ConvoHut
Retention use case

The order is not the end of the conversation.

The period between paying and receiving is where anxiety lives, where most support tickets are created, and where the second purchase is either set up or quietly lost.

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At a glance

TriggerOrder completed
GoalReduce uncertainty, create the next action
Primary KPISupport deflection and repeat action
Messages3–4 across the delivery window
Estimated setup timeUnder 20 minutes

What is post-purchase automation?

Post-purchase automation handles everything after checkout: order confirmation, delivery updates, usage guidance and the review request. On WhatsApp it runs as one continuous thread, so a customer asking 'where is my order' gets an answer instead of raising a ticket.

Key takeaways

  • Most post-purchase support tickets are the same three questions. Answer them before they are asked.
  • Ask for the review after satisfaction is confirmed, not on a fixed timer.
  • Route unhappy customers to a person immediately — never to a review link.
  • This journey is where the second purchase begins.

Why this leaks revenue today

01

'Where is my order' dominates support

The single highest-volume support question in ecommerce is one the system already knows the answer to.

02

Review requests arrive blind

A timed review request reaches delighted and disappointed customers identically, and surfaces the disappointed ones publicly.

03

The relationship ends at delivery

No usage guidance, no check-in, no natural path to the next purchase. The customer has to remember you unprompted.

The signal ConvoHut acts on

The journey only starts when all of these are true. Getting the entry conditions right matters more than the message.

Order placedOrder shippedDeliveredDelivery window passed with no scan

What has to be connected

Order recordItems, value, delivery method and tracking status
Fulfilment eventsShipped and delivered timestamps from your carrier or platform
Product contentSetup guidance, care instructions and FAQs for the item bought
Satisfaction signalThe customer's own answer, captured before any review request

The journey

Built once, then it runs unattended. Every branch has a defined outcome, and the journey stops the moment the goal is met.

Trigger

Order placed

Message

Send confirmation

Delay

Wait for delivery event

Conversation

Check in on satisfaction

Then it branches on what the customer does

Happy

Send the review request with a direct link

Problem

Escalate to a human with the full order context

No reply

Send usage guidance only, no review request

Goal: Issue resolved, review left, or next purchase prompted

A journey without a stop condition is a journey that gets your number blocked.

The messages, and why each one exists

Starting points, not scripts. You rewrite them in your own voice and approve every message before it goes live.

On order

Sets the expectation that this thread is where updates and questions live. That is what deflects tickets.

Order confirmed. I'll message you here when it ships — and you can ask me anything about it in this thread.

On delivery

Pre-empts the most common post-delivery question before it becomes a support ticket.

Your {product} was delivered today. Anything you need to know about setting it up?

Delivery + 3 days

One open question. The answer decides whether the next message is a review link or a human.

How's the {product} working out?

On positive reply

Asks only the customers who have already told you they are happy.

Glad to hear it. If you have a minute, a short review really helps: {link}

What it looks like to the customer

This is the part a broadcast tool cannot do. The customer replies, the question gets answered from real data, and the journey continues — in one thread.

If the AI reaches the edge of what it has been approved to answer, it escalates to your team with the full history attached. The customer sees one continuous conversation.

Your espresso machine was delivered today. Anything you need to know about setting it up?
How long do I run the first flush for?
Two full tanks through without coffee, then you're ready. Takes about ten minutes.
Perfect thanks
Any time. I'll check in in a few days once you've pulled a few shots.

Illustrative conversation. Not a customer transcript.

What to measure

Pick one primary metric before launch and agree how it is calculated. Everything else is secondary.

Support deflection

Post-purchase questions answered in-thread rather than becoming tickets.

Review completion rate

Reviews left as a share of customers who confirmed they were happy.

Issue recovery rate

Problems caught and resolved before they became a public review.

Repeat purchase rate

Customers from this journey who order again inside the agreed window.

How we keep this honest. The attribution window is agreed before launch. Direct and influenced conversions are reported separately. Where volume allows we hold out a control group. We do not claim every order that happens after a message.

Set it up

  1. 1

    1. Connect order and fulfilment events

    The journey needs shipped and delivered events, not just the order.

  2. 2

    2. Load your product guidance

    Give the AI the setup and care information for your top-selling items.

  3. 3

    3. Add the satisfaction check

    One question, three days after delivery. This gates everything downstream.

  4. 4

    4. Set the escalation path

    Define who receives an unhappy customer and how fast.

  5. 5

    5. Connect the review destination

    Point the review link where it actually helps you, and only to happy customers.

Then tune it

Move the satisfaction check, not the review request

If review rates are low, the check-in usually landed before the customer had used the product.

Add the top three product questions

Look at your support inbox. The three questions you answer most belong in the delivery message.

Treat complaints as the win

A journey that surfaces a problem privately just prevented a public one-star review.

Questions this raises

Does this replace my transactional emails?

It runs alongside them. Transactional email remains the record; WhatsApp is where the customer asks the follow-up question and actually gets a reply.

When should I ask for a review?

After the customer has confirmed they are happy, not on a fixed timer. Asking blind is how you collect negative reviews you could have resolved privately.

What if the delivery goes wrong?

The journey branches to a human with the order context attached. Delivery problems are the moment a customer decides whether to buy from you again.

Will customers mind being messaged after they have already paid?

Post-purchase is the most welcome messaging window there is, provided the messages are useful. Order updates and setup help are wanted; upsells too early are not.

Can I add a cross-sell to this journey?

Yes, but not before the product has been used. Recommending an accessory on the day of delivery reads as a sales push; recommending it a fortnight in reads as helpful.

How does this reduce support cost?

The high-volume questions are answered in the thread, from real order data, without a person. Measure it as tickets avoided per hundred orders.

Related use cases

Free download

The Post-purchase Playbook, as a PDF.

Everything on this page in a document you can send to your team or your client: entry conditions, journey logic, the messages with the reasoning behind each one, the metrics and the setup steps.

No email required. Take it and build the journey somewhere else if you want to — the logic is the useful part.

Post-purchase Playbook

PDF · 4 pages · Version 1.0

Download the playbook See all resources

Your customers are already showing intent.

Turn those moments into automated conversations that move customers toward conversion. We work with a small group of early access customers and set the first journey up with you.

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