Let's understand how the info you generate searching for a product / service can be used for a "LEAD SCORING" model. Results could feed your CRM tool giving a better direction to your sales team.
For this work I will treat the output decision as a classification problem.
Steps:
>> feature selection
>> split dataset
>> data engineering
categorical variables >> dummy variables
numerical variables >> scaled variables
>> train model (Radom Forest Classifier)
>> feature importance rank
TOP 3 most important variables by index
Variable: total time spent on website: 0.7
Variable: totalvisits: 0.1
Variable: lead origin: 0.09
Check code here >>
#businessanalytics #dataengineering #datascience #machinelearning #analytics #marketing #CRM #sales #salesmanagement
image credit >> https://lnkd.in/eJgjj6n
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