AI agents

AI agents for customer insight & research

3 live agents (Basket Affinity Analyst, Customer Lifetime Value Model, Style Preference Profiler) and 5 on the roadmap: what each does, the data it needs and the questions it answers.

2 Nov 2026 · 2 min read

3 agents you can switch on today

Basket Affinity Analyst

Finds which categories are bought together and suggests bundles, adjacencies and cross-sell placements.

Try the live demo →

Who it's for: Your team (console, API)
Data it needs: Order lines, Products
Tools it uses: read-only SQL over your retail data (sandboxed per workspace)

Ask it, for example:

  • "Which categories are most often bought together?"
  • "What do customers buy with handbags?"
  • "Suggest 3 bundles from basket data"

Customer Lifetime Value Model

Estimates customer value by tier and city from order history to guide retention and acquisition spend.

Try the live demo →

Who it's for: Your team (console, API)
Data it needs: Customers, Orders, Order lines
Tools it uses: read-only SQL over your retail data (sandboxed per workspace)

Ask it, for example:

  • "What is the average customer value by tier?"
  • "Which cities have our most valuable customers?"
  • "How much more do Club Gold members spend?"

Style Preference Profiler

Profiles customer style clusters from purchases by colour, category and price to guide ranging.

Try the live demo →

Who it's for: Your team (console, API)
Data it needs: Customers, Orders, Order lines, Products
Tools it uses: read-only SQL over your retail data (sandboxed per workspace)

Ask it, for example:

  • "What style clusters do our customers fall into?"
  • "Favourite colours by tier"
  • "Do Club Gold members buy higher price points?"

Coming next

  • Footwear Fit Data Analyst: Analyses fit-related returns by shoe model and size to improve size advice and future buys.
  • Survey Insight Summariser: Summarises open-text survey responses into themes, sentiment and verbatim quotes for each audience.
  • Net Promoter Driver Analysis: Links NPS scores to journeys, stores and products to show what drives promoters and detractors.
  • Shopper Mission Classifier: Classifies trips into missions such as top-up, big shop or gifting to tailor ranges and layouts.
  • Conversational Survey Agent: Runs short chat-based surveys with customers and adapts follow-up questions to their answers.

How to turn them on

  1. Load the data each agent needs (upload, API or, soon, a connector to your e-commerce platform).
  2. Open Agent catalog in the ServiceBuddy console: agents whose data is present show as ready.
  3. Install, add your own instructions, and test in the Playground.

#customer insight#ai agents

See it on your own catalog. Explore the agents

Coming soon: Customer insight & research

🔍 Coming soon

Customer insight & research

Footwear Fit Data Analyst

Analyses fit-related returns by shoe model and size to improve size advice and future buys.

For your team
On the roadmap
🔍 Coming soon

Customer insight & research

Survey Insight Summariser

Summarises open-text survey responses into themes, sentiment and verbatim quotes for each audience.

For your team
On the roadmap
🔍 Coming soon

Customer insight & research

Net Promoter Driver Analysis

Links NPS scores to journeys, stores and products to show what drives promoters and detractors.

For your team
On the roadmap
🔍 Coming soon

Customer insight & research

Shopper Mission Classifier

Classifies trips into missions such as top-up, big shop or gifting to tailor ranges and layouts.

For your team
On the roadmap
🔍 Coming soon

Customer insight & research

Conversational Survey Agent

Runs short chat-based surveys with customers and adapts follow-up questions to their answers.

For customers
On the roadmap

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