One set of store numbers your whole team trusts, from order to repeat purchase
Shopify says one thing, Meta says another, and Klaviyo claims the rest. Raquel pulls them into a single view built on your actual orders. You see what's making money, what's just taking credit, and which customers come back.
Does every app in your stack claim the same sale?
- Add up the revenue each tool takes credit for, and you get more than you actually sold.
- You know top-line revenue but not margin by product after discounts, shipping, and returns.
- Nobody can say how many first-time buyers came back for a second order.
- Weekly trading meetings start with 20 minutes of "which number is right?"
Picture a Shopify skin and body care brand selling around $4M a year. Meta Ads Manager reports a strong return on ad spend. Klaviyo attributes a big share of revenue to its flows. GA4 credits organic search. Shopify shows a single total that's smaller than all three claims combined. The founder is about to raise ad spend for the holidays. She doesn't know which report to believe. The ecommerce build reconciles every claim to Shopify's orders. Then it adds the piece most brands lack: what each customer group is worth after the first purchase.
Why is ecommerce analytics priced as a range?
A single-storefront brand with Shopify, GA4, and Klaviyo is the lighter end. Add a wholesale channel, a subscription app, or Amazon, and there's more to connect. Product costs scattered across supplier invoices add more to reconcile. Raquel fixes your number once she's seen your stack.
How does the ecommerce analytics build run?
- 01Stack review and the decisions you need to make
- 02Order-level data pulled into one place
- 03Reconcile every tool against Shopify orders
- 04Build the trading, margin, and cohort views
- 05Walk-through, training, and handover
Raquel did this work in-house as a digital analytics manager at an eCommerce company: GA4 tracking, SQL in BigQuery, and Tableau dashboards for executives.
All the steps, in detail
- Raquel reviews every app that reports revenue: Shopify, GA4, Klaviyo, Meta Ads, Google Ads, and any subscription or review apps.
- She asks which decisions are hardest right now: ad budget, discount strategy, or which products to restock.
- She brings order-level data into one place, usually BigQuery or Google Sheets, keyed to Shopify order IDs.
- She checks GA4 purchase tracking against those orders and notes any gaps.
- She compares what Meta and Klaviyo claim with the orders they can actually be tied to.
- She builds contribution margin by product and by channel, from your product costs, shipping, discounts, and returns.
- She builds cohort views: repeat purchase rate and revenue per customer, by first-order month and by acquisition channel.
- She builds a weekly trading view for your team meeting, in Looker Studio or Tableau.
- Your team uses it for two weekly cycles. They flag anything that doesn't match how they think about the business.
- She revises, documents every definition, and trains the people who will use it.
What does the ecommerce analytics build include?
- Order-level data from Shopify joined to GA4, Klaviyo, and Meta Ads
- A reconciliation of each tool's revenue claims against real orders
- Contribution margin by product and by channel
- Customer cohort views: repeat rate and revenue per customer over time
- A weekly trading dashboard in Looker Studio or Tableau
- A metric glossary written for a founder, not an analyst
- A training session for the team that runs the weekly meeting
What you get, what this is not, and what you need to bring
What you get
- Revenue that adds up to what Shopify actually recorded
- A view of which products and channels make money after costs
- An early read on whether new customers are worth what you pay to acquire them
What this is not
- Not a replacement for your attribution app or Shopify reports. It checks them against your orders and puts them in context.
- Not ad buying or email marketing. Raquel shows where the money works; your team or agency runs the campaigns.
- Not a forecast of next year's sales.
- Not a guarantee of higher revenue or better ad returns.
What you need to bring
- Shopify staff access with reports permission, plus read access to GA4, Klaviyo, and Meta Ads
- Product costs, even if they're in a supplier spreadsheet
- Your shipping and returns policy, and how discounts are applied
- The founder or marketing lead who makes budget calls
Five questions that set the price
- Besides Shopify, do you sell through wholesale, Amazon, or a subscription app?
- How many years of order history do you want analyzed?
- Where do your product costs live, and are they current?
- Which ad and email platforms are in scope?
- Do you need the views refreshed daily, or is weekly enough?
Price
- What moves it
- Sales channels, years of history, the state of your product cost data, and platforms in scope
- Payment terms
- Half at kickoff, half when your team has the finished views in hand
What if it isn't worth it?
Raquel fixes your number after she's seen your stack, before kickoff. If your GA4 is badly broken, the GA4 audit may be the cheaper first step.
Questions people ask before booking
We already pay for an attribution app. Why add this?
Attribution apps are good at modeling the path to a sale. They're weaker on margin, returns, and what a customer is worth a year later. This build ties everything to your actual orders. That also lets you check whether your attribution app's story holds up.
How is this different from the GA4 tracking audit?
The GA4 audit checks one thing: whether Google Analytics records your store correctly. Ecommerce analytics uses the whole stack to answer business questions about margin, channels, and repeat customers. If your GA4 is badly broken, the audit can be the cheaper first step.
Does Klaviyo's attributed revenue count?
It counts as a claim, not a fact. Klaviyo credits a sale to an email if the buyer opened or clicked within its attribution window. That holds even if they would have bought anyway. The build shows that claim next to the orders, and you decide how much weight to give it.
What's Raquel's ecommerce background?
As a digital analytics manager at an eCommerce company, she worked on GA4 tracking, SQL in BigQuery, and Tableau dashboards for executives. She also runs her own print-on-demand online shop. She sees the same ad, product, and margin questions from the owner's side.