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This module enables the user to: •
define which metric to optimize (average basket, conversion vs impression...) and score the entire database of Weborama against this parameter and then arbitrate, when selecting a target, between impact (% of internet users exposed) and expected performance (performance index)
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extend a target audience by targeting customers in Weborama’s database that have a very similar profile than the customers who converted to a specific campaign (= look-alike audience)
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understand which parameters drive the most value for a campaign (predictive segmentation tree).
Steps
1. cClone creation
Options to be set
Positive event, Negative event (Universe)
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cClone Mode, Clusters Only, Versioned profile
Algorithm parameters
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2. Check and modify the status of a c-clone
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3. Select the audience to target vs. scoring performance
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4. Check the key variables that predict performance
5. Save the audience
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