WooCommerce and ecommerce analytics for agency client reporting

You manage the stores. You manage the sites. You report on them separately.

Here’s the Monday morning reality for an agency managing 15 e-commerce clients:

8:30am — Log into Shopify Admin for Client A. Export the monthly order summary. Note the revenue number. Log out. Log into Shopify Admin for Client B. Export. Log out. Client C. Export. You have 9 Shopify clients. This takes 30 minutes if nobody’s store has issues.

9:00am — Switch to WordPress. Open WooCommerce analytics for Client D. Export the order report. Client E has WooCommerce plus Gravity Forms — check both. Client F runs WooCommerce on a multisite install. Three separate analytics views. This takes 20 minutes.

9:20am — Open GitHub. Client A’s Shopify theme had a checkout update this month. Pull up the commit history. Client D’s WooCommerce site had a plugin conflict that required an emergency deploy. Find the PR. This takes 15 minutes.

9:35am — Check Stripe for the clients with subscription billing alongside their stores. Cross-reference subscription revenue with e-commerce revenue. Note discrepancies for the report.

9:50am — Start assembling client decks. One for each e-commerce client. Copy revenue data from one tool, deploy data from another, form data from a third. You haven’t gotten to the non-commerce clients yet.

That’s 80 minutes before the first client call — just on data assembly. And you’re doing this weekly or monthly for 15+ clients.

The problem isn’t the stores. It’s the context around them.

WooCommerce Analytics tells you Client D processed 234 orders for $47,800 this month. That’s useful.

What it can’t tell you:

• That your developer shipped a checkout optimization on March 3rd and conversion rate improved 12% afterward
• That the contact form on the marketing site captured 89 demo requests this month — up 30% from the CRO landing page your team built
• That Stripe processed $4,200 in subscription billing separately from the store revenue
• That uptime was 99.99% despite a hosting migration mid-month
• That a theme update on March 15th briefly broke mobile checkout until your team caught it and rolled back within 2 hours

Each of those data points lives in a different tool. WooCommerce Analytics, GitHub, WordPress, Stripe, Oh Dear. Five tools. Five logins. One story to assemble.

Burrow puts the story together for you.

Commerce signals in context

In Burrow, a client’s e-commerce data isn’t isolated in a store admin panel. It’s one signal category among many in the project timeline:

Client D — March 2026 Operations Summary

Commerce: 234 WooCommerce orders ($47,800). Average order value: $204. Checkout health: stable. Mobile conversion improved 12% after v2.3 checkout optimization (shipped March 3).

Engineering: 5 releases shipped. Notable: v2.3 checkout optimization, v2.4 product page redesign, v2.4.1 hotfix for mobile checkout regression (detected and resolved March 15, 2-hour impact window).

Forms: 89 demo requests via marketing site (up 30% from February). 142 newsletter signups. Contact form volume stable.

Billing: $4,200 in Stripe subscription revenue cleared. All renewals successful.

Uptime: 99.99%. Hosting migration completed March 8 — zero downtime.

That digest wasn’t manually assembled from 5 tools. It compiled itself from events flowing through Burrow from WooCommerce, WordPress, GitHub, Stripe, and Oh Dear.

Behind it sits the Ecommerce channel itself. Top Stores ranks every store you manage by revenue or orders. The per-store drill-down shows customer economics — new versus returning buyers, repeat rate, average customer lifetime value — plus best sellers by revenue and the highest-value abandoned carts with how long they’ve been idle. Recoverable revenue, itemized, for the team to chase.

Three scenarios where context changes everything

Scenario 1: The checkout regression nobody caught

Without Burrow: Wednesday — Developer pushes a WooCommerce theme update. Thursday — The client checks WooCommerce Analytics and sees a 35% drop in checkout completions. Friday — They email your agency asking what happened. The developer investigates, finds broken shipping calculator on mobile, fixes it. Three days of reduced conversions. The client is frustrated.

With Burrow: Wednesday 2pm — deploy.succeeded event. 2:30pm — WooCommerce checkout error signals spike in the same project timeline. Scout flags the anomaly. Developer sees the correlation between the deploy and the checkout drop immediately. Rollback deployed by 3:15pm. Impact: 75 minutes, not 3 days. Thursday’s client call: “We caught a checkout issue within an hour of deploying and rolled it back. Here’s the timeline.”

Scenario 2: The revenue story that sells the retainer

Without Burrow: Quarterly review. The client asks what they’re getting for $8K/month. Your AM opens the store analytics and says “revenue is up 18%.” The client says “that’s the market. What did you do?” The AM scrambles to pull GitHub data, form conversion numbers, and uptime stats from separate tools. The meeting runs 30 minutes over.

With Burrow: Quarterly review. The AM pulls up the Burrow project. The Ecommerce channel’s Written Summary has already drafted the recap in plain English from the quarter’s events; the AM adds the narrative: “Revenue is up 18%. Here’s why: we shipped 14 releases including the checkout optimization that improved mobile conversion by 12%. Form conversions are up 30% from the CRO landing page we built in February. Uptime was 99.98% across the quarter. One incident — 2-hour checkout regression — detected and resolved same day.” Every claim has a timestamp and an event trail. The client renews.

Scenario 3: The WooCommerce-Shopify hybrid

Without Burrow: Client runs WooCommerce for their primary store and Shopify for a pop-up brand. Different admin panels. Different analytics. Different checkout architectures. Your developer checks two dashboards. Your AM assembles two data sets. The monthly report takes twice as long because every metric needs “Shopify:” and “Woo:” prefixes.

With Burrow: The WooCommerce orders flow into the project today through the WordPress plugin. Once the Shopify integration ships, the pop-up brand’s orders join the same stream and the automated digest combines them: “Total commerce: 312 orders ($62,400) — 234 via primary store (WooCommerce), 78 via pop-up brand (Shopify). Both checkout flows healthy.” One project. One report. One portal.

Why merchant-facing tools don’t solve the agency problem

Shopify Analytics / WooCommerce Analytics: Built for store owners managing their own business. Shows products, orders, customers, revenue. Cannot show GitHub deploys, form health, CMS activity, uptime, or billing from tools outside the store.

Kleio ($29/mo) / Triple Whale ($219-$5,099/mo): Shopify profit analytics — P&L, LTV, cohort analysis, ad attribution. Excellent for the merchant asking “am I profitable?” Cannot help the agency asking “what happened across this client’s full stack this month?”

Metorik: WooCommerce reporting SaaS — order analytics, customer segments, email automation. Similar gap: merchant-focused, single-store, no cross-stack context.

These tools belong inside the store. Burrow belongs across the retainer. The agency managing commerce clients might use Metorik for store analytics inside each WooCommerce store and Burrow for the operational layer that unifies commerce signals with everything else.

Getting started with e-commerce clients

Start with your highest-value e-commerce retainer:

1. Install the Burrow WordPress plugin (captures WooCommerce events automatically) or the Craft CMS plugin for Craft Commerce stores
2. Connect GitHub for deploy tracking
3. Connect Stripe for billing signals

The first unified timeline appears within minutes. Commerce events alongside deploys alongside billing — the cross-stack narrative that manual reporting could never assemble efficiently.

Shopify integration | WooCommerce integration | Client reporting use case | Client portals