SHREYANS SHAH

Projects:

• Marketing Mix model

Built marketing mix model for various Automobile and FMCG clients to decompose the sales/dealer traffic/brand equity into different media activities. Based on the model, derive the effectiveness and efficiency of media activities.

Technologies: SPSS,SQL,SAS,Excel

Model : Multiple linear regression, Saturation curves

Impact: Optimized media plan for upcoming year based on media activities performance and their saturation level

PROJECTS

• Frequency booster

Proposition is to boost the frequency of a customer for a particular offer product. Methodology developed locates the customers who have been engaged with the offer product but not loyal to the product

Technologies: Python, Pyspark, Excel

Model and Statistic: LightGBM, Hypothesis Testing, AB Test

Impact: Drives great uplifts for suppliers, they offered to fund the proposition completely

• Uplift Attribution

Applied ANCOVA technique to derive statistically significant uplift from the AB test setup which was in place for different media customer engagement propositions.

Technologies: Python, Pyspark, Excel

Statistics: ANCOVA

Impact: Improved the probability of getting significant results from earlier rule-based technique

• Relevant Coupon

Built a rule-based model to target customers with relevant coupons based on their purchase behavior on a monthly basis based to increase engagement with the retailer.

Technologies: Python, Pyspark, Excel

Model and Statistics: RFM model, AB test

Impact: Improved the probability and engagement for retailer