Customer Analytics Agent
Which customers are worth the most, and which are about to leave.
A Customer Analytics Agent answers natural-language questions about customer value and segmentation — lifetime value, recency and frequency, who is at risk — from a governed dataset that refreshes daily. Marketing stops guessing which segment to target.

The job to be done
“I know we have the data to tell me who is about to churn. I do not know how to get at it without booking an analyst for a week.”
Before
Segmentation done once a quarter, in a spreadsheet, by whoever had time.
After
Live customer segments anyone in marketing can interrogate directly.
How it works
- 1
Reads the customer base
Works from a governed, permission-enforced dataset covering the full customer base, refreshed daily.
- 2
Scores value and risk
Applies lifetime value and recency-frequency segmentation.
- 3
Answers in plain language
"Which high-value customers have gone quiet this month?" returns a list, not a report request.
- 4
Feeds the campaign
Segments flow into the marketing platform rather than being re-keyed.
Where this one was built
Built and live for an ASX-listed telco across a customer base of roughly fifty thousand, refreshed daily.
Questions
What does a Customer Analytics Agent do?
It answers plain-language questions about customer value and behaviour — lifetime value, recency and frequency segmentation, who has gone quiet — from a governed dataset that refreshes daily. Marketing can interrogate the customer base directly instead of booking an analyst.
Do we need a data warehouse first?
You need a governed, trustworthy source of customer data — in practice, a data warehouse. This matters more than it sounds: an agent sitting on unreliable data does not fail loudly, it simply answers wrong, quickly and confidently. We build the foundation as well as the agent.
Want this one running in your business?
We will scope it against your systems, build it, and teach your team to build the next one themselves.