★★★★★
The Checkout Loom team were easy to work with and brilliant at the work itself. I highly recommend them to anyone who needs dependable automation.
IveraAutomation client
Verified
Customer support and order care automation
Customer support and order care automation for online stores that answers order and returns questions in seconds
Customer support and order care automation for online stores starts from a simple observation, which is that roughly one ticket in five in published helpdesk data is a customer asking where an order is, and the answer already sits in your store and your carrier tracking. We connect chat, email and WhatsApp to live order, return and policy data, let the system answer and act within limits you set, and pass every sensitive or upset conversation to your team with the full history attached.
- Fixed price from $3,190, paid once
- Answers come from live order data, never guesses
- Every sensitive case reaches a person with context
- Platforms supportedShopify, Shopify Plus and WooCommerce, with chat, email and WhatsApp connected to the same order data.
- Typical storeStores handling a hundred to ten thousand support conversations a month with a clear returns policy and tracked shipments.
- Help desksGorgias, Zendesk, Help Scout, Freshdesk or a shared inbox, connected so handoffs arrive with the whole conversation.
- Stores coveredOne store per plan, with several storefronts, brands or regions available as priced options.
- ChannelsWebsite chat, email, WhatsApp where customers have opted in, and social inboxes through your help desk.
- Live inThree to five weeks for a pair of services and up to ten weeks for a full support system built in stages.
The costly disconnect
Why support tickets pile up even though the answers are already in your store
A customer who asks about an order is asking for a fact that your store, your carrier and your returns policy already hold, yet most stores still pay a person to look it up, copy it and type it back, one ticket at a time.
Where-is-my-order questions
Order status questions make up roughly one in five tickets in the helpdesk data that has been published, and each one takes an agent a minute to look up and a customer hours to receive. Many owners only notice this problem when a customer complains, so catching it earlier is one of the quiet benefits of automation for online stores.
Returns handled by hand
A returns request that needs an order lookup, a policy check, a label and a refund decision passes through three tools and two people before the customer hears anything. Left alone, this problem repeats with every order, which is why automation for online stores is built to handle it by rule and not by memory.
Promises the policy does not make
Chat tools that answer from memory instead of from your written policy can promise refunds you do not offer, and a tribunal has held a business to what its chatbot said. It is easy to overlook until a busy week exposes it, and by then the cost to online stores is already counted in refunds, hours or lost sales in the automation work.
Context lost at handoff
When a conversation moves from chat to email to a person, the customer repeats the story, and the agent starts without the order, the history or the mood. The fix is not more effort but a better rule, and that is exactly what the automation build for online stores puts in place.
Separate inboxes for each channel
Chat, email, WhatsApp and social messages land in different places, so the same customer can be answered twice or not at all. Many owners only notice this problem when a customer complains, so catching it earlier is one of the quiet benefits of automation for online stores.
No view of why customers write
Without categories on every ticket, a late supplier or a confusing size chart never shows up as the cause of fifty tickets a week. Left alone, this problem repeats with every order, which is why automation for online stores is built to handle it by rule and not by memory.
- 1 in 5support tickets is an order status question in first-party helpdesk data, which is why order care is the first thing we automate.
- 24 hoursis the customer service window WhatsApp allows for free-form replies after a customer writes, so answers have to be quick as well as correct.
- 8 weeksis a typical timeline for a full support system built in stages, with order status first.
Sources: Gorgias and Yuma published ticket category data; Meta WhatsApp Business Platform documentation; Moffatt v Air Canada, 2024 BCCRT 149, on liability for chatbot statements.
What changes in your support operation once order care runs itself
Routine questions are answered from live data in seconds, and your team spends its time on the conversations that need judgement.
Support as it runs today
- An agent looks up each order by hand.
- Returns are decided and labelled one at a time.
- Chat, email and WhatsApp are separate inboxes.
- Handoffs lose the history.
- Nobody knows why customers write.
Support after the build
- Order questions are answered from live store and carrier data on every channel.
- Returns follow your written policy, with labels issued and refunds capped by limits you set.
- All channels feed one queue in your help desk.
- Handoffs carry the order, the conversation and a short summary.
- Every ticket is categorised, so repeated causes become visible.
What your inbox shows afterwards
- Fewer tickets reach your team.
- First replies arrive in seconds, day and night.
- Agents handle only what needs a person.
- Customers repeat themselves less.
- You can fix causes, not symptoms.
What now answers itself
- Answering order status, delivery and tracking questions from live data.
- Starting returns and exchanges within your policy and issuing labels.
- Applying refunds below the limit you set and logging each one.
- Categorising and routing every ticket to the right queue.
- Summarising the conversation when a person takes over.
What stays with your team
- Refunds above the limit and goodwill decisions.
- Upset, urgent or high-value customers.
- Changes to the returns and shipping policy itself.
- Complaints involving damage, safety or legal claims.
- Replies to anything the system flags as uncertain.
Which online stores should automate support and order care first
If your team answers the same few questions all week, the saving is immediate, and the customer is usually happier to get an instant correct answer than a slow friendly one.
Stores buried in order status tickets
When most tickets are about tracking, live order lookup removes the bulk of the load at once. We look at this situation in the audit and give online stores an honest view of whether the build is worth doing now or later in the automation work.
Stores with frequent returns
Fashion, footwear and home goods benefit from a returns flow that follows the policy and issues labels without a ticket. If this describes your business, the automation work for online stores is likely to pay back quickly, and we will tell you plainly if it will not.
Stores serving several time zones
Instant answers outside office hours stop overnight queues from building. Owners in this position often say the biggest change is the time returned each week, and automation is built to deliver that first for online stores in the customer support and order care automati build.
Stores with a small support team
One or two agents can cover far more volume when routine questions never reach them. This is the kind of situation where a fixed-price build is easier to justify than a monthly subscription for automation for online stores.
Stores with seasonal peaks
Launches and holidays multiply tickets, and automation absorbs the surge without temporary hires. We look at this situation in the audit and give online stores an honest view of whether the build is worth doing now or later in the automation work.
Stores selling on WhatsApp
Customers who already message you on WhatsApp expect the same quick, correct answers there. If this describes your business, the automation work for online stores is likely to pay back quickly, and we will tell you plainly if it will not.
The store and channel events that start each support journey
The system listens for the moments customers write and the moments your store can write first.
inbound_messageCustomer writes on any channel
A message on chat, email or WhatsApp is matched to the customer and their latest order before an answer is chosen. We test this moment on your own records before launch, so the automation build for online stores has met it before it meets a real customer.
order_tracking_updatedTracking changes
A carrier exception or delay triggers a proactive message before the customer has to ask. The timing of this step is written down in the rule table, which means you can change when it happens without asking us to rebuild anything in the automation build for online stores.
return_requestedReturn requested
A request is checked against the policy window, item condition rules and order status before a label is issued. If the same event arrives twice, the second copy is recognised and ignored, so automation for online stores never repeats an action by accident.
refund_requestedRefund requested
Refunds below your cap are processed and logged, and larger ones go to a person with the evidence attached. A short summary of how often this event occurs appears in the weekly report, giving online stores a clear view of how busy this part of the automation work is.
sentiment_flagCustomer sounds upset
Strong frustration, legal words or repeated contact route the conversation to a person immediately. Where the event depends on outside data, the data is checked for freshness first, because a stale figure is worse than no figure for automation for online stores.
ticket_closedTicket closed
Closing a ticket records the category and outcome, and a satisfied resolution can start a review request. Each moment like this has its own rule, so automation for online stores behaves the same way every time and never has to guess what to do next.
One customer question followed from chat to answer and, when needed, to a person
This shows how an order question is answered from live data and how a harder case reaches your team without losing anything.
- 01
The customer writes
A shopper asks on the website chat where their order is, and the system matches the email or order number to the order in the store. At the end of this stage you can pause, adjust a rule or carry on, so automation for online stores always moves at the pace that suits you.
- 02
Live data is read
It reads the fulfilment status and the carrier tracking, so the answer is the real delivery day and not an estimate from the order date. Every step like this is recorded, so the automation work for online stores can be traced from the first input to the final result without any gaps.
- 03
The answer is sent
The reply gives the date, the tracking link and what to do if the parcel is late, in your tone and quoting your shipping policy. If the step cannot finish, the record says why and waits for you, so automation for online stores never moves on with a half-completed task.
- 04
A return follows
The same customer then asks to send an item back, and the system checks the window and condition rules, issues a label and records the return. You can see the outcome of this step before the next one starts, which keeps the automation build for online stores under your control throughout.
- 05
A limit is reached
They ask for compensation above the refund cap, so the system stops, writes a summary of the order and conversation and assigns it to a person. The step uses only the facts you supplied, so nothing in the automation result for online stores depends on guesses or on outside sources you did not approve.
- 06
The ticket is closed
The outcome is categorised, and the cause joins the weekly report that shows which problems generate the most tickets. Timing for this step is paced to the limits of your tools, so automation for online stores keeps running calmly even when volume is high.
Pricing
Price your support and order care automation
Choose how many support services to combine, tell us about your help desk and channels, and add any extras, and the total and live date update as you go.
What support and order care automation costs and what raises the price
Our fee is fixed and paid once, while your help desk, carrier tools and WhatsApp messages are billed by their own providers.
Number of channels
Chat, email, WhatsApp and social inboxes each add an integration and a test set. If this factor is small for you, it adds little to the price, and the written quote shows exactly how much it did add for online stores in the automation work.
Complexity of returns
Exchanges, store credit, restocking fees and final-sale items add rules to write and test. You can lower the cost by tidying this part first, and we say so plainly in the plan when the automation work for online stores would benefit.
Languages
Each language multiplies the tone checks and the test questions. Anything extra that this factor creates later is quoted before it is built, so the fixed price for automation never grows by surprise for online stores.
Help desk and tools
Older or heavily customised help desks take longer to connect cleanly. We explain this factor in the quote in plain words, because online stores should understand what drives the price before agreeing to anything in the automation work.
Escalation and approval rules
Multi-step approvals and several queues add configuration and testing. Changes to this factor after the quote are handled as a written change, with its own price, and never as a hidden charge on automation for online stores.
Reporting depth
Cause-of-contact dashboards and cost-per-ticket views take extra build time. A smaller first build can leave this factor for later, and online stores can add it at a priced step once the first results are in in the automation work.
Gorgias, Zendesk and similar help desks bill by plan and by automated resolution; WhatsApp is billed per message by Meta.
Next step
Ready to price Customer Support and Order Care Automation for Online Stores?
Customer support and order care automation for online stores answers the questions that arrive after checkout, such as where an order is, how to return it and whether it can be changed, from live store data on chat, email and WhatsApp, and hands anything sensitive to your team with the full history attached.
- One fixed price from $3,190, paid once
- Answers grounded in live order data
- Thirty days of fixes after launch
Three more order care jobs the same system can run
Because the order data and policies are already connected, further jobs are quick to add.
Proactive delay notices
When tracking shows a delay, the customer is told first, with a new date, which prevents many of the tickets that would have followed. The job follows the same approval rules as everything else, so nothing reaches a customer of online stores without passing the checks you already trust in the automation work.
Order changes before dispatch
Address fixes and cancellations are accepted until the order is picked, and refused politely afterwards with the reason. If the job does not pay back, it can be switched off without affecting the rest of the automation build, and nothing needs to be unpicked for online stores.
Review and feedback prompts
A resolved ticket with a happy customer can start a review request, and an unhappy one never does. The wording and the limits for this job come from the same rule table as the main automation work, so one change updates both for online stores.
Which data the support system reads and where each fact is the source of truth
A support answer is only as good as the data behind it, so each fact has one owner and one place it is read from.
| Store object | Fields we use | Direction | Source of truth |
|---|---|---|---|
| Orders | Status, items, fulfilment, address, totals | Read live | Store orders |
| Tracking | Carrier, events, delivery estimate | Read live | Carrier or tracking service |
| Policies | Returns window, shipping rules, refund limits | Read before every answer | Your written policy pages |
| Customers | Email, history, tags, consent | Read, notes written | Store and help desk |
| Tickets | Channel, category, owner, outcome | Written by the system | Help desk |
| Refund log | Amount, reason, approver, time | Written on every refund | Store and ticket |
Policy text is read from your published pages, so the system quotes the same wording your customers can see.
Edge cases in support automation that we test before launch
The hard conversations are the ones that decide whether customers trust the system, so we test them deliberately.
An order that cannot be found
When no match exists, the system asks one clarifying question and then hands over instead of guessing at an order. We test this case before launch on your own records, so automation for online stores has met it before it meets a real customer on a busy day.
Partial shipments and split orders
Orders that ship in parts are described part by part, with a delivery date for each. When the case appears, the workflow follows a written rule and records the choice it made, so you can review it afterwards if you wish in the automation build for online stores around customer support and order care automati.
Someone else’s order
Order details are shared only after the customer proves they own the order with the email or a verification step. If a rule cannot settle the case safely, it goes to you with the record attached, and automation for online stores waits instead of guessing.
Customers writing in other languages
The system replies in the customer’s language where it can and hands over when its confidence is low. Cases like this are the reason the automation build for online stores includes a trial run, because a tidy example never shows them but real records do for this customer support and order care automati work.
Repeated contact
A customer who writes three times about one issue is escalated to a person automatically. Your answer to this case is added to the rule table, so the same situation is handled automatically the next time it appears for online stores in the automation work in the customer support and order care automati build.
Items outside the policy
Requests outside the return window are declined with the written reason and offered a person for exceptions. The weekly report counts how often this case occurs, which tells online stores whether it deserves a better rule or is simply rare in the automation work.
A help desk add-on, a chat app and a built support system compared
Help desk add-ons are quick to switch on, chat apps are cheap to install, and a built system chooses between them and connects them to your own order data and rules.
| Help desk add-on | Chat app | Checkout Loom build | |
|---|---|---|---|
| Reads live order and tracking data | ✓ | Partly | ✓ |
| Quotes your own written policy | Partly | Partly | ✓ |
| Covers chat, email and WhatsApp together | Partly | – | ✓ |
| Refund limits and approval rules | Partly | – | ✓ |
| Handoff with a summary and history | ✓ | Partly | ✓ |
| Cost pattern | Per resolution fee | Monthly plan | A single build fee plus the tools you retain |
Help desk AI add-ons commonly charge per automated resolution, so we compare that running cost with your ticket volume before recommending one.
How the support system is built and what each tool costs
We choose the tools for your store and explain what each one will cost you every month next to our one-time fee.
Gorgias, Zendesk, Help Scout or Freshdesk
The help desk that holds tickets, macros and reports, with its AI add-on used where it is cost-effective and our own build used where it is not. Its role is written in plain language in the handover guide, which means a new team member at online stores can understand it in a few minutes in the automation work.
Shopify and WooCommerce order data
Orders, fulfilments and returns are read through the platform APIs, using only the permissions the system needs. The monthly price of this layer is written next to our fixed fee before you commit, so the true cost of running automation for online stores is clear from day one.
A carrier or tracking service
AfterShip, ShipStation or the carrier directly, so tracking answers are real events and not estimates. You can replace this layer later with another tool, because the rules live in a table you own and are not locked inside any one product in the automation build for online stores.
WhatsApp Business Platform
Customer service replies inside the free 24-hour window and approved templates for proactive notices, billed per message by Meta. We choose the lightest option that does the job for online stores, since a simpler layer means fewer things to maintain and fewer ways to fail in the automation work.
An AI model with your policies
A language model that answers only from your policies and live data, with instructions that forbid inventing terms. If you already pay for something that covers this need, we use it, and we only add a new service when automation for online stores genuinely requires one.
Make, Zapier or n8n
Glue between the store, the help desk and the channels, with retries and alerts for every step. Access to this layer is granted from your own account and can be removed at any time, so you stay in control of the automation build for online stores.
How we keep support automation correct and available
A wrong answer costs more than a slow one, so reliability work is mostly about grounding and early warning.
Answers grounded in your data
The system answers from live data and written policy and says it does not know when neither contains the answer. When something goes wrong in automation for online stores, the failure is named, retried within safe limits and listed for you, instead of vanishing into a log nobody reads.
Retries and fallbacks
A failed lookup retries, then falls back to a human reply time and a ticket, never a guess. This safeguard runs on every batch and not only on a schedule, so a problem in automation is caught before it can spread to the next record for online stores.
Alerts that name the failure
Alerts name the channel, the step and the customer count affected. Each alert names the rule, the record and the next step, which means you can fix the cause from the message alone without opening any tool in the automation build for online stores.
A test set of real questions
Every release is run against a set of your real past questions, and answers are compared to what your team replied. We compare the results of automation with your own records on a regular basis, so a small drift for online stores is repaired before it becomes a large one.
Response time tracking
First reply time and resolution time are tracked by channel so slowdowns show early. If a check fails, nothing is sent or changed for that record, and it waits in a short list for you, because a delay costs less than a wrong action in the automation build for online stores.
Written answers from the owner
Questions and incidents in the first month are answered by the owner in writing, with the cause and the fix. The safeguard is tested during the trial batch by feeding it deliberately awkward records, so online stores sees how it behaves before real customers are involved in the automation work.
Privacy, permissions and protected data in support automation
Support conversations include names, addresses and order details, so access is narrow and the AI sees only what it needs.
Least-privilege access
We request read access to orders and write access only to the actions you approve, such as labels and capped refunds. Every access is logged in your own accounts, so you can see who or what touched a record and when, without asking us for a report in the automation build for online stores.
Protected customer data respected
Shopify’s protected customer data rules decide which fields an app may read, and we request only the levels the build needs. If a key is ever lost, it can be replaced in minutes without rebuilding the automation work for online stores, because the rules do not depend on it.
Credentials in your accounts
API keys stay in your accounts and can be revoked at any time. The arrangement is reviewed at the end of the month of corrections, and any access that is no longer needed is removed in writing in the automation build for online stores.
Minimal data to the AI
The AI receives the order facts needed to answer and never payment details. Customer details are never used to train outside models, and drafts for online stores are built only from the facts and records you supply in the automation work.
Identity checks before order details
Order information is shared only after the customer confirms the email or order number. We explain in plain words what each permission allows, so the person approving it for online stores knows exactly what they are agreeing to in the automation work.
Clean removal
We list every change we made and remove our access when we hand over. At the end of the engagement you receive a list of every connection that was made, so nothing stays open by accident in the automation build for online stores.
What you receive with your support and order care build
Every plan ends with a working system, a tested set of answers and the notes to keep it healthy.
- Order status and tracking answers on the channels in your plan, from live data.
- A returns and exchange flow that follows your written policy and issues labels.
- Refund limits, approval rules and an audit log of every refund.
- Ticket categories and routing in your help desk.
- Handoff summaries that carry the order and conversation to a person.
- A test set built from your real past questions and the results.
- Proactive delay notices where included in the plan.
- A weekly report showing why customers write.
- Thirty days of fixes after launch.
Reviews from clients and the support facts behind our approach
Below are unedited reviews from verified clients of the Checkout Loom team, followed by the support figures our designs are built around.
- 1 in 5tickets is an order status question in published helpdesk data, so live order lookup comes first.
- 2024is the year a tribunal held an airline responsible for what its chatbot told a customer, which is why answers are grounded in your policy.
- 30 daysof fixes follow launch so the system settles before we step back.
Ticket shares come from Gorgias and Yuma published data; the chatbot liability case is Moffatt v Air Canada, 2024 BCCRT 149.
★★★★★
Everything was configured exactly as discussed, and the team made sure the automation was stable before delivering it. It has been a huge time-saver for our whole team, and it runs without any manual work.
BellamyUnited States
Verified
★★★★★
This was excellent automation work, and it is clear that the team has strong experience with AI and automation. I highly recommend the Checkout Loom team to other businesses.
FinnUnited States
Verified
★★★★★
I am genuinely impressed with the work the Checkout Loom team did on my AI and automation project. They are extremely professional, skilled, friendly and easy to work with, and I am delighted with the final result.
DavidUnited States
Verified
★★★★★
The Checkout Loom team built an automation that simplified my workflow and worked perfectly from day one. Communication was excellent, delivery was fast, and I would happily recommend the service.
RebeccaUnited States
Verified
★★★★★
They set up my automation remarkably fast and executed everything perfectly. Communication and service were top tier, so I could not be happier with the results and I highly recommend the Checkout Loom team.
AbbieGermany
Verified
★★★★★
The automation was set up in a clean and practical way by the Checkout Loom team. It saved me a lot of manual work and made the whole process much easier.
JanoUnited Kingdom
Verified
★★★★★
I highly recommend ordering from the Checkout Loom team. I had slow responses and poor communication with other providers, but this team was great and I am very happy with their service.
HarmetUnited States
Verified
★★★★★
I am a returning customer because my first AI automation workflow worked so well. Once again everything was built exactly as requested, and the whole process was reliable from start to finish.
WilliamUnited States
Verified
How the support build runs from ticket audit to a staged launch
We start from your real tickets because they show what customers actually ask.
- 01
Ticket audit
We read a batch of your recent tickets, group them by cause and measure how many are routine. You see the result of this step in writing before the next one begins, which keeps the automation build for online stores on schedule and under your control.
- 02
Policy and limits
We turn your returns, shipping and refund rules into written limits and agree them with you. If this step shows a problem, we say so at once and propose the fix, and the date for automation is moved in writing rather than quietly for online stores.
- 03
Connect the data
We connect orders, tracking and the help desk with the narrowest access possible. Nothing in this step touches your live customers, so online stores can review it calmly and ask for changes before anything goes public in the automation work.
- 04
Build and test
We build the answers and actions and run them against your real past questions on a test store or sandbox. The step has a clear finish line, which means you always know whether the automation work for online stores is on time or running behind.
- 05
Staged launch
We switch on order status first, watch it for several days and then add returns, WhatsApp and the rest. Questions that arise here are answered in writing, so there is a record of every decision made about automation for online stores.
- 06
Hand over
You receive the playbook and reports with thirty days of fixes, and we remove our access. We keep each step small enough to check, because large steps hide mistakes and make the automation build harder to correct for online stores.
Estimate what support automation could save your team each month
Put in your ticket figures and the estimate shows what the automation rate you choose would save, which is a planning guide and not a forecast.
Tickets handled automatically each month–
Agent hours saved each month–
Handling cost saved each year–
The estimate uses the automation rate you enter and ignores any extra sales from faster answers, so the real value is usually higher than shown.
Customer support and order care automation questions, answered in full
These are the questions store owners ask about support automation, accuracy, channels and cost before they order.
What is customer support and order care automation for online stores?
It is a system that answers the questions customers ask after checkout, such as where an order is, how to return it and whether it can be changed, using live order data and your written policies, and that hands anything sensitive to a person with the history attached.
Which support services can I combine?
You can combine an AI support chatbot, order status and tracking answers, returns and refund handling, proactive delay notices, WhatsApp support and help desk routing, and we recommend the order from your ticket data.
Will the system make up answers?
No, because it answers only from live data and your published policy, it says when it does not know, and every release is tested against your real past questions before customers see it.
Can it issue refunds?
It can, but only up to the limit you set, with every refund logged with the reason and approver, and anything above the limit goes to a person with the evidence attached.
Does it work on WhatsApp and email as well as chat?
Yes, all channels share the same order data and answers, WhatsApp is used only for customers who have opted in, and your help desk shows a single queue.
Which help desk do I need?
Gorgias, Zendesk, Help Scout and Freshdesk are all supported, and a shared inbox works for smaller stores, with the best choice depending on your volume and the cost of automated resolutions.
How do you protect customer data?
We request the narrowest access, respect Shopify’s protected customer data levels, send the AI only the facts needed to answer and remove our access when we finish.
When will support go live and what do I need to provide?
A pair of services is usually live in three to five weeks, and a full system in up to ten. We need access to your store, help desk and carrier tools, an export of recent tickets and your written policies, and we send a checklist after you order.
Are there running costs after I have paid for the plan?
Our fee is charged once, while your help desk, carrier tool and WhatsApp messages are billed by their providers, and we list the expected monthly cost for your ticket volume before you decide.
Can I start with one service and add more later?
Yes, because the first service builds the data connections and policy rules that later ones reuse, which makes each additional service quicker and cheaper to add.
Let your store answer order questions while your team handles the people
Choose a plan in the pricing calculator and continue to checkout, or request a quote listing your platform, help desk and the questions your team answers most. We reply in writing within one working day with a confirmed start date and a short checklist, so the ticket audit begins straight away.
- One fixed price from $3,190, paid once
- Answers grounded in live order data
- Thirty days of fixes after launch