AI Shopping Assistant

This article explains how to configure an AI Shopping Assistant. The assistant is a conversational tool embedded in your store that lets customers describe what they are looking for in natural language and receive matching products straight away, without scrolling through long product lists.

The assistant supports a range of capabilities:

• Profile context - the assistant has access to the profile of the customer, so its responses can be personalized to that specific person.
• Conversation history - customers can view their past conversations from up to two weeks back and pick up where they left off.
• Product page context - the assistant is aware of the product page the customer is currently on, so it can answer contextual questions like "show me accessories that go with this product."
• Persona and tone of voice - you can give the assistant a name, a motto, and a specific tone to match your brand identity.
• Engagement level - you can control how inquisitive the assistant is, that is, how intensively it asks the customer follow-up questions to clarify their needs before responding.
• Recommendation models as tools - you can connect AI recommendation campaigns to the assistant. Each campaign has its own filtering and boosting rules, which gives you control over what products the assistant shows.
• Brickworks schemas as tools - you can attach a Brickworks schema as a tool. This allows the assistant to pull data from Synerise objects like aggregates or expressions, or from external services.
• MCP tools - you can connect the assistant to any MCP (Model Context Protocol) server to give it access to external tools and data.
• Custom actions - you can define a tool that returns a specific action payload during a conversation. Your frontend can then handle this action in any way you choose.

Prerequisites

1. To configure Shopping Assistant you must be granted user permissions.

2. Upload and configure an item feed:

   • If you use Google Merchant feed, configure pulling it from an URL as described in Configure AI engine for your item feed.
   • If you want to use a Synerise catalog, through API request or through a workflow and then configure the AI engine for your item feed.
3. Configure AI engine for your item feed. If you use Google Merchant Feed, in this step, you can launch pulling the feed from the URL.

4. Go to AI Hub > AI Search and create an index. In the configuration of the index, you must:

   • add the category attribute to facetable attributes.
   • set the Matching words option to At least one word must match.

Configuration

Creating an AI Assistant

1. Go to AI Hub > AI Assistant > New AI Assistant.
   Result: A configuration form with four sections displays.

   

Brand

This section defines your brand identity. The assistant uses this information to understand the business context and adjust its responses accordingly.

1. In the Brand section, click Define.
2. In the Brand name field, enter the name of your brand or business.
3. In the Business description field, enter a description of your brand or business. This is used as additional context that affects the assistant's behavior.
4. Confirm the settings in this section by clicking Apply.

Assistant

This section defines the persona, tone of voice, and behavior of the assistant.

1. In the Assistant section, click Define.
2. In the Persona name field, enter the name the assistant uses to introduce itself to customers.
3. In the Motto field, enter a short tagline for the assistant.
4. In the Tone of voice field, describe how the assistant should sound in its responses, for example homely, enthusiastic, reactive, or friendly.
5. In the Style Guide field, enter guidelines for the assistant's communication style.
6. In the Assistant job field, describe the assistant's role and how it should help customers, for example recommending products or asking about their needs.
7. In the Response words limit field, enter the maximum length of the assistant's responses, in words.
8. Optional: Under Suggestions, click Add suggestion to add a quick prompt shown to the customer in the chat interface. You can add up to 10.
9. Confirm the settings in this section by clicking Apply.

Products

This section configures the product catalog the assistant uses to find and return items.

Search index

Click Select index to choose which AI Search index the assistant will use. After selecting one, you can click Change to pick a different index or remove the current selection. Selecting an index unlocks the attribute mapping and filter options below.

Attribute mapping

After selecting a search index, map its attributes to the assistant's built-in product attributes so it knows which field to use for each one, for example, which field holds the price or the image link. The table has two columns:

• Source - the fixed built-in attributes the assistant needs, for example itemId, category, title, description, price, imageLink, link.
• Target - the corresponding attribute from the selected search index, chosen from the dropdown.

IQL Filter

Click Define filter to add an IQL expression that limits which products the assistant returns. This option is available only after you select a search index.

Tools (optional)

This section extends the assistant with additional capabilities. Click Add tool and select a type from the menu. You can add multiple tools. Each tool appears as a card with a delete and info icon.

Recommendation

Links an AI recommendation campaign to the assistant. The campaign can include its own filtering and boosting rules.

1. Click Add tool and select Recommendation.
2. In the Tool name field, enter a name for the tool. Maximum 100 characters.
3. In the Instructions field, describe when and how the assistant should use this tool. Maximum 2000 characters.
4. In the Recommendation field, select the recommendation campaign from the dropdown.
5. Confirm the settings in this section by clicking Apply.

Brickworks schema

Gives the assistant access to a Brickworks schema. This allows it to pull data from Synerise objects like aggregates or expressions, or from external services.

1. Click Add tool and select Brickworks schema.
2. In the Tool name field, enter a name for the tool. Maximum 100 characters.
3. In the Instructions field, describe when and how the assistant should use this schema. Maximum 2000 characters.
4. In the Brickworks schema field, select the schema from the dropdown.
5. Confirm the settings in this section by clicking Apply.

Custom action

Returns a specific action payload during the conversation. Your frontend application can handle this action in any way you choose.

1. Click Add tool and select Custom action.
2. In the Tool name field, enter a name for the tool. Maximum 100 characters.
3. In the Instructions field, describe when and how the assistant should trigger this action. Maximum 2000 characters.
4. In the Custom action name field, enter the name of the action returned in the payload, which your frontend uses to identify it. Maximum 100 characters.
5. Confirm the settings in this section by clicking Apply.

MCP Server

Connects the assistant to an external MCP (Model Context Protocol) server so it can use external tools and data.

1. Click Add tool and select MCP Server.
2. In the Tool name field, enter a name for the tool. Maximum 100 characters.
3. In the Instructions field, describe when and how the assistant should use this MCP tool. Maximum 2000 characters.
4. In the Connection field, select the MCP connection from the list.
   This list loads the connections defined in Settings > Connections. You can also create a new connection directly from this field: click Select connection, then Add connection in the list that appears. A connection created this way is automatically assigned to the HTTPS category.
5. In the URL field, enter the URL of the MCP server endpoint. Maximum 2000 characters. Example: https://example.com/mcp.
6. In the MCP tool name field, enter the name of the tool on the MCP server. Maximum 200 characters.
7. Confirm the settings in this section by clicking Apply.

Saving your configuration

In the upper-right corner, click Save.

Testing the AI Assistant

In the Preview tab, you can send test messages to see how the assistant responds. Check that it handles your queries correctly and adjust the configuration if needed before going live.