A shopper asks whether a backpack will fit their laptop. Your colleague opens the product page, checks the dimensions, recommends a size and sends a link. The shopper still has to find that option, select it again and work out whether it is available.
At busy times, the same questions sit unanswered. Outside working hours, the shopper may leave before your team can help. You add an AI assistant, but now the conversation finishes with a helpful paragraph and another product link. The final steps still belong to the customer.
For a WooCommerce store, I would start with that gap: can a shopper move from a question to an inspectable product choice and a working checkout? The objective is a useful buying journey, with clear limits on what the assistant can promise.
My work on Slivo connects Retell voice conversations with WooCommerce catalogue data, visible product cards and an order workflow. The journey below is how I would scope a similar shop project. It is a proposed implementation approach, not a claim that adding an assistant has produced a measured sales increase.
Pick the questions that actually interrupt a purchase
Bring the questions your staff answered last week, along with the product pages they used. Separate routine facts from questions requiring judgement. “Is the black version available?” differs from “Will this fit a device whose model I cannot identify?”
For the backpack example, the assistant could ask for the laptop dimensions, show suitable products and explain the relevant catalogue facts. If the store does not record the usable compartment dimensions, it should say that a fit check is needed. A confident answer cannot replace missing product information.
Choose one product category for the first release. Define the questions it can answer, the options it can help select and the situations it must pass to a person. This gives your team a manageable trial and a clear boundary for the assistant's work.
Also choose the interaction your customers need. Text may suit a quick stock check. Voice may help someone describe several requirements, especially when the product options remain visible on screen. You do not need voice simply because it is available; the choice should follow the shopping task.
Show the product and the exact option being recommended
A useful recommendation should lead to a real item in your store. Show its name, image, selected option and the information supporting the suggestion. Let the shopper compare or change the choice before adding it to the cart.
This matters when one product has several sizes or colours. In WooCommerce, variations can have different prices and stock. A general answer about “this backpack” may describe one option while the shopper selects another.
I would have the conversation and the visible selection refer to the same product and option. If the shopper changes their requirements, the assistant should confirm the new choice. If two items fit, show the tradeoff using recorded information rather than quietly choosing the more expensive one.
This is one reason the visual interface matters in Slivo's voice-commerce implementation. The customer can inspect product cards while receiving guidance, rather than remembering several spoken options. That engineering case covers the system behind the experience; here the starting point is what your shopper must be able to do.
Check the store before making a promise
Your catalogue may be copied into a search system so the assistant can find useful products. That copy helps discovery, but prices and availability can change before the customer acts.
The shopping flow should check current store information at the relevant step. If the selected option is no longer available, tell the shopper and show any valid alternatives. Do not leave the original recommendation looking purchasable. If the price has changed, show the current price and ask the customer to review it.
Stock rules also matter: available now, available on backorder and temporarily unavailable are different promises. Delivery estimates may depend on the address, shipping method and store settings. The assistant should explain known policy and leave the final shipping options and total to checkout when those details are not yet available.
In Slivo, the catalogue is synchronized for search and the order workflow queries WooCommerce again for current price and availability. For your store, I would check the actual stock, shipping and variation rules before defining what the assistant can confirm.
Make the cart and checkout handoff explicit
“I found the right item”, “it is in your cart” and “your order is complete” are different outcomes. Your customer should be able to see which one has happened.
For an initial project, I would usually guide the shopper to the correct item, confirm the option and quantity, and connect that selection to the store's checkout. The customer reviews the cart, delivery details, final total and payment using the checkout you already operate.
Adding an item to the cart does not complete payment. Creating an order record does not necessarily mean it has been paid. The assistant should describe the confirmed state returned by the shop, rather than announcing success because the conversation reached its final line.
Test the handoff with the checkout and extensions you actually use. A bundle, subscription, personalised product or unusual shipping rule may require additional work. Those requirements belong in the project scope before someone promises that a general shopping assistant will handle every product.
Give staff the question and the work already done
Some purchases need a person: a missing measurement, an exception to the returns policy or a product question the catalogue cannot resolve. The useful outcome is a clear handoff, with the conversation and selected products available to your team.
Ask only for the contact information needed for that handoff, with the shopper's agreement. Tell them whether they are speaking to a person now or leaving a request for later. If staff are unavailable, the assistant should not describe a saved request as a live transfer or promise an unagreed response time.
For the backpack question, staff should see the laptop measurements supplied, the option considered and the missing fit information. They can resolve the specific uncertainty and update the catalogue if the answer will help future shoppers. That is more useful than asking the customer to start again.
Decide whether a plugin covers the journey
A ready-made plugin can be the right starting point when the task is straightforward and its documented features work with your store. Check it against your actual questions and checkout before commissioning a custom product.
Use the same small set of shopping scenarios to assess both options:
| Your store needs | What to check before choosing a solution |
|---|---|
| Answers about a standard catalogue | Correct product facts and a clear response when information is missing |
| Different sizes, colours or bundles | The exact purchasable option remains consistent through the cart |
| Current availability and pricing | Changed information is checked and shown before the relevant action |
| Staff involvement | The unresolved question reaches a real destination with useful context |
| A particular checkout or extension | The buying journey works with that configuration |
| Voice plus visible product selection | The conversation and on-screen choice stay aligned |
Custom development becomes relevant when the required journey is not covered: special selection rules, a combined voice and visual experience, additional business systems or a handoff specific to your team. There is no need to build every part from scratch. The project can combine supported WooCommerce behaviour with the missing integration or interface.
Include ongoing ownership in that decision. Who updates product information, reviews unanswered questions, checks failures after plugin updates and adjusts the assistant's limits? A small implementation with a clear owner can be more useful than a broad feature list nobody maintains.
Trial one buying journey before expanding
For the first release, agree on one category, the supported question types, one checkout path and the staff handoff. Use examples your team already understands to decide what a correct answer and a successful selection look like.
Try a missing attribute, an unavailable variation, a changed price, a shopper revising their choice and an unanswered question outside business hours. Check the actual cart and order state after each attempt. Also confirm that a repeated request does not silently add the same item twice.
During the trial, review incorrect recommendations, unanswered questions, cart handoffs and completed purchases where your existing analytics can connect the steps appropriately. Count the work staff still need to do. A busy conversation log is not evidence that the assistant improved sales, and a small trial does not establish the cause of every conversion change.
Keep the normal shopping path available, so a customer can browse and buy without using the assistant. Give the store owner a way to pause the feature if product data or an integration starts behaving unexpectedly.
Bring the shopping problem, not just a request for a chatbot
To scope the work, bring representative customer questions, the affected product category, your checkout and extensions, and the staff process for unresolved questions. An example where helpful advice still fails to become a correct purchase is especially useful.
Slivo demonstrates my work connecting conversations, product data, visible selection and the SaaS layer supporting stores. For your business, I would turn the agreed buying journey into a scoped integration, test it against the store's rules and hand over the controls your team needs to operate it.
If shoppers need more than a product-page answer, tell me where they get stuck. My AI product engineering service covers the application and integrations around the assistant; voice AI development is relevant when voice belongs in that journey.