A custom GPT-powered assistant for internal use that integrates with multiple third-party SaaS platforms, such as Shopify and Klaviyo. It allows non-technical team members to pull and correlate real-time data from both systems using natural language queries through a single conversational interface.
E-commerce teams run their business across several platforms. Orders and customers live in Shopify, email and SMS engagement lives in Klaviyo, and answering a question that spans both usually means exporting CSV files, matching customers in a spreadsheet and hoping nothing is missed. Marketing managers wait for someone technical to pull the data, or they make decisions on gut feel because the answer takes too long to assemble.
A Shopify Klaviyo AI data assistant lets team members ask questions in plain English in Slack or a simple web page. The assistant works out which data it needs, calls the Shopify and Klaviyo APIs, combines the results and replies with the answer or a short list. A manager can ask which recent buyers of a product have not opened the latest campaign and get a usable segment in minutes instead of waiting on an export. It is read-only by default, so the assistant can report but cannot change orders or send campaigns.
A team member asks a question in a Slack channel or web chat, and the message is passed to an LLM with function definitions for the available data queries.
The LLM decides which functions to call, such as Shopify orders by product and date range, and Klaviyo campaign engagement by profile.
A back-end service executes these calls with read-only API credentials, handling pagination and rate limits, and returns structured results.
Results are joined on email address or customer ID in code, not by the model, so matches are exact and the logic is testable.
The LLM summarises the answer in plain language, attaches a CSV if the list is long, and logs the query for audit and improvement.
A marketing manager at a fashion brand asks their internal Slackbot, 'Which customers who bought the 'Summer Dress' on Shopify last week have not yet opened our latest email campaign in Klaviyo?' The AI agent queries both APIs, correlates the data, and returns a list of customer names.
OpenAI Assistants API, Shopify API, Klaviyo API, REST API Integration, Slack/Web Interface
Customer names, emails and purchase histories are personal information under the Privacy Act, so limit access to staff who need it and restrict Slack channels accordingly. If lists produced by the assistant are used for marketing emails or SMS, make sure recipients have consented under the Spam Act 2003 and that unsubscribes in Klaviyo are respected. Consider where the LLM provider processes data, and send only the fields needed for each answer rather than full customer records. Log who asked for what so you can respond to access requests and investigate any misuse.
This solution requires careful evaluation of cost-benefit ratio. Consider implementation only after thorough analysis and risk assessment.
Not in the recommended setup. It uses read-only credentials so it can report on data but not change anything. Write actions like tagging customers or creating segments can be added later with explicit confirmation steps, but starting read-only keeps the risk low while the team builds trust.
Yes. Each data source is added as a set of functions the LLM can call. Common additions are Google Analytics, a helpdesk such as Gorgias or Zendesk, and accounting data from Xero. Each new source needs its own credentials, testing and thought about which fields are safe to expose.
Numbers come directly from the APIs and matching is done in code, so accuracy depends mainly on whether the question was interpreted correctly. Showing the filters used with each answer lets users spot a misread date range or product name and ask again with a clearer question.
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