Industry · Online retail
ERP & E-Commerce for online retail
Orders from three channels, real-time inventory, returns without drama, DATEV without Excel — online retail needs an architecture that doesn't collapse on its first Black Friday.
Pain Points
What companies in this industry struggle with.
- Multi-channel chaos: shop, Amazon, eBay, B2B portal — every channel its own data state, nobody knows where the real inventory sits.
- 30–50 % return rate in fashion/furniture — without an end-to-end workflow between shop, ERP, and warehouse, every return becomes an Excel exercise.
- DATEV handover at 2,000+ documents per month: doing this manually loses one to two days at month-end — and produces errors the tax advisor books back.
- Seasonal peaks (Black Friday, Christmas, seasonal sales) triple volume — but not the support team. AI pre-qualification is mandatory, not bonus.
- Optimizing shipping costs and carrier mix: DHL for parcels, DPD for bulk, GLS for B2B. Deciding manually is a time and margin killer.
Tech Stack
Our typical tech stack.
weclapp ERP
Master system for articles, inventory, conditions, B2B/B2C differentiation, DATEV integration
Shopify or Shopware
Storefront with live inventory from weclapp, theme customization, marketing pixels, A/B testing
Marketplace connectors
Amazon, eBay, Kaufland, OTTO — master data and inventory synced from weclapp, orders flow back
Multi-carrier shipping
DHL · DPD · GLS · UPS — automatic carrier selection by weight, size, region, label generation automated
Helpdesk + AI pre-qualification
Standard tickets are auto-classified, replies pre-drafted — team scales without growth
DATEV interface
Documents handed over daily or live, OPOS lists automatic, tax advisor pulls directly
Outcomes
What it gets you in the end.
- 01 Live inventory identical across shop, marketplace, and ERP — overselling impossible, hourly sync automatic.
- 02 Return workflow end-to-end: shop request → label automatic → goods receipt → DATEV credit note — no manual touching.
- 03 Shipping costs reduced by 8–15 % through automatic carrier selection — at 100,000 shipments/year that quickly hits six figures.
- 04 Helpdesk response times during Black Friday week down 60 % — at the same team size.
- 05 DATEV handover under one hour at month-end — instead of two days of Excel and reversed bookings.
Deep dive
Industry in detail.
What makes online retail special as an IT discipline
Online retail is the industry with the highest data and transaction pressure in mid-market. Three peculiarities make the IT architecture especially demanding: first, multi-channel reality — running only your own shop is the exception today. Marketplaces (Amazon, eBay, Kaufland, OTTO) and B2B wholesale portals run in parallel. Each channel wants master data, inventory, and order routing — usually with different requirements.
Second, volume scaling with hard peaks — Black Friday, Christmas, seasonal sales triple daily revenue. ERP systems, the shop, the helpdesk team need to take it. Hiring staff for four weeks isn’t economical; automation (AI pre-qualification, self-service, automatic shipping) isn’t bonus, it’s mandatory.
Third, return reality — in fashion or furniture, 30–50 % return rates. Without an end-to-end workflow between shop (return portal), warehouse (goods receipt, inspection), and accounting (credit note, DATEV), every return becomes an Excel exercise. Margin eats itself from behind when the process jams.
Our typical setup
For online retailers we build a stack of six components: weclapp as ERP backbone (master data, inventory, conditions, DATEV), Shopify or Shopware as the storefront with live inventory and marketing pixels, marketplace connectors for Amazon/eBay/Kaufland/OTTO, a multi-carrier shipping solution (DHL/DPD/GLS/UPS) with automatic carrier selection, a helpdesk with AI pre-qualification for scaling support volume, and the DATEV interface for clean handovers to accounting.
The architecture follows one principle: ERP is master, channels are slaves. Master data, prices, and inventory exist exactly once in weclapp and are pushed to all channels. Orders flow back with channel tag into the order stream — so you can later evaluate B2C, B2B, Amazon, eBay etc. separately without constant re-merging.
When this fits
- You run an online shop with annual revenue from ~€500k — below that, the architecture depth usually doesn’t pay off.
- You sell through two or more channels (shop + marketplace, shop + B2B portal, etc.).
- Seasonal peaks or growth are foreseeable — you want scaling without doubling the team.
- Returns, DATEV, or multi-carrier shipping are manual bottlenecks today.
- You have between 5 and 50 employees, with accounting, warehouse, marketing, and customer service as separate functions.
If that fits — write to us. 30 minutes initial call and we know whether we’re the right partner.
FAQ
FAQs from this industry.
Which ERP fits online retail best? +
weclapp is the right choice 70 % of the time: native DATEV interface, B2B conditions, multi-warehouse logic, German hosting, strong Shopify/Shopware integration. Odoo fits when you need very specific workflows (e.g., own B2B portal, complex configure-to-order with configurator) or open-source sovereignty matters. Zoho One fits when marketing/CRM are equally weighted with e-commerce volume. Full comparison: /en/blog/weclapp-vs-odoo-vs-zoho.
How do you connect shop, marketplace, and ERP? +
Pattern: ERP is master of master data (articles, prices, inventory), all channels are slaves. Shopify or Shopware gets inventory every 5–15 minutes via API, marketplaces every 10–30 minutes depending on connector. Orders flow into the ERP order stream with channel tag (so you can later evaluate B2B/B2C/Amazon/etc. separately). For high-risk items (low stock, high margin) we add real-time webhooks so a shop order immediately reduces marketplace stock.
How do you handle high order volume without growing the team? +
Three levers: first, AI pre-qualification in the helpdesk — incoming tickets are auto-classified (delivery status, return, product question, complaint), replies pre-drafted, the team only confirms. Second, automated shipping pipeline — DHL/DPD label automatic, tracking mail automatic, multi-order consolidation per customer automatic. Third, self-service for standard cases — track page with status, return portal with label generation, FAQ bot. With this, Black Friday weeks at 3× volume are doable without doubling the team.
What does the implementation timeline look like? +
For an online retailer with shop + 1–2 marketplaces + B2B business we plan 14–22 weeks from kick-off to go-live. Discovery 2–3 weeks, weclapp setup + master data migration 4–6 weeks, shop integration 3–4 weeks, marketplace connectors 2–3 weeks, helpdesk + AI 2–3 weeks, training + hypercare 4 weeks. Existing ERP predecessor with clean data goes faster, Excel chaos with 50k+ articles takes longer. We deliberately do NOT plan go-live right before Black Friday — Q1 or Q3, with hypercare into peak season.
Which Mate iT cases run productively in online retail? +
Three relevant cases: I-CLIP (premium consumer goods, weclapp + Shopify + grey-market database, international direct sales), Haselherz (D2C food, weclapp + Shopify fulfillment automation), Reifen24 (e-commerce tire trade, weclapp + Shopify + AI helpdesk, seasonal scaling). All three at /en/cases with architecture description and CEO quotes.