Shopware Is a Good Shop System — but a Limited Analytics Tool
TL;DR:
- Shopware Analytics shows revenue and orders — but not return rate per product, true ROAS on margin, or assortment gaps.
- These five missing analyses typically cost Shopware merchants four- to six-figure amounts per year they never see.
- A Shopware analytics alternative like oneAgent delivers them via chat — no data-warehouse project, with a Live URL Reader for instant market comparisons.
Shopware does many things right. Fast checkout, flexible product variants, stable extensions. As a shop system for European mid-market merchants, it has earned its place.
But as a Shopware analytics alternative, the built-in reporting only covers the basics. You notice that the moment you try to understand which products actually make money and which ones only produce inventory, returns, and customer-service tickets.
This article is not Shopware-bashing. We show what the built-in reporting does well, where it hits hard limits, and how Shopware merchants today run analyses that used to require a data-warehouse project.
What Shopware Analytics Does Well
Credit where credit is due. Shopware delivers solid baseline data out of the box:
- Revenue trends by time period, category, and payment method
- Checkout funnel conversion rate
- Average order value
- Top products by revenue
- Customer and order counts over time
For the daily overview, the weekly team check-in, or a quick look at the revenue curve, that is enough. A merchant who arrives at the office and wants to know "how did yesterday go" is well served by the Shopware dashboard.
For real business decisions, it is not enough.
Which Five Analyses Are Actually Missing?
Across our Shopware customer projects, we see the same pattern. Most merchants do not have a data problem. They have an access problem. The database knows everything; the UI shows a small slice.
These five analyses are not niche. They are the questions every merchant with more than 500 orders per month should be able to answer — and that simply do not appear in the Shopware dashboard.
1. What is the return rate per product and variant?
Illustrative example from typical Shopware setups: a fashion retailer with roughly 12,000 orders per year stocked an "Urban Parka." On the Shopware dashboard the product looked great — 340 units sold in one quarter, solid contribution margin on paper.
What the dashboard did not show: the return rate was 38 percent. In practice, 129 parkas came back to the warehouse. At a purchase price of EUR 89 and roughly EUR 8 per return handling, that produces EUR 1,032 in direct return costs plus around EUR 11,400 in write-downs and unsellable inventory — a combined hidden cost of roughly EUR 12,400 from this single article.
The Shopware built-in reporting shows return rate — but aggregated across the whole shop. Not broken down by product, size, or variant. That is precisely where the decision sits: which variants do I cut, which product do I need in different sizes, how deep are the return clusters per supplier.
If you want to go deeper, the article Returns Analysis and Margin explores how merchants identify return clusters and calculate margins cleanly.
2. What is your true ROAS — on margin, not gross revenue?
Google and Meta report ROAS based on gross revenue. That is advertising for their platforms, not a decision basis for you.
True ROAS subtracts purchase costs, average return rate, shipping, and payment fees before weighing ad spend. The result often differs dramatically:
- Google Ads reports ROAS 4.2 on gross revenue
- Subtract 32 percent cost of goods, 18 percent returns, 6 percent shipping, and the true ROAS on margin drops to around 1.8
- At EUR 20,000 monthly ad spend, that is the difference between profitable and loss-making
The Shopware dashboard cannot perform this calculation. It requires combining shop, ads, and inventory data in one view.
3. Where are the assortment gaps vs. the market?
What is selling well on Amazon in your category right now that you do not offer? What are customers searching for that you have no answer for?
You can answer this today without commissioning market research — we show how in the practical example below. Shopware itself only knows what you sell. The outside-in view is part of assortment planning, and it is where most dashboards stop.
4. Who are your truly valuable customers (RFM segmentation)?
Not every customer is worth the same. RFM analysis (Recency, Frequency, Monetary) splits your customer base into segments: who bought last, how often, and for how much?
The e-commerce rule of thumb: 15 to 20 percent of customers generate 60 to 70 percent of revenue. In our mid-market implementations we regularly see even more concentrated patterns. One pet-supplies merchant discovered after an RFM analysis that just 7 percent of customers (847 of 12,000 active accounts) accounted for 64 percent of yearly revenue. The obvious move: a dedicated loyalty flow for those 847 — instead of discount blasts to the whole list.
Illustrative from typical Shopware setups: once you know who your top 7 percent are, you can invest in retention precisely — instead of pouring the entire marketing budget into acquisition.
5. What does seasonality look like for inventory planning?
The winter peak in apparel is over in October, not in December. Christmas business for many categories starts in early November. Whoever reorders in late October gets stock when the peak is already running — or not at all.
Seasonality patterns from your own historical data are the most reliable planning basis you have. They sit in your Shopware system. You just need to be able to analyse them — by category, colour, size, and supplier lead time.
Why the Shopware Dashboard Stops Here
The built-in reporting is deliberately lean. Shopware is a shop system, not an analytics platform. The database knows everything — order positions, returns, customer data, categories, variants. But the UI shows only a small slice. That applies to both Shopware 5 and Shopware 6, although the database structures differ between the two versions (see the official Shopware documentation for details).
The alternatives merchants typically try:
| Approach | Effort | Repeatable | Fit for Shopware merchants? |
|---|---|---|---|
| Excel export | High | No | Only for one-off questions |
| Looker Studio | Medium (SQL) | Yes | Only with data know-how |
| Power BI | High (IT/consultant) | Yes | Often overkill |
| Dedicated e-commerce BI | Low | Yes | Expensive, often narrow |
| NL-BI chat (e.g. oneAgent) | Low | Yes | Mid-market fit |
A deeper comparison is in oneAgent vs Excel and ChatGPT and oneAgent vs Power BI Copilot.
The fifth option — querying Shopware data via chat and combining it with external sources — has only emerged over the past two years. That is where oneAgent fits in.
Practical Example: URL in the Chat, Instant Market Comparison
One of the most useful features in oneAgent is the Live URL Reader. Here is how it works:
You ask oneAgent: "Which products in my 'Outdoor Jackets' category are currently best-sellers on Amazon Germany?"
Then you paste the URL of an Amazon bestseller page into the chat — a publicly accessible category page. oneAgent reads the page in real time, extracts the product list, and compares it against your Shopware inventory data.
The result: a side-by-side view of which of Amazon's top 20 you stock, which you do not, and which of yours barely appear there. Assortment gaps become visible — with no market research, no CSV export, no hours in Excel.
No connector setup, no API onboarding, no waiting period. Paste URL, ask question, read result. The same works with competitor shops, price-comparison pages, or category-specific marketplace rankings.
How to Connect Shopware to oneAgent
oneAgent uses a live connection directly against your Shopware database. No ETL process to build yourself, no data-modelling project, no multi-month BI implementation.
What you need:
- Shopware 5 or 6 (both supported)
- Read-only access to the database
- Roughly 30 minutes one-time setup with our team
What happens after:
- All order, product, customer, and return data is queryable via chat
- You ask in natural language instead of writing SQL
- Results appear as tables or charts automatically
- Dashboards you need daily can be pinned and stay live
If you have additional data sources — Google or Meta ads, an inventory system, a returns tool — they can be combined via the dashboard workflow.
A broader comparison of e-commerce analytics approaches is in Shopware Analytics Alternative.
How oneAgent Fits Shopware Data Analysis by Design
- Deterministic: every question is translated into a concrete database query. An automatic verification layer checks the answer against your actual data — no hallucinated numbers.
- Live URL Reader: market comparisons, competitor checks, and external sources directly in the chat — no integration.
- Hosted in Frankfurt, GDPR compliant: on-premise option available.
- No data copy: with the live connection, your data stays in your database.
FAQ
Do I need a database administrator to connect oneAgent to Shopware?
No. You need someone who can create a read-only database user once — in most Shopware setups the hoster or the Shopware agency partner handles this in a few minutes. Our team guides the one-time setup.
Is my Shopware data stored by oneAgent?
No. With the live connection method, no data is copied. The query runs directly against your database, and the result is shown in your browser. No data copy on our servers, no persistent cache. oneAgent is fully GDPR compliant and hosted in Frankfurt.
Does this work with Shopware 5, or only Shopware 6?
Both versions are supported. Shopware 5 and Shopware 6 have different database structures, but oneAgent knows both schemas. The matching schema template is loaded during setup.
Can I connect oneAgent to other systems too — for example my ERP or returns tool?
Yes. oneAgent supports 550 data-source connectors, including SAP, Sage, Salesforce, Google Analytics, and many more. Combining Shopware with an inventory system or an ads account is possible through the dashboard workflow.
How is oneAgent different from a BI tool like Power BI or Tableau?
Classic BI tools require someone to build data models, dashboards, and reports. oneAgent takes natural-language questions, translates them into database queries, and returns the result in seconds. For shop operators this means no dependency on an IT or BI team.
What does it cost to get started?
The trial is free and includes prepared Shopware sample data so you can try the features end-to-end. Pricing for live connection and user licences is on our pricing page.
Takeaway: Shopware as a Data Source, Not Just a Shop System
Shopware collects more data every day than most merchants ever analyse. Order positions, return reasons, customer segments, seasonality patterns — it all sits in the database. What is missing is access without SQL skills and without Excel marathons.
The next step is not "a better Shopware dashboard." The next step is being able to ask questions. Live. In the language you think in.
Try oneAgent free — ready to explore with real Shopware sample data.
Nothing to install, nothing to connect, no credit card. The demo environment runs on anonymised Shopware order data, so you can try the return analysis, the ROAS check, or the market comparison straight away.
If you would rather talk to us first before connecting your own database: Book a demo.