Online User Acquisition

Case 1

Client: One of the largest job portals in the world

Opportunity: Predict profit propensity of resumes to optimize online acquisition / marketing of resumes and resume search

Solution: 

  • Define the key variables driving revenue and profit: compensation and propensity to get a job
  • Develop a predictive model for action taken by recruiters based on details in resume
  • Use segmented linear regression model for predicting views from resume details e.g. work experience, industry, compensation, functional area etc.
  • Train and test the model on millions of records
  • Develop a score based on propensity to be viewed for easier understanding and scaling
  • Implemented the model in search and online advertising

Result

  • 125% increase in resume views leading to similar increase in revenue and ~220% increase in profits
  • 140% increase in resume modification to increase the score driving a virtuous cycle

 

Case 2

Client: One of the largest job portals in the world

Opportunity: Target customers for value added services of resume creation and modification

Solution: 

  • Determine the important variables to predict propensity to buy for domestic and international customers
  • Assign weights of the variables for the predictive model for buying propensity using multivariate linear regression models
  • Calculate bias for different values of the variables metropolitan areas, roles, compensation, years of experience, industry and roles
  • Train and test the model proving its effectiveness
  • Finalize the calling list and implement it in the sales channel

Result:

  • Doubled the revenue to $30 MM USD in a year for the value added service