Solutions
Artificial Intelligence
Models and assistants applied to specific CRM decisions: who is about to leave, what to send them, when to send it, and how to draft it faster. Used where they change an outcome, and left out where they would only add a badge.
Most AI in CRM is answering a question nobody asked.
A model earns its place by changing a decision. A churn score that arrives after the customer has gone, or a subject-line generator producing copy an editor rewrites anyway, has cost more than it returned. The useful question is never "where can we add AI" — it is "which decision are we currently making badly, often, at volume".
That framing also decides the build. Predicting which customers will lapse next month is worth doing if there is a programme ready to act on the prediction. Without one, the model is a report. We would rather tell you that before building it than after.
What you get
- Propensity and churn models trained on your data, with the feature set documented and the failure modes stated plainly
- Honest evaluation: baseline comparison, holdout performance, and the point at which the model stops beating a simple rule
- Send-time and channel optimisation where the volume supports it — and a clear answer when it does not
- Content assistance wired into the tools your team already uses, drafting against your own brand and tone rather than generic output
- Retraining and monitoring: drift checks, a schedule, and an owner, because an unmonitored model degrades quietly
- The decision record — what was tried, what was rejected, and why — so a future team is not re-running the same experiments
How the work runs
- 01
Find the decision
We start from a decision made repeatedly and imperfectly, with data attached and an action available. If any of those three is missing, the project is not ready.
- 02
Beat the baseline
The first benchmark is the simple rule you would use without a model. Plenty of problems are solved well enough by recency and frequency, and finding that out is a result.
- 03
Wire it to an action
A score is only useful inside a programme. The model ships together with the automation that consumes it, never on its own.
- 04
Monitor honestly
Performance tracked against the holdout after launch, not just at training time. If it stops earning its keep, we say so.
Let's build better customer experiences.
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