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AI Automation for Ecommerce Brands

Ecommerce at $3M to $10M has a specific shape of pain: support volume that scales exactly with revenue, returns that eat margin invisibly, and supplier communication that lands entirely on the founder.

Growth makes all three worse, which is why the busiest quarter is often the least profitable one.

Where the money goes

OperationWhat it costs before it is replaced
Customer supportHeadcount that has to grow in step with order volume
Returns and exceptionsCase-by-case decisions made inconsistently under time pressure
Supplier and 3PL communicationChasing, confirming, and reconciling, usually by the founder
Product data and listingsCopy, attributes, and translations re-done per channel
Post-purchase follow-upGeneric sequences that ignore what the customer actually bought

What changed where we have done this

MeasureBeforeAfter
Support headcountGrows in step with order volumeFlat through the next thousand orders
First reply timeHoursMinutes
Returns decisionsThree agents, three answersOne rule applied the same way, exceptions escalated
Founder hours on suppliersSeveral a weekExceptions only

These are the numbers from the specific builds linked at the foot of this page, not an average across a portfolio. Yours will not be identical, which is what the assessment is for.

Every additional thousand orders brings a predictable number of where is my order, can I change the size, and it arrived damaged. Most brands answer that by adding people, so support cost tracks revenue instead of falling per order.

Trained on your real replies and your actual policy, a support system carries the repetitive load and escalates what is genuinely unusual. The measure of it working is whether the next thousand orders need another hire.

Returns are decided inconsistently, and that is the cost

Your policy says one thing. Under pressure at four in the afternoon, three different agents make three different calls. The inconsistency costs margin and it also teaches customers to push.

Encoding how you actually want these decided, and applying it the same way every time, is worth more than the labour saved. Exceptions still go to a person, on purpose.

The founder is the supplier communication layer

Chasing a shipment, confirming a spec change, reconciling what arrived against what was ordered. At this size that almost always sits with the founder, and it is the least leveraged hour in the company.

It is also unusually replaceable, because it is bounded, repetitive, and evidenced in years of email.

What an assessment looks at here

  • Support contacts per hundred orders, and their composition
  • How many contacts are answerable from data you already hold
  • Return rate by reason, and how consistently the policy is applied
  • Hours per week the founder spends on supplier and logistics threads
  • Which post-purchase touches are generic and could be specific

Ecommerce is the one industry where the fastest win is almost always support. It is high volume, well evidenced, and it shows up in contacts per order within a fortnight.

Questions from this industry

We use a helpdesk with an AI feature already. Why is this different?

Bundled features are trained on your help centre. What we build is trained on the replies your team actually sent, which is where the difference between published policy and real practice lives.

What about peak season?

Peak is the argument for it. A system that carries the repetitive half of contacts is the difference between seasonal hiring and not.

Will it refund people it should not?

Refund authority is a rule you set, with a value ceiling above which a human decides. That is part of the build, not an afterthought.

What this looked like when we did it

Comparisons buyers in this industry run

Find out what your most expensive operation is

The assessment covers the whole company: how you get customers, how you deliver, and how the place runs. You get it in writing, and you can build from it with or without us.

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