Data analysis
Margin-based data analysis that shows where your margin really sits.
Measuring is step one, but a clean number doesn't say much on its own. Here we put your conversion data next to your purchase prices, your shipping costs and your returns, and look for the places where money leaks away or gets left on the table. They're usually somewhere different from where you'd expect.
The problem
Most online stores don't have a data shortage. They have too little time to do anything with it, and no way to translate revenue figures into profit.
- Revenue per campaign sits in Google Ads, margin sits in your backend, and the two never meet.
- Returns and shipping costs don't appear in any ad dashboard, even though they eat up the entire margin on some product groups.
- Bestsellers automatically get the most budget, even when they're at the bottom of the margin list.
- The analysis stops at describing what happened, without leading to a decision.
The opportunity
Once margin, returns and shipping costs are in your data, the picture tips. Products that look good on ROAS sometimes turn out to be loss-making, and categories you barely looked at suddenly have room to scale. That same analysis feeds the rest of the system: the bidding strategy in your campaigns, the priorities in your content calendar, and whether a channel continues or stops. What you get from us isn't a report full of observations, but a list of what we'd change and why.
Our approach
How we pull your numbers apart.
We work in GA4, Looker Studio and, where needed, BigQuery, supplemented with your own order and margin export.
Margin in your data
We link purchase prices, shipping costs and return rates to your product data, so every order gets a profit figure instead of just a revenue figure.
Channel contribution
Which channels bring in new customers, and which ones pick up orders you'd have gotten anyway? We look at assisting paths and at the difference between branded traffic and the rest.
Product and category analysis
Profit per order, return rate and room to scale, per product group. We base the bidding strategy in your campaigns on this list.
Customer value and repeat purchases
What a customer delivers over the long term. For stores with a lot of repeat purchases, the first order can afford to cost more than you currently accept.
Search data next to sales data
We put search terms from your campaigns and from Search Console next to what actually sells, so the content calendar covers questions with revenue behind them.
From analysis to decision
Every finding gets an action, an expected impact and a place in the plan. Otherwise it becomes a nice document that nobody opens again.
In the Growth System
Stage 02: this is where the opportunities come from.
Analysis sits between measuring and doing. What surfaces here determines where the ad budget goes in stage 03 and which pages get tackled first in stage 04. It's also the stage where we test whether organic and paid actually reinforce each other for your store, instead of just assuming it.
View the full Growth System- 01 Measure
- 02 Discover
- 03 Attract
- 04 Get found
- 05 Scale
Frequently asked questions
What clients usually ask.
Missing a question? Email or call us, the lines are short here.
Does my tracking need to be sorted first?
Largely, yes. Analysing data that's full of gaps produces conclusions that are just wrong, and that's more dangerous than no conclusion at all. We always check how reliable your measurement is first, and tell you if something else needs to happen before this.
How do you get hold of my margins?
Usually from an export from your online store or your accounting software. If that's not possible, we work with margin groups per category. Exact per-item figures are nice, but a good approximation per product group already gets you a long way.
Is this a one-off or ongoing?
Both happen. We often start with a one-off review, and it then feeds into the monthly report and the quarterly session afterwards. Margins and return rates shift over time, after all.
Do you need BigQuery?
Not always. For many stores, GA4, Looker Studio and an order export are enough. We bring in BigQuery when your data volume or your questions call for it, for example with long customer journeys or lots of product variants.
What do I actually get delivered?
A profit breakdown of your channels and product groups, plus a prioritised list of what we'd change. In a session, we walk through it together, so you see for yourself where the numbers come from.
There's a good chance your bestseller is your worst product.
Bring your margins to the growth session, and we'll work out on the spot which product groups are advertising below cost price.
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