Find the growth your budget is already paying for.
20-30% of enterprise marketing spend isn't driving incremental growth. We find it, reallocate it, and build the intelligence layer that stays, permanently.
For B2C brands with long consideration journeys, offline sales, and high-ticket purchases.
Your CMO walks into a board meeting
with five problems
AI investment they can't justify
The board asks what the AI spend is producing. They don't have an answer that survives scrutiny.
Capital going to the wrong channels
Platform reporting says everything is working. But the CFO sees revenue flat and asks where the growth is.
Measurement outside their ecosystem
The analytics function lives in a SaaS vendor's dashboard. They're renting intelligence they should own.
A SaaS stack built for everyone
Generic tools built for generic companies. None of them solve their specific measurement problem.
Their senior analyst just handed in his notice
Six months of knowledge, context, and institutional memory walking out the door. And nobody documented it.
One engagement. One infrastructure. All five solved.
Intelligence that stays
when we leave
We don't sell you a dashboard. We build a growth intelligence layer inside your infrastructure trained on your data, compounding with every decision, permanently yours.
The Methodology Engine
Our core intelligence gets smarter with every deployment.
- Marketing Mix Modelling (MMM)
- Experimental design
- Mid funnel modelling
- Pricing
- Forecasting
- Bot traffic detection
- Campaign and ad auditor
- Brand tracking
Your Growth Intelligence
Deployed inside your infrastructure. The brain stays when we leave.
- Your data, your infrastructure
- Memory layer that compounds decisions
- Analyst knowledge captured automatically
- Your team operates it independently
It's Yours
Deployed inside your infrastructure. Your data never leaves. No vendor lock-in. Cancel anytime, the brain stays.
It Compounds
Every test, decision, and insight captured automatically. After 6 months, it knows your markets, channels, and CFO's questions.
It Evolves
Every improvement GD makes across all deployments flows to you. You benefit from the network without sharing your data.
"When the engagement ends, the intelligence stays.
Inside your infrastructure. Trained on your data. Permanently yours."
No vendor lock-in. No data leaving your walls. Cancel anytime, the brain stays.
Cases
Channels taking credit they didn't earn
Platform dashboards double count. Multi-touch attribution understates anything that touches offline. We run incrementality tests (difference-in-differences, propensity-score matching) to isolate the lift each channel actually drove.
Outcome: reallocation, not more spend.
The traffic you paid for that wasn't human
Platform-reported clicks and conversions include a layer of bot traffic. We audit it against GA4 and server logs, isolate the fake portion, and clean it out of your attribution numbers before decisions get made on top.
Outcome: decisions made on real demand.
Find the 20 to 30% already paying for nothing
Most budgets carry a layer of spend that is not incremental. It converts users who would have bought anyway. We isolate that layer across paid, promo, and channel mix, and rebuild the plan around what actually drives growth.
Outcome: same budget, more growth.
Stores doing the brand work no one credits
Every new store is a natural experiment. We measure the halo on ecomm in the surrounding postcodes, isolate cannibalization between stores, and size catchments before the next opening. The numbers usually surprise the team that thought stores only sold to walk-ins.
Outcome: opening decisions on real area lift.
Half your search clicks started somewhere else
Customers don't search in a vacuum. Half the people who click your Google non-brand ads cite another channel as what made them look. We run surveys at the point of conversion, map the cited channels back to spend, and find the upper-funnel work quietly feeding your search demand.
Outcome: fund the channels creating the demand search captures.
Same spend. +15% Share of Search. +60% revenue.
One client shifted budget from bottom-of-funnel to top-of-funnel discoverability. Share of Search climbed first; revenue followed two years later. We measure Share of Search weekly against the category and run lag correlations to find the same signal in your data.
Outcome: brand momentum that lands in revenue.
Marketing can't win at the wrong price
Marketing fights with one hand tied when the price is wrong. Most plans treat price as fixed and lean harder on media. We measure how demand moves with competitor price gaps and your own price changes, then tell you whether the next growth dollar belongs in price or in media.
Outcome: the next dollar in the right place, price or media.
Channels taking credit they didn't earn
Platform dashboards double count. Multi-touch attribution understates anything that touches offline. We run incrementality tests (difference-in-differences, propensity-score matching) to isolate the lift each channel actually drove.
Outcome: reallocation, not more spend.
The traffic you paid for that wasn't human
Platform-reported clicks and conversions include a layer of bot traffic. We audit it against GA4 and server logs, isolate the fake portion, and clean it out of your attribution numbers before decisions get made on top.
Outcome: decisions made on real demand.
Find the 20 to 30% already paying for nothing
Most budgets carry a layer of spend that is not incremental. It converts users who would have bought anyway. We isolate that layer across paid, promo, and channel mix, and rebuild the plan around what actually drives growth.
Outcome: same budget, more growth.
Stores doing the brand work no one credits
Every new store is a natural experiment. We measure the halo on ecomm in the surrounding postcodes, isolate cannibalization between stores, and size catchments before the next opening. The numbers usually surprise the team that thought stores only sold to walk-ins.
Outcome: opening decisions on real area lift.
Half your search clicks started somewhere else
Customers don't search in a vacuum. Half the people who click your Google non-brand ads cite another channel as what made them look. We run surveys at the point of conversion, map the cited channels back to spend, and find the upper-funnel work quietly feeding your search demand.
Outcome: fund the channels creating the demand search captures.
Same spend. +15% Share of Search. +60% revenue.
One client shifted budget from bottom-of-funnel to top-of-funnel discoverability. Share of Search climbed first; revenue followed two years later. We measure Share of Search weekly against the category and run lag correlations to find the same signal in your data.
Outcome: brand momentum that lands in revenue.
Marketing can't win at the wrong price
Marketing fights with one hand tied when the price is wrong. Most plans treat price as fixed and lean harder on media. We measure how demand moves with competitor price gaps and your own price changes, then tell you whether the next growth dollar belongs in price or in media.
Outcome: the next dollar in the right place, price or media.
Channels taking credit they didn't earn
Platform dashboards double count. Multi-touch attribution understates anything that touches offline. We run incrementality tests (difference-in-differences, propensity-score matching) to isolate the lift each channel actually drove.
Outcome: reallocation, not more spend.
The traffic you paid for that wasn't human
Platform-reported clicks and conversions include a layer of bot traffic. We audit it against GA4 and server logs, isolate the fake portion, and clean it out of your attribution numbers before decisions get made on top.
Outcome: decisions made on real demand.
Find the 20 to 30% already paying for nothing
Most budgets carry a layer of spend that is not incremental. It converts users who would have bought anyway. We isolate that layer across paid, promo, and channel mix, and rebuild the plan around what actually drives growth.
Outcome: same budget, more growth.
Stores doing the brand work no one credits
Every new store is a natural experiment. We measure the halo on ecomm in the surrounding postcodes, isolate cannibalization between stores, and size catchments before the next opening. The numbers usually surprise the team that thought stores only sold to walk-ins.
Outcome: opening decisions on real area lift.
Half your search clicks started somewhere else
Customers don't search in a vacuum. Half the people who click your Google non-brand ads cite another channel as what made them look. We run surveys at the point of conversion, map the cited channels back to spend, and find the upper-funnel work quietly feeding your search demand.
Outcome: fund the channels creating the demand search captures.
Same spend. +15% Share of Search. +60% revenue.
One client shifted budget from bottom-of-funnel to top-of-funnel discoverability. Share of Search climbed first; revenue followed two years later. We measure Share of Search weekly against the category and run lag correlations to find the same signal in your data.
Outcome: brand momentum that lands in revenue.
Marketing can't win at the wrong price
Marketing fights with one hand tied when the price is wrong. Most plans treat price as fixed and lean harder on media. We measure how demand moves with competitor price gaps and your own price changes, then tell you whether the next growth dollar belongs in price or in media.
Outcome: the next dollar in the right place, price or media.
Channels taking credit they didn't earn
Channels claim credit for sales they did not create. Platform dashboards stack every touchpoint that was on the path; multi-touch attribution flattens contributions evenly. Neither tells you what would have happened without the spend.
What we do
We design quasi-experiments around the channels you suspect. Difference-in-differences on geo splits, where one region keeps spend and another drops. Propensity-score matching to compare exposed and unexposed customers with similar profiles. Each test isolates the lift the channel actually drove.
What you get
A clean number per channel. The spend that earned its place, the spend that did not. A reallocation plan that finds growth without needing a budget increase.
Outcome: reallocation, not more spend.
The traffic you paid for that wasn't human
Platform-reported clicks and conversions include a layer of bot traffic. The optimisation engine learns from data that includes ghost users, and the budget keeps following them.
What we do
We compare platform-reported events against GA4 and your own server logs. Patterns surface quickly: impossible click rates, no scroll, no time-on-page, clusters from suspicious IP ranges. We score each layer for likely automation and pull it out of the conversion dataset before any decision gets made on top.
What you get
A clean conversion baseline. Audit-grade inputs for the incrementality work that follows. A defensible plan to defund traffic that was never going to buy.
Outcome: decisions made on real demand.
Find the 20 to 30% already paying for nothing
Most marketing budgets carry a layer of spend that is not incremental. It converts users who were going to buy anyway, and the platforms still report the conversion. The plan looks healthy while growth quietly stops.
What we do
We isolate the non-incremental layer across paid media, promotional cycles, and discount mechanics. Geo holdouts show what happens when a channel goes dark. Promo testing shows what margin you keep when the offer comes off. The two together size the reclaimable layer.
What you get
A reclaimable percentage of total spend, typically 20 to 30 percent in the audits we run. A reallocation plan that frees budget without cutting growth. A margin number that does not depend on the next discount cycle.
Outcome: same budget, more growth.
Stores doing the brand work no one credits
Stores get measured on what walks in, but they are quietly doing brand work for the surrounding area. Online sales rise in the catchment. Direct traffic increases. Search volume for your brand grows. None of it shows up in foot traffic numbers.
What we do
Every new store is a natural experiment. We measure ecomm and direct demand before and after the opening, in postcodes inside the catchment and postcodes outside. We control for cannibalisation between nearby stores. We size the area lift at the right geography for the next opening decision.
What you get
A real area-lift number per store and per format. A catchment map that drives the next location pick. A capital case for property and CFO conversations that has the brand effect priced in.
Outcome: opening decisions on real area lift.
Half your search clicks started somewhere else
Customers do not search in a vacuum. Half the people who click your Google non-brand ads cite another channel as what made them look. The platform takes credit for capturing demand it did not create.
What we do
We run short surveys at the point of conversion. One question, well-framed: what made you look us up. The responses get coded back to your channel mix. Over time the pattern stabilises and shows you which upstream channels are loading the search funnel.
What you get
A demand-creation map across your full channel mix. Specific channels you can fund harder because they are doing the upstream work. Search budget right-sized to the demand it actually earned.
Outcome: fund the channels creating the demand search captures.
Same spend. +15% Share of Search. +60% revenue.
One client held total spend flat, lifted Share of Search by 15 percent, and grew revenue 60 percent over two years. The play was reallocation: budget shifted from bottom-of-funnel to top-of-funnel discoverability. Share of Search climbed first, revenue followed.
What we do
We measure your Share of Search week over week against the category, then run lag correlations against revenue. The relationship usually appears in both directions, but is much stronger when Share of Search leads Sales, which is consistent with brand-driven demand creation. Spend gets used as a control variable, and seasonality gets segmented out so the signal stays clean.
What you get
A leading indicator of brand strength, refreshed weekly. A reallocation case from bottom-of-funnel to top-of-funnel that does not require a budget increase. A signal the CFO can read months before any quarter closes.
Outcome: brand momentum that lands in revenue.
Marketing can't win at the wrong price
Most plans treat price as fixed and lean harder on media when growth slows. Marketing can't win at the wrong price. Sometimes the next growth dollar belongs in a price move, not another impression. This is permanent price work, not promotion: discount cycles train customers to wait and rarely grow the brand, while pricing the product correctly compounds.
What we do
We pull competitor pricing alongside your own price history and detect price-change events automatically. Pre/post analysis on each event tells us how units, revenue, and gross profit moved. Order-volume models attribute demand to price gap, site actions, and demand signals, separating the price effect from the media effect. Scenario modelling predicts orders under alternative price points so the price-vs-media tradeoff is explicit.
What you get
An optimal price by product group, with a confidence range. A reallocation recommendation showing where the next dollar grows margin fastest, price or media. A pre/post readout on every price move you make, attributed to revenue, units, and margin. The price signal wired into the brain so price decisions sit alongside media decisions, not separately.
Outcome: the next dollar in the right place, price or media.
Most companies hit a point where growth stalls even though spend keeps climbing
Your measurement tools favor what works this quarter. They structurally undervalue brand investment and overstate activation performance. The result: you optimize into a corner.
This is the DEATHZONE, the gap between what you're spending and the growth you're getting. Not because you're spending wrong. Because you're measuring wrong.
How much of your budget is not driving growth?
Enter your annual marketing spend. We'll show you what the industry benchmarks say you're losing.
Estimated budget not driving incremental growth
$15M — $25M
Based on 20-30% waste range observed across incrementality testing
Want to know exactly which channels are in the Deathzone?
Find out where your budget is leaking
A quick diagnostic that shows whether your measurement setup has blind spots and where the hidden growth is. No commitment. Just clarity.
Book your free diagnostic
A few quick questions so we can review your setup before the call and come prepared with what we can already see from the outside.
Got it. Thanks.
We'll review your details and be in touch. If you'd like to pick a time now, you can book a slot below.
From leaking budget to compounding intelligence
Find the Waste
Pinpoint the 20-30% of ad spend that isn't driving real growth. Not opinions, causal measurement.
Reallocate Smartly
Move spend to the channels with real feedback and ROI. Capital to what earns it.
Prove It
Show CFO-ready numbers you can defend in a board meeting. Not platform vanity metrics.
Keep It
The intelligence doesn't leave when the engagement ends. It's already inside your infrastructure.
From first conversation to permanent intelligence
Every step designed to deliver value before asking for commitment.
Diagnose
We map where your growth is being missed. Share of Search analysis delivered in days.
From $700Deploy
One statement of work. We build your growth intelligence layer inside your infrastructure, trained on your data.
Engagement feeProve
We run analysis and a causality calendar to prove what is working, with full transparency on model limitations.
Full visibilityOwn
The brain stays. Your team runs it. GD provides methodology updates. Intelligence compounds.
Yours forever5 Measurement Blind Spots Costing You Growth
Most enterprise marketing teams are losing 20-30% of their budget to measurement gaps they can't see. This guide shows you exactly where to look.
- Why attribution overstates paid search by up to 12x
- The brand investment your tools structurally undervalue
- Where diminishing returns hide in your spend curve
- What platforms aren't telling you about their own performance
- How analyst turnover erases your measurement memory
Get the guide free
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Start where it makes sense. Scale when you're ready.
Share of Search
See where you're leaking. A diagnostic report delivered in days.
- Brand search visibility mapped
- Competitor share analysis
- Category trend identification
- Actionable recommendations
- Delivered in 5 business days
Workshop
Upskill your team on measurement that actually matters.
- Hands-on measurement training
- Custom to your data stack
- Incrementality fundamentals
- Team exercises included
- Follow-up support session
Growth
Build the intelligence layer. Full measurement and capital allocation.
- Marketing Mix Modelling (MMM)
- Experimental design
- Mid funnel modelling
- Pricing
- Forecasting
- Bot traffic detection
- Campaign and ad auditor
- Brand tracking
Charlie de Thibault
The marketing scientist who talks like a CFO.
Former investment banker with over a decade in financial services. Built measurement functions as a Data Scientist at Sky and Starling Bank. Saw the same problem everywhere: measurement tools telling half the story, and the half they missed was where the growth was.
Growth Dynamics exists to fix that permanently. Not another vendor you manage. An intelligence layer you own.
▶ Watch IntroGreat systems, even greater people
Charlie de Thibault
Founder & Methodology
Karis Dimond
Operations Manager
Alyasa Suleman
Content Specialist
What happens when your senior analyst hands in their notice?
The answer shouldn't be panic. It should be: nothing changes. The intelligence is already inside.