Profit analytics for e-commerce brands
Find the money hiding in your store dataThe E[X] Group — ad spend, margin and pricing analysis for Shopify and beyond
I take your store, ad and cost data and come back with a short deck of figures and comparison tables: where spend is wasted, which products actually make money, and what to change before the next peak. No jargon required.
+20%
holiday revenue
from moving ad spend two weeks earlier into the demand ramp
−31%
wasted ad spend
after cutting campaigns that were buying customers who would have bought anyway
18 SKUs
losing money
identified in a top-100 catalogue once returns and shipping were included
Illustrative examples of the kind of result these analyses surface.
Tell me what you want to know
One question is enough to start — "is Meta actually profitable for us?", "which products lose money?", "should we discount in November?". I reply within two business days with what data I would need and what the answer would take.
What I analyse
Every one of these ends in the same place: a number, a comparison table, and a recommendation you can act on this quarter.
Ad spend returns by channel
Which of Meta, Google, TikTok, email and affiliates actually pays back — and where the next euro of spend belongs.
A/B and holdout tests
Set up and read tests so a "winner" is a real difference and not noise you paid to chase.
Incrementality and geo tests
How many of those sales would have happened anyway without the ad. The number platforms never show you.
Margin by product and SKU
Which bestsellers quietly lose money once COGS, shipping, discounts and returns are subtracted.
Discount and promo effectiveness
Whether a promotion grew profit or simply pulled forward orders you would have received anyway.
Customer value and CAC payback
What a customer is worth by cohort and acquisition channel, and how many months it takes to earn the acquisition cost back.
Repeat purchase and churn
Who comes back, when they come back, and which products or flows make a second order more likely.
Returns and refunds
Which products, sizes and regions drive returns, what they cost you, and what the fix is worth.
Pricing and elasticity
How volume actually responds to a price change, so a price move is a decision instead of a gamble.
Shipping and fulfilment cost
Free-shipping thresholds, carrier and region cost differences, and the true delivered cost per order.
Inventory and demand forecasting
What to stock ahead of a peak so you avoid both stockouts on winners and cash tied up in dead stock.
Seasonality and holiday planning
When demand actually rises, and how far ahead of it spend and promotions should be moved.
Funnel drop-off
Where revenue leaks between visit, add-to-cart, checkout and paid order — and what closing each gap is worth.
What you get
Two documents at the end of every engagement — one to decide from, one to verify with.
Findings presentation — 5 to 10 pages
Built for the person making the call. Headline numbers, side-by-side comparison tables, before-and-after charts, and a ranked list of actions with the expected impact of each. No statistical vocabulary required.
- Headline figures and what changed
- Comparison tables by channel, product and period
- Charts that make the answer obvious
- Ranked actions with expected upside
Official technical report
The full argument behind the numbers: every model used, why it was chosen over the alternatives, the assumptions checked, the robustness tests run, and the limits of what the data can support. For your CFO, your board, or any analyst who wants to audit the work.
- Model specification and justification
- Assumption and diagnostic checks
- Robustness and sensitivity analyses
- Honest statement of limitations
Your data: what I use and where it comes from
A short guide so we start on the same page. Most brands already have everything I need — it is a handful of exports.
Store platforms
- Shopify & Shopify Plus
- WooCommerce
- BigCommerce
- Magento / Adobe Commerce
- Wix Stores
- Squarespace Commerce
- Salesforce Commerce Cloud
- Shopware
- PrestaShop
- Ecwid
Marketplaces
- Amazon Seller Central
- Etsy
- eBay
- Walmart Marketplace
- Faire
Ads, email & analytics
- Meta Ads Manager
- Google Ads
- TikTok Ads
- Amazon Ads
- Google Analytics 4
- Klaviyo
Money & costs
- Stripe
- PayPal
- Shopify Payments
- Xero
- QuickBooks
- Your COGS spreadsheet
How to pull your exports
Orders and products from your store
Shopify: Admin → Analytics → Reports → Export, plus Orders → Export as CSV. WooCommerce, BigCommerce and Magento all have an equivalent order export. Easiest of all: add me as a staff user with report access.
Ad spend from each platform
In Meta Ads Manager, Google Ads or TikTok Ads: Reports → export CSV at campaign and day level, including spend, impressions, clicks, conversions and attributed revenue.
Traffic and funnel from analytics
GA4: Explore → export your sessions, landing pages and checkout funnel — or simply grant me viewer access.
Email and SMS performance
Klaviyo (or your equivalent): export campaign and flow performance with revenue attributed per send.
Your costs
A simple spreadsheet is enough: cost of goods per SKU, average shipping and packaging cost, payment fees, and fixed monthly costs. This is what turns revenue analysis into profit analysis.
Send it over
Raw CSVs are perfectly fine — messy, inconsistent or partial exports included. Cleaning and reconciling the data is part of the job, not something you need to do first.
What makes the analysis stronger
- 12+ months of daily data lets me separate seasonality from a real change.
- Campaign-level ad spend beats account totals — that is where the decisions live.
- Per-SKU costs unlock margin work; without them I can only speak to revenue.
- All data and findings are confidential, and I sign an NDA whenever you need one.
Pricing
Sized for brands between $1M and $20M in annual revenue. Fixed scope, fixed fee — agreed before any work starts.
Focused audit
from €2,500
One question, answered end to end.
- A single decision — e.g. ad spend efficiency or SKU margin
- Findings deck plus technical report
- One review call to walk through the results
- Typically 1–2 weeks
Most popular
Full profit review
from €6,000
The whole picture, in one engagement.
- Ad returns, margin by SKU, LTV/CAC, returns and promo effectiveness
- Incrementality read on your largest spend channels
- Prioritised roadmap of what to change first
- Findings deck, technical report and working session
Ongoing partner
from €2,500 / month
A quantitative team member on retainer.
- Monthly reporting on the metrics that move profit
- Test design and readouts before you commit budget
- Forecasts ahead of peak season
- Direct line for ad hoc questions
Final pricing depends on scope, number of data sources, and the state of the data. You get a fixed quote after a short scoping call — no hourly billing surprises.
How it works
Four steps from your first message to a decision you can defend.
Tell me the decision
We start from the choice you are trying to make — scale a channel, reprice a range, plan Q4 — not from a dataset.
Get the data in
You export what you have using the guide above. I clean, reconcile and sanity-check it against your own reporting.
Analyse and verify
Models are fitted and then stress-tested. If a result does not survive the robustness checks, you hear that instead of a confident-sounding number.
Deliver and act
You get the short findings deck, the full report, and a call where we agree what changes next week.
Under the hood
You never need to read this part. But if you or your analyst want to know what is actually behind the figures, here it is — properly specified, properly verified, in R and Python.
Frequently asked questions
Practical answers about working together.