A Gorgias alternative should be evaluated around the work your store needs to do after a customer asks a question. Some enquiries are about products, delivery policies and returns guidance. Others require current order information, changes to a transaction or coordination across a support team. A website assistant can be excellent at the first group without covering every task in the second.
Chaat is a candidate for a focused public storefront assistant built around your content. Gorgias presents a conversational AI platform for ecommerce with a broader commerce-support focus. This guide helps you separate knowledge from order actions, prepare a realistic store trial and decide which operating model fits your business.
Comparison published by Chaat. Competitor overview checked against official product information. Features and terms can change; verify requirements with each provider.
Categorise store enquiries by the information they need
Review recent customer questions and identify the evidence required to answer each one. “What are the dimensions?” can be answered from a product specification. “Where is my order?” requires information about that customer’s transaction. “Can I return this?” may begin with a general policy but become order-specific as the conversation develops.
Create separate groups for public product knowledge, public policy, live order information and actions. This avoids evaluating every question as though it were a FAQ. It also helps you identify a useful first scope for an assistant without promising capabilities that have not been implemented.
Consider the customer’s next step. A pre-purchase question may end with a relevant product page. A delivery problem may need a request to the team. A cancellation may need an authorised operation in an order system. The same chat interface can lead to each, but the underlying requirements differ.
Compare the relevant product capabilities
Gorgias’s official website describes an ecommerce-focused conversational AI platform. Review the current product and integrations that matter to your store. Ask for the exact order-related tasks you need to be demonstrated with the appropriate permissions and confirmation behaviour.
Chaat’s core workflow is knowledge-based website conversation: create a bot, add public sources, test answers, configure the chat and publish it. Conversation history and optional contact requests support review and follow-up. These functions should not be presented as proof that Chaat can inspect or change orders in your commerce platform.
A fair comparison identifies the scope each candidate covers. If the store mainly needs help explaining products and policies, a focused assistant may be enough. If order actions are central, treat them as essential requirements rather than optional items hidden at the end of a checklist.
Prepare product information that supports useful answers
Choose a representative product sample with meaningful differences. Include sizes, materials, compatibility, variants and any important limitations. Similar products are especially useful for testing whether an assistant can keep details separate rather than merging them into a generic recommendation.
Explain units and abbreviations in the source. A spreadsheet can be valuable knowledge if column names are clear and product identifiers are preserved. A bare list of codes is harder to interpret. Make sure a retrieved row or paragraph still identifies the product it describes.
Keep recommendations tied to published facts. The assistant can compare documented features and ask what the customer needs, but it should not invent a use case or guarantee compatibility that the product information does not establish. This matters most when a purchase depends on a specific technical condition.
Preserve the conditions in store policies
Returns, delivery and warranty guidance often contain exceptions. Organise them so the general rule and the exception remain connected. Name the relevant product category, region or timeframe directly. A short answer that drops a condition can create a customer expectation the store cannot honour.
Test hypothetical questions. Ask about returning an item after it has been used, delivery to a location outside the standard area or a product category with a separate policy. The assistant should apply the documented distinction or explain when the information is insufficient.
Do not turn policy explanation into an individual approval. The bot can say how to request a return and what the published conditions are. It should not claim that a return has been accepted or a refund issued unless an authorised system has actually confirmed that action.
Keep live commerce facts with live systems
Inventory, shipment status and current promotions can change quickly. A website extraction or catalogue document is a snapshot, not necessarily a live connection. If the assistant cannot inspect the relevant system, it should direct the customer to the appropriate current page or support process.
Ask vendors to demonstrate an order question from beginning to end. How is the customer identified? What information is retrieved? What happens when a record cannot be found? If an action is performed, how is success confirmed? A confident answer in a demo is not enough to establish these details.
For a Chaat pilot, define the public-knowledge scope explicitly. It may explain tracking instructions or show the order-help route without accessing a private order. That can still be useful, provided the wording does not imply that the assistant has done more than it has.
Evaluate knowledge updates during a trading week
Stores change information frequently. A promotion ends, a new variant arrives or a delivery explanation is revised. Test how the proposed tool handles those ordinary updates. Ask the content owner to make a change and verify the new answer without relying on the original evaluator.
Chaat accepts public URLs, documents and pasted text as knowledge sources. Review extraction for old offers, duplicated navigation and incomplete product variants. Remove obsolete material deliberately and wait for the updated source to finish processing before replaying the test questions.
Keep a small source register for the pilot. Record which document owns each important fact and which questions should be retested after a change. This helps prevent an old offer in a PDF from contradicting a newer policy page.
Plan contact requests for unresolved issues
Customers who need order-specific help should have a clear route. Decide whether that route is an existing support form, a published address or Chaat’s optional contact request. The assistant should explain the actual process and avoid promising immediate staff attention unless that service exists.
When Chaat requests are enabled, configure notifications if useful and assign someone to review the dashboard. Test a clearly identified request and check whether the team can understand the customer’s issue from the context. The follow-up process matters as much as successful submission.
If automatic creation of a record in another helpdesk or commerce system is required, verify that connection separately. An email notification should not be described as equivalent to all the order context, assignment and automation available in a broader support setup.
Test the storefront experience on mobile
Install the widget on a product page and a help page. Check whether the launcher covers the basket, checkout, sticky purchase button or cookie notice. A chat assistant should support shopping without obstructing the primary controls.
Configure the chat name, colours, photo and launcher presentation to fit the store. Use concise replies with clear product links. When an answer compares options, short paragraphs or a small list can make it easier to understand than a long block of promotional text.
Try a conversation that moves between two products and then asks about delivery. Check that the assistant keeps the details straight and links to the correct destination. Follow a link, return to the conversation and restart it. These ordinary interactions should feel predictable.
Compare costs for the same workload
Use current provider pricing and the plans that include your essential requirements. Record how usage is counted and which functions are optional. A focused public assistant and a broader ecommerce support platform may cover different work, so a headline-price comparison can be misleading.
Include the tools and staff work that remain necessary. If another system still handles order changes, its cost belongs in the total. If a platform removes substantial manual order work, account for that value. Content maintenance and request review also need an owner whichever product you choose.
Model a typical week and a busy campaign period. Ask how the service behaves when demand rises and whether the required features remain available under the relevant terms. Avoid promising a fixed saving without evaluating the store’s actual usage and operating process.
Keep the trial results available to future maintainers so later changes can be checked against the same approved product facts and policy conditions.
Choose based on demonstrated customer outcomes
Pilot Chaat on a bounded set of product and policy questions. Use approved sources and a repeatable test set, including exceptions and requests the assistant cannot fulfil. Review source-based answers in the Test view and confirm that the public reply gives a useful next step.
Gorgias deserves consideration where its ecommerce-focused support capabilities match the store’s operational needs. Chaat deserves a trial where the main goal is a maintainable website assistant explaining public information and collecting optional follow-up requests.
The right choice preserves the distinction between knowing a policy and acting on an order. Evaluate both sides when your business needs both. A useful assistant helps customers understand what to do next without manufacturing inventory, shipment updates or completed transactions.