Northbeam

What Stevin gets out of Northbeam

Northbeam looks beyond last-click: with multi-touch attribution and machine learning it tries to weigh the contribution of every touchpoint in the customer journey, down to creative level. For e-commerce brands that understand the last tap is not the whole story, that gives a richer picture than the standard reporting. The caveat is that multi-touch models make assumptions about how value gets spread across touchpoints, and that split is a choice, not a measurement. Teams get stuck there: they treat the assigned value as fact and steer hard on it. Stevin uses Northbeam's granular attribution to read creative-level performance and links it to your broader cross-validation, so you do not just learn that a channel works, but which hook in which audience adds the most value. Every recommendation with budget impact goes past the consultant first.

What you pair it with

Northbeam gives you attribution fine enough to steer creative choices with, but it stays a model with its own way of splitting value across the touchpoints. Count on laying the results next to other measurements and not treating it as the only truth, however convincing the detail looks. The gain is in granularity plus control: the detail that backs a creative choice, weighed against a second source. Without that cross-check you optimize your creatives on a split the model chose, not on what demonstrably brought the revenue.

Common mistakes

• →Treating the assigned value as fact while the split is a choice.
• →Steering hard on a model without laying it next to a second measurement.
• →Optimizing creatives on a split the model chose.
• →Confusing granularity with certainty: fine detail is not yet proof.