Next-level personalization in loan comparison
How can AI optimise and time transactional messages — application status updates, offers, reminders — so they adapt in real time to different customer behaviours and needs, maximising conversion and customer experience without message fatigue? The right message, at the right time, in the right channel, to the right customer. You get a real dataset (anonymised messages + emails + conversions) and ship a Dockerised solution + a short doc explaining your thinking.
How can AI optimise and time transactional messages — application status updates, offers, reminders — so they adapt in real time to different customer behaviours and needs, maximising conversion and customer experience without message fatigue? The right message, at the right time, in the right channel, to the right customer. You get a real dataset (anonymised messages + emails + conversions) and ship a Dockerised solution + a short doc explaining your thinking.
Datasets, full brief and submission format live on the public Notion hub. Read it carefully before you start.
| Criterion | Max |
|---|---|
Conversion value Estimated lift on the metrics that matter (apply → offers → accept → paid out). | 10 |
Behaviour match How well the proposed messaging mirrors real customer behaviour + timing. | 10 |
Implementability Plausibly slots into Sortter's existing systems via API / integration guide. | 10 |
Upgradeability Stays useful as customer behaviour and market shift over time. | 5 |
The deadline is strict at Sun 15:00. Submissions go by email to the partner — clicking Submit via email opens a pre-filled draft from your client.