Hi all! We have used lead scoring for some time (all be it, not very well) I’ve recently created sections splitting our sales leads and talent leads to give us a more accurate score of each record type. I have a few questions:
1) does the AI model look at all leads that are converted, or all leads that go on to be closed opportunities as the data set that scores the leads.
2) is there a way to apply more weighting to certain fields manually or do we not have control over that. I.e for us, someone’s “Right to work” is more important that what their university that they have been to.
3) finally has anyone got any recommendations on how to include newly created fields in the scoring model. I.e back fill that data with converted leads or closed opps through data loader.
Bit of a long one, just trying to get my head around it, thanks!
@Matthew Gardner with the latest einstein lead scoring model i believe you can only define which all core fields should be part of evaluation.
as i understand, weightage of it will be determined by the model based on volume of data per field OR adoption of that field with data.
and if you plan to add a newly created field to the model.. ensure it has sufficient data .. else.. model will take time to show good scoring.. depending on how many records has data entered for the newly created field
