Build your team'scapability to leadgrowth with confidence.
Growth blueprint: your data strategy, plan and set-up in 4 weeks.
Then we train your team to own it, or run it with you.
- Measurement
- Channel health
- Experimentation
- Forecasting
- AI workflows
Proudly partnered with
What we do
Data strategy, measurement strategy and training.
Data strategy
What to collect, how it's structured and who owns it. We set up the data foundation your team builds on.
Measurement strategy
We decide which method answers which budget question, and how MMM, tests, attribution and search data fit together.
Training
We train your team to run it, implement it with them and support them while they run it.
Results from client work
As a PPC marketer, understanding how much additional business your advertising actually generates is an essential next step. Working with Charlie has helped me move beyond platform metrics and give insights to my clients.
Where to start
Growth blueprint
A lot of companies take six months to a year to figure out what to do. We give you the blueprint in four weeks.
Your data strategy, a prioritised plan and your data set up, starting with a budget waste audit.
Week 4 of 4: the data foundation is set up. Then you choose.
Growth diagnostic
Budget waste audit
The waste it finds usually covers most of the blueprint's cost.
- Competition and brand visibility evaluation
- Channel audit
- Performance and revenue review
- Measurement audit
- Lightweight MMM
- Data structure audit
- Team AI and technology audit
Data strategy and priorities
A clear, prioritised plan, with next steps across people, data, tools and measurement.
Data set-up
We set up the data foundation the plan calls for.
Then you choose
Capital Allocation
We improve the system with you
We implement the priorities and run the system with your team.
Training
We build the capability in your team
We train your team to run it, implement it with them and support them while they run it.
The problems we solve
Your analytics live in other people's tools
Data strategy
Your data sits in vendor dashboards, agency reports and platform numbers. Each shows part of the picture, and nobody inside owns the whole.
Team capabilities
Your team is working out AI on its own, and the analysis your budget decisions need sits with outside vendors.
Measurement
When the budget decision comes, MMM, attribution and platform numbers disagree, and nobody can say which one to trust.
What your team will be able to do
Everything we build stays yours: your data, your measurement, your AI workflows.
Measurement
Read MMM, tests and attribution together, so no single number decides the budget.
Channel health
Find waste, bot traffic and placements that get clicks but no sales.
Experimentation
Design geo and lift tests, and read them before you move national budget.
Forecasting
Plan spend and revenue ahead, and say how sure you are.
AI workflows
Run your own analysis with AI, on your own data, without waiting on a vendor.
Our growth philosophy
The Deathzone
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.
The formula
The one equation the whole thing hangs off.
Once you see it, budget arguments stop being opinions.
AB, Available Buyers
Everyone performance marketing can actually win: people who are in-market and already willing to buy from you. Spend past this pool and you are in the Deathzone.
ICP, Your category
Everyone who could ever buy what you sell. You do not grow this. It is the size of the pond.
%IM, In-market now
The share ready to buy today. Performance marketing captures this demand, it does not create it.
%WBFU, Willing to buy from you
The share who would choose you when they are ready. That is brand. It is the one lever that expands the whole pool, and the one your tools do not measure.
Performance marketing can only win the people who are both in-market and already willing to buy from you. Spend past that pool and you are in the Deathzone. The only term you can grow is the share willing to buy from you, and that is brand. We measure it, and we tell you which spend is draining the pool and which is growing it.
How we measure
Six layers of evidence
MMM, attribution and experiments each see part of the picture. We read six layers of evidence together, so no single tool decides where the budget goes.
Growth quality
Is preference growing?
Share of search · Branded organic search growth · Baseline revenue · Revenue per branded search
We either run it for you, or train your teams to do it.
In practice
Seven ways we find the growth
Every case is one of two moves: cutting spend that drains your Available Buyers, or building the share willing to buy from you. Both come straight off the formula.
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 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.
The growth already in your budget
How much of your budget is not driving growth?
Enter your annual marketing spend. We'll show you how much of it the benchmarks say you could put back behind growth.
Budget you could redirect to growth
$10M to $15M
Based on the 20 to 30% waste range observed
$50M
Total annual spend
$10M to $15M
Likely not incremental
$35M to $40M
Actually driving growth
The Growth blueprint starts with a budget waste audit. The waste it finds usually covers most of the blueprint's cost.
* Based on historical observation. The number can vary. A first diagnosis will help to have a better directional number. If you are using last touch and platform attribution you are likely to be in that range.

About
Charlie de Thibault, founder
I started in investment banking and financial services. I moved into measurement at Skai, working with large advertisers across retail, e-commerce, airlines and financial services, then at Oracle, where I helped build and scale the measurement capability as Measurement Manager and Principal Data Strategist.
I work on your own data, explain what I find in plain words and tell you how sure I am.
Start with a 30-minute call.
Tell us where your data and team are today, and we'll say whether the Growth blueprint fits.
Book a call