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Simple to set up. Easy to use. Powerful integrations.
Get startedAsk any e-commerce support manager what their agents spend most of their time on and the answer is almost always the same: order status. Where’s my order? When will it arrive? Why hasn't my tracking updated? These aren’t complex questions. They aren’t questions that require empathy, product knowledge, or any of the capabilities that make a trained support agent genuinely valuable.
They’re structured, repetitive, and entirely predictable. And in most operations, they’re still being answered manually by agents who could be handling the calls that actually require them.
The SLA is a contract, not a target
For most e-commerce operations, an abandon rate below 5% and an average speed of answer below 40 seconds aren’t internal performance aspirations; they’re contractual commitments with commercial consequences. Missing them in a quiet period is a problem. Missing them during Black Friday, when inbound volume runs at three to five times the baseline, is a different order of problem entirely.
The average contact centre loses 27% of its inbound calls to abandonment. Every one of those abandoned calls is either a customer who calls back and joins the queue again, or a customer who doesn't (over half). The ones who don't represent a direct revenue and retention cost, and US businesses lose as much as $3 trillion annually from poor customer service.
The seasonal staffing response to peak volume is expensive, slow, and inconsistent. Temporary agents take weeks to onboard. Their quality varies. And the brands that have invested most heavily in tone of voice find that inconsistency most damaging at precisely the moment when customer volumes—and therefore brand exposure—are highest.
WISMO is the entry point, not the ceiling
When AI Virtual Agent is connected to Shopify via Automated Tasks, the ‘Where is my order?’ (WISMO) interaction is resolved without a human agent. The customer calls, AI Virtual Agent verifies their identity using order number and email address, pulls live order status from Shopify mid-call, and delivers the complete answer (status, carrier, tracking reference, estimated arrival) in under 60 seconds. No queue. No hold time. No abandoned call.
For returns, the agent checks eligibility against the configured return policy, initiates the workflow for qualifying requests, and confirms next steps. Return rates reached 20.4% in 2024, up from 17.6% the previous year, making returns one of the fastest-growing cost centres in e-commerce. Standard return initiation follows the same structured, repeatable pattern as order status. It belongs in the same agent.
Damaged goods, missing items, fraud claims, and complex disputes route immediately to human agents with full call context already captured. The virtual agent doesn’t attempt to handle what it shouldn’t handle. Its scope is defined, and within that scope, it operates consistently at any volume.
The multilingual gap is a direct revenue leak
"Our operators only speak French. When a Spanish customer calls, they hang up."
Every call that ends because no one can speak the customer's language is a lost sale. Not a degraded experience; a lost transaction. Multilingual staffing at the level required for full shift coverage requires six or more FTEs per language. For mid-market operations, that isn’t a realistic investment. AI Virtual Agent supports multiple languages natively, without additional headcount, closing a gap that directly impacts revenue in any operation serving a multilingual customer base.
The "We've tried chatbots" objection
It comes up in almost every conversation about AI in e-commerce support. The previous investment in rule-based IVR or a scripted chatbot that frustrated customers, failed on anything outside its narrow script, and left a lasting association between "automated support" and "poor experience."
That association is understandable and worth addressing directly. Legacy IVR and rule-based systems respond to button presses and keyword matches. AI Virtual Agent, however, understands intent. It handles natural language, manages deviations from the expected path, and resolves the interaction rather than deflecting it. The distinction matters, and for buyers who have been burned before, demonstrating it rather than asserting it is what changes the conversation.
eCommerce: by the numbers
Cost per call in e-commerce support runs between $2.70 and $5.60. At the volumes most mid-market and enterprise operations handle—70 to 100 calls per day for smaller teams, 120,000 per year for enterprise—the cost of automating the tier-one layer isn’t a marginal efficiency gain, it’s a structural cost reduction. 80% of customers say they’re willing to pay more for a better support experience. The same automation that reduces cost also creates the conditions for that premium.
It’s time to let AI do the heavy lifting on day-to-day enquiries, and free your team to take care of customer calls that really need them.
Published on May 4, 2026.
