01
Support volume scales with orders
Every 10% growth in orders brings roughly 10% more “where is my order”. Headcount is the only lever most teams have.
Ecommerce & Retail
Commerce that keeps up with your orders, not your headcount.
Technology, Software and AI Automation for Ecommerce and Retail
Retail support volume is predictable, seasonal and dominated by a handful of intents. The constraint is not whether AI can answer — it is whether it can see the order.
- 09:10Overnight orders sync to the ERPOne SKU mapping fails and 40 orders sit unallocated until someone notices.
- 11:30A campaign email landsTraffic triples. The checkout slows and cart abandonment climbs quietly.
- 14:00"Where is my order?" peaksAgents open the store, ERP and carrier portal for each ticket.
- 17:45A courier misses the collectionNobody knows until the customers who were promised next-day delivery start writing in.
- 22:00Refund requests pile upThey wait for the morning shift, and some customers raise chargebacks instead.
01Strategize
Platform decisions, integration architecture between store, ERP, warehouse and payments, and whether a replatform is genuinely needed or the current stack can be made to behave.
Explore 02BuildCustom commerce where the operation is the hard part: collection windows, stock across locations, account pricing, fulfilment rules and the exceptions a standard cart never models.
Explore 03AutomateOrder status, returns, refunds, failed payments and post-purchase communication answered from live data instead of a help centre.
Explore 04RunManaged commerce: uptime through campaigns and peak season, integration monitoring, patching, and capacity planned before Black Friday rather than during it.
ExploreThe short answer
How does AI automation work in an ecommerce business?
In ecommerce, AI automation connects to the commerce platform, ERP, payment gateway and carrier so it can answer customer questions from live order data instead of a help centre, and watch order state so that stalled or at-risk orders are dealt with before the customer complains. The highest-return starting point is almost always the order-status intent, because it is the largest single share of contact volume and it is fully answerable from data the business already holds.
- Workflows mapped
- 6
- Tasks safe to automate
- 9
- Kept with people
- 6
- Systems we connect
- 12+
What we usually find
Six problems that show up in almost every ecommerce & retail business
02
Peak season breaks the model
Temporary staff are hired and trained just as volume and error rates are highest.
03
Answers live in four systems
Platform, ERP, payment gateway and carrier — agents alt-tab between them for a question with one right answer.
04
Problems surface as complaints
A stuck order is discovered when the customer emails, not when it stalled.
05
Returns eat margin and time
Eligibility gets decided inconsistently, and refunds get chased in three separate channels.
06
No view of contact drivers
Nobody can say which product, courier or page is generating the tickets.
Workflows
What the work looks like once it is automated
Pick a workflow to see each step. Every one reads from your real systems, and hands over to a person where the rules say it should.
Order status enquiry
- 1
Identify order
- 2
Fetch live state across platform, ERP and carrier
- 3
Answer with the real date
- 4
Schedule follow-up if the order is at risk.
Every step is logged, and anything outside policy goes to a person.
Return request
- 1
Check eligibility against policy and order state
- 2
Create the return
- 3
Issue the label
- 4
Update the customer and the system.
Every step is logged, and anything outside policy goes to a person.
Refund status
- 1
Read the payment and settlement position
- 2
Explain accurately
- 3
Execute or route for approval based on your threshold.
Every step is logged, and anything outside policy goes to a person.
Stalled order sweep
- 1
Detect paid-but-not-progressing orders
- 2
Diagnose cause
- 3
Chase the missing input or escalate to fulfilment.
Every step is logged, and anything outside policy goes to a person.
Failed payment recovery
- 1
Detect failure
- 2
Contact the customer by message, then by call
- 3
Provide a secure completion path.
Every step is logged, and anything outside policy goes to a person.
Stock and alternatives
- 1
Answer availability from live inventory
- 2
Offer genuine alternatives
- 3
Capture demand for out-of-stock items.
Every step is logged, and anything outside policy goes to a person.
Reference architecture
How the pieces fit together
Automation is only as good as what it can see. This is the shape we build towards in ecommerce & retail: channels on top, your systems of record underneath, and people where judgement is needed.
Customer channelsWhere the enquiry starts.
- Website chat
- Phone
- Marketplace messages
Commerce truthWhat the AI must be able to read.
- Order management
- Inventory
- Payments
- Fulfilment / 3PL
- Carrier tracking
AutomationIntent, policy, action.
- Intent classifier
- Returns policy engine
- Refund thresholds
- Stalled-order detection
- Proactive comms
PeopleWhere humans take over.
- Helpdesk
- Approval queue
- Agent copilot
- Escalation rules
Where the line sits
What software handles, and what stays with your people
Handled automatically
- Order status and tracking
- Delivery estimate questions
- Return eligibility and label issuing
- Refund status explanations
- Stock and availability
- Address and detail changes before dispatch
- Post-purchase and delay notifications
- Failed payment recovery
- Ticket classification and routing
Always a person
- Refunds and goodwill above your approval threshold
- Complaints, damage and safety issues
- Any second contact about the same order
- High-value orders and flagged accounts
- Fraud and chargeback decisions
- Anything the policy does not cover
Advice before you spend
Three technology decisions ecommerce & retail businesses often get wrong
Replatform or fix the integrations?
Most retailers who want to replatform actually need their store, ERP and warehouse to agree on stock and order state. Fix that first; replatforming a broken data flow just moves the problem.
Headless or not?
Only when the storefront experience is a real competitive advantage and you have the team to run it. Otherwise a well-configured platform theme is faster and cheaper to own.
What to automate first?
Order status. It is the largest single share of contacts, fully answerable from data you hold, and easy to measure.
What to measure
Four numbers that tell you whether technology is helping. We take a baseline before any work starts.
Contacts per 100 orders
Shows whether support load is growing faster than the business.
Order-to-dispatch time
Where most "where is my order" contacts are really created.
First-contact resolution
A second contact about the same order costs twice and annoys the customer twice.
Checkout conversion at peak
Tells you whether the platform holds up when it matters most.
Where it fits
Common starting points
Peak-season support
Absorb the predictable intents so the team handles genuine exceptions instead of drowning.
Click-and-collect deadlines
Where a missed collection window cancels the order and loses the revenue.
Multi-store and multi-region
One automation layer across stores with different policies, languages and currencies.
Marketplace order support
Consistent answers across your own site and marketplace channels.
Related work
Systems we have built
Case study
Omnichannel E-commerce for an Airport Travel-Retail Leader
A full pre-order and click-and-collect e-commerce platform for one of India's largest airport duty-free operations - thousands of SKUs, high...
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Read the case study Case studyRetail Digital Signage Network for a Supermarket Chain
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Read the case studyWe are on Magento 2 with a custom ERP integration. Can you work with that?
Yes. Large multi-store Magento 2 with custom APIs and ERP integration is directly in our experience — see the airport travel-retail case study. Magento’s API surface is usually sufficient without invasive changes to the store.
What share of our tickets could be automated?
We would rather measure than guess. Classifying one month of real tickets shows the intent mix and the ceiling before anything is built — and it sometimes shows the answer is process change rather than AI.
Will this replace our support team?
It changes what they do. The repetitive intents stop reaching them; complaints, exceptions, high-value customers and judgement calls still do. Most teams we work with redeploy rather than reduce, because the exception work was previously being done badly under time pressure.
What about peak season specifically?
Peak is the strongest case, because the automated share does not degrade under volume. It is also the worst time to deploy something new — build and prove it in a quiet period.
Tell us what is slowing your operation down.
One process, one system or one decision. An engineer who understands ecommerce & retail replies within one working day with how we would approach it, and whether it needs building at all.