Few catches around Audience Manager Models.
https://experienceleague.adobe.com/docs/audience-manager/user-guide/features/algorithmic-models/look-alike-modeling/understanding-models.html?lang=en
A few thousand users should be enough to run the model on, given that there is significant trait overlap between the baseline population and the population in the selected data sources. Look-Alike Modeling produces more accurate results, the larger the baseline is.
Trait weight scale is a percentage that runs from 0% to 100%. Traits ranked closer to 100% means they’re more like the audience in your baseline population. TraitWeight ranks newly discovered traits in order of influence or desirability.
As stated above, a few thousand users should be enough to run the model on, given that there is significant trait overlap between the baseline population and the population in the selected data sources.
Use data sources which have at least some overlap with your baseline trait/segment, but at the same time bring in additional users. You should also consider the cost associated with each data feed. Cost and pricing models vary among data providers in Audience Marketplace.
Once the model run has completed you can start creating your traits and segments.
Please go through the https://experienceleague.adobe.com/docs/audience-manager/user-guide/features/algorithmic-models/look-alike-modeling/understanding-models.html?lang=en link for point 10 & 11 and let us know if you have any specific questions/issues which we may assist you with in any of the models.
Currently, you can create up to 20 algorithmic models and 50 algorithmic traits. The model retrains once every 8 days, along with refreshing the algorithmic trait population.