Can you predict which customers will leave?
A model may help prioritise accounts when there is suitable historical data, but a score needs validation against later outcomes. We do not promise a prediction accuracy or a fixed warning period. Start with clear business rules and compare a proposed model with that baseline before using it to direct customer work.
Which account data is useful?
Renewal dates, agreed product usage, open support issues and recorded customer feedback can help explain an account. Use data your business is permitted to process, resolve duplicate customer IDs and show when each signal was last updated. A missing record should remain visible as missing, rather than becoming a negative score.
Will this connect to our CRM?
The scope depends on your CRM edition, available APIs, account permissions and data quality. We can assess a one-way summary, a task queue or approved write-back. Start with a small sample and verify record matching, duplicates, permission boundaries and the response when an integration is unavailable.
Does an account score replace the customer success manager?
No. A score is a review aid. A usage decline may reflect a holiday, completed project or changed contact rather than dissatisfaction. The account owner should inspect supporting records, correct mistakes and decide whether a conversation, training session or commercial review is appropriate.
What security and hosting evidence should we ask for?
Ask for the actual providers, processing and storage regions, access roles, retention settings and subprocessor terms proposed for your project. Confirm any required certifications against current evidence for the relevant service and scope. This page does not establish a Yes AI certification or an Australian-only processing architecture.
How should we measure the pilot?
Record the baseline time spent preparing account reviews, the number of useful alerts and false alarms, and outcomes after an agreed observation period. Keep expansions, contractions and cancellations separate. Compare like-for-like accounts and include staff review time and software costs before attributing an improvement to the workflow.