You Have Data.
You Don't Have
Answers.
Most businesses are drowning in dashboards and starving for decisions.
Pageviews, sessions, bounce rates — numbers that describe what
happened without explaining why, or telling you what to do next.
We turn your data into a growth system: clean, connected, and built to tell
you exactly where the money is going and what it’s returning.
Tell us what you're trying to build.
73%
of businesses are making decisions on inaccurate data
6–10×
ROI improvement when attribution is properly modelled
48hrs
Typical time to first actionable intelligence insight
Data without direction is just storage.
Every business we audit has the same problem: data that’s collected but not connected, tracked but not trusted, and reported but not acted on. GA4 installed but misconfigured. Ads running in one platform, organic in another, CRM in a third — with no thread linking them. Reports that show traffic going up while revenue stays flat, and nobody can explain why.
Growth Intelligence is the discipline of making your data actually useful. It means building a tracking infrastructure where nothing slips through the gaps. It means attributing revenue to the channels and campaigns that genuinely caused it — not just the last click that happened before someone bought. And it means applying AI and predictive modelling to identify what your competitors won’t see coming until it’s already happened.
We work at the intersection of data engineering, marketing strategy, and applied AI — so the insights we surface are tied to commercial decisions, not just analytical curiosity.
What Accurate Intelligence Moves
The metrics that shift when your data infrastructure actually works.
ROAS
Real return on ad spend — based on actual revenue, not modelled guesses
CAC
True cost of acquisition by channel, campaign, and cohort
LTV
Customer lifetime value with predictive 12-month projection
MRR↑
Monthly revenue growth rate tied to data-driven decisions
Where Does Your Business Sit on the Data Maturity Curve?
Stage 1
Blind
No tracking. Decisions made on instinct. No visibility into what's working.
Stage 2
Fragmented
Basic GA4 or UA. Siloed channel data. No cross-platform picture.
Stage 3
Conflicted
Data exists but platforms disagree. Attribution is a guessing game.
Stage 4
Connected
Clean, unified data. Single source of truth. Decisions made with confidence.
Stage 5
Intelligent
AI-driven insights. Predictive modelling. Marketing decisions made before the market moves.
Most of our clients arrive at Stage 2 or 3. We move them to Stage 4 in 30–60 days, and toward Stage 5 over the following quarter.
Your Analytics Are Collecting Data. They're Not Telling You the Truth.
The Problem
The Universal Analytics sunset forced millions of businesses onto GA4 — and most of them migrated with the same broken setup they had before, just in a different interface. Form submissions tracked as pageviews. Duplicate transactions inflating revenue figures. Conversion events firing on bots. Cross-domain journeys snapping in half. The data keeps coming in, but the picture it’s painting is fiction.
Accurate analytics starts with a foundation audit — identifying every tracking gap, misfire, and misconfiguration before layering in the new measurement logic your business actually needs. This isn’t about ticking compliance boxes. It’s about building a data model that reflects how your real customers actually move through your funnel — across devices, across channels, across sessions that might be days or weeks apart.
We work across GA4, Google Tag Manager, server-side tracking, and Looker Studio — building a tracking architecture where every meaningful user action is captured cleanly, every platform feeds from a consistent source of truth, and every stakeholder in your business has a dashboard that answers their specific questions without requiring a data analyst to interpret it.
Current State — Conversion Tracking Audit
7 issues found
£84,200
GA4 Revenue
£41,700
Actual Revenue
???
True Source
—
CRM Match
⚠ Duplicate transaction events detected. Offline conversions not imported. Cross-domain tracking broken at checkout.
- Full GA4 audit, reconfiguration, and event taxonomy rebuild
- Google Tag Manager setup, version control, and governance framework
- Server-side tracking implementation for iOS-resilient, privacy-compliant measurement
- Cross-domain and cross-device journey tracking architecture
- Custom Looker Studio dashboards built per stakeholder role (CMO, channel manager, e-commerce lead)
- CRM-to-analytics pipeline: offline conversions and lead quality feedback loops
- Data layer documentation so every future developer knows what's there and why
Analytics & Tracking KPIs
100%
Event accuracy rate post-implementation audit
CWV
Data freshness — time from action to dashboard visibility
≤5%
Acceptable data discrepancy between platforms
0
Duplicate transaction events or ghost conversions
Why Monarch
We’ve audited data setups across hundreds of businesses and the same mistakes keep appearing — often in organisations that have been with analytics agencies for years. We fix the foundation properly the first time, document everything, and train your team so they’re never dependent on us to read their own data.
Attribution KPIs
True
ROAS per channel based on data-driven attribution
Path
Most common high-value conversion path length and mix
Assist
Assisted conversion value by channel
iROAS
Incremental ROAS — what you'd lose if you cut a channel
We’ve helped businesses recover significant budget they were about to cut from channels that looked unprofitable under last-click — but were driving the majority of first-touch discovery. Correct attribution doesn’t just change how you read your data. It changes how you spend your money.
You're Crediting the Last Click. The Real Work Happened Six Touch points Ago.
The Problem
Last-click attribution is the accounting equivalent of giving the goal to the player who put the ball in the net — and ignoring the midfielder who won the ball, the winger who created the cross, and the manager who devised the tactic. It makes one channel look like a hero while every channel that contributed to the decision goes unrewarded, unfunded, and eventually cut.
The average B2B buyer makes 27 touchpoints before converting. Even in e-commerce, multi-session, multi-device journeys are the norm — not the exception. When your attribution model only sees the final touch, you’re flying blind on 26 of those 27 moments. You defund the channels that start conversations because you only see the channels that finish them.
We build data-driven attribution models that give appropriate credit to every meaningful touchpoint in the buyer journey — from the first blog post a prospect read six weeks ago to the retargeting ad that brought them back. Then we connect those models to your budget planning process, so channel investment decisions are made on real contribution data rather than platform-reported vanity ROAS.
Customer Journey — 8 Touchpoints, 22 Days to Conversion
Organic Search
Blog Article
Email Newsletter
Meta Ad
Google Ad
Direct Visit
Comparison Page
Conversion ✓
Last-click ignores 7 of 8 touchpoints that influenced this £4,200 conversion.
- Current attribution audit — identifying which channels are over- and under-credited
- Data-driven attribution model build in GA4 and custom modelling frameworks
- Cross-channel budget reallocation recommendations based on true contribution data
- Offline conversion imports: CRM pipeline stages, sales call bookings, in-store purchases
- Incrementality testing to validate channel contribution with controlled experiments
- Marketing mix modelling for larger budgets where platform data has inherent bias
- Monthly attribution review: channel contribution trends and budget efficiency analysis
Your Competitors Are Still Reading Last Month's Reports. You Could Be Ahead of Next Month's.
The Problem
Traditional analytics is retrospective. You find out that September was your worst month in October. You discover that a campaign wasted £14,000 after the budget has already been spent. You notice a churn spike in your customer data three weeks after the early warning signs were sitting there, unread, in a report nobody opened. Business intelligence built on hindsight is just an expensive post-mortem service.
Applied AI changes the relationship between your data and your decisions. Machine learning models trained on your historical patterns can identify which leads are most likely to convert before your sales team picks up the phone. Predictive LTV models can tell you which customer cohorts are worth investing in retention spend and which are natural one-time buyers. Anomaly detection surfaces problems the moment they emerge — not weeks later when the damage is done.
We build AI-powered insight systems that are specific to your business, your data, and your commercial questions — not off-the-shelf dashboards dressed up with a machine learning label. Whether that’s a churn prediction model for a SaaS platform, a demand forecasting engine for an e-commerce brand, or a campaign performance anomaly detector for a high-spend media buyer, we match the AI application to the business problem.
- AI Growth Intelligence — Live Signal Feed
- Anomaly detected: Google Ads CPC up 34% on "commercial flooring" terms — market shift or competitor entry event 2m ago
- LTV prediction: Cohort acquired via Meta Stories in Oct showing 2.3× predicted 12-month LTV vs. Search cohort 14m ago
- Churn risk: 18 accounts showing early disengagement signals — usage below threshold for 11 consecutive days 1h ago
- Opportunity: "fire suppression system installation" search volume up 67% this week — no paid coverage detected 3h ago
Monthly Growth Intelligence Summary — October
AI Insight
- Revenue concentration risk: 62% of October revenue came from customers with a single previous purchase. Retention cohort needs activation — predicted 4.1× LTV uplift if second purchase achieved within 45 days.
- Channel efficiency shift: Organic search CAC has decreased 18% month-on-month while Paid Social CAC has increased 29%. Budget reallocation of £3,200/month recommended to optimise blended CAC.
- Seasonality forecast: Based on 3-year cohort patterns, demand is predicted to peak in weeks 6–9. Recommend front-loading 35% of Q1 ad budget into that window.
- Predictive LTV modelling — identify high-value customers at acquisition, not in hindsight
- Churn prediction models with early-warning signal dashboards
- Demand forecasting for inventory and campaign planning
- Campaign anomaly detection — automated alerts for performance deviations
- AI-generated monthly growth intelligence reports with prioritised action recommendations
- Natural language query dashboards — ask your data a question in plain English
- Competitive intelligence monitoring: search trend shifts, share-of-voice changes
AI Growth Intelligence KPIs
LTV↑
Customer lifetime value prediction accuracy and uplift
Churn↓
Churn rate reduction via early-intervention signals
Speed
Time-to-insight: from signal detection to recommendation
Decisions
Data-driven decisions made per week vs. prior period
We don’t sell you an AI platform and walk away. We define the business question first, build the model around that question, and then integrate the output directly into the workflow of the people who need to act on it. The best AI insight is the one that actually changes a decision — not the one that looks impressive in a demo.
200+
Analytics infrastructures audited, rebuilt, and documented
48hrs
Average time from audit completion to first actionable findings
£2.4M
Ad spend reclaimed from misattributed channels across client portfolio
6–10×
ROI improvement range when attribution modelling is corrected
We turn your data into your
competitive edge.
Strategy Before Software
We don't lead with platforms. We start with the questions your business most urgently needs answered — then choose the right tools, models, and data connections to answer them. Technology in service of insight, not the other way around.
No Black-Box Reporting
Every model we build is documented. Every insight we surface comes with the reasoning behind it. Your team understands where the numbers come from — and they can challenge them, refine them, and own them. We don't create dependency; we build capability.
Connected to Your Marketing, Always
Because we also manage SEO, paid media, and content for our clients, our analytics and attribution work is plugged directly into the strategy. Insights don't sit in a separate report — they inform tomorrow's campaign decisions and next month's budget allocation.
Built for Your Business, Not a Template
Every client has different data maturity, different commercial questions, and different team workflows. We don't deploy standard dashboards and call it implementation. We build measurement frameworks shaped around your specific business model, revenue logic, and decision cadence.
You Own Every Data Asset
GA4 property, BigQuery datasets, Looker Studio reports, custom model documentation — everything is in your accounts, in your name, fully documented. If you ever leave, you leave with a data infrastructure that's more valuable than the one you came in with.
Speed to Insight
Most analytics projects take months to produce the first useful finding. We deliver an initial audit report within 48 hours of access, a full tracking rebuild within 2 weeks, and first predictive model outputs within 30 days. You're making better decisions within a month.
Your data is already telling you something.
You just can't hear it yet.
what’s broken, what’s missing, and what it’s costing you — in clear,
plain language your whole leadership team can act on.