Relevate AI combines identity resolution, AI modelling, and behavioural insights for people-based marketing and lead generation. Strawberry can inspect how an audience or recommendation was assembled. It can compare the available signals with observed results, identify uncertain assumptions, and prepare a marketer’s review before a segment is activated.
01
Know what the audience model is actually assuming.
A precise-looking audience can conceal a broad inference about who a person is or what they are likely to do. Strawberry can read the visible Relevate AI configuration and results to turn that inference into a reviewable explanation for the marketer who owns the campaign.
02
Separate behavioural signal from sales certainty.
A lead score or intent indicator can help prioritise research, but it is not proof that a person is ready for a message. Strawberry can compare visible recommendations with the available response evidence and leave a validation queue rather than treating a prediction as permission.
03
Trace identity questions before they reach activation.
Identity resolution is useful when it brings fragmented customer context together, and risky when a marketer cannot see why records were connected. Strawberry can flag visible matching questions, missing context, and segments that warrant a human check before an audience is used.
04
Review new segments at the start of the working week.
A Monday review lets marketing and sales align on an audience before briefs, budgets, or outreach sequences are built around it. It also prevents a new model output from quietly becoming a shared assumption.
Relevate AI Strawberry