sprints informed by live data and AI analysis of what is actually converting.

Scale

Compound what works, more markets, more channels, more automation, without proportional headcount.

Outcomes the board can measure

We report in pipeline, cost and hours reclaimed, the language your leadership team already uses.

Source of truth

One reconciled measurement layer for the whole business.

Better budget efficiency

From reallocating spend to verified revenue drivers.

Less manual reporting time

Automated dashboards replace monthly spreadsheet builds.

Hours to anomaly detection

Down from weeks of undetected failure.

Budget allocated on verified revenue contribution

Board reporting that survives scrutiny

Marketing and sales working from the same numbers

Tracking failures caught in hours rather than weeks

Forecasts accurate enough to plan hiring and inventory against

Analyst time spent on interpretation instead of assembly

Technology stack

The tools running behind this service

Governed, interoperable and selected for reliability, not novelty.

GA4

Behavioural analytics and conversion measurement.

BigQuery

Warehouse layer for unified, queryable data.

Supabase

Application and attribution data storage.

Looker Studio

Executive and operational dashboards.

Segment

Event collection and consistent data routing.

n8n

Data pipelines, syncs and alerting workflows.

OpenAI

Narrative insight generation and anomaly explanation.

HubSpot

CRM pipeline and revenue source data.

Education

Multi-brand education group

Four institutional brands, six marketing channels and three CRM instances. Enrolment reporting took eleven days to compile monthly and no one could state the true cost per enrolment by channel.

Before

11 days to compile monthly reporting
No verified cost per enrolment
Three unreconciled CRM instances
Tracking failures found weeks later

After

Live dashboards updated hourly
Cost per enrolment by channel and brand
One unified reporting model
Anomaly alerts within hours

Less reporting effort

Lower cost per enrolment

Budget reallocated to winners

0.0x

Return on investment

“We stopped debating whose numbers were right and started deciding what to do about them.”

Group Marketing Director, education group

Questions

Analytics & Growth Intelligence answered

Everything decision-makers ask us before committing to an engagement.

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30-minute working session. You leave with a growth system map, whether we work together or not.