A/B Testing Impact of Google’s ConsumerSDK on our metrics
Md Aamir Sohel Ansari
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Data Analyst
Product Analyst
Python
SQL
I employed a 37.5/31.25/31.25 split: Control group (IDs ending with 7,8,9,d,e,c); Test group 1 (Live tracking with distance + traffic layer ON, IDs ending with 0,1,2,3,4); Test group 2 (Live tracking with distance + traffic layer OFF, IDs ending with a,b,f,5,6). Metrics tracked: G2N (Target), OCARA (Check).
The two-sample t-test p-value for G2N and OCARA for both traffic layer OFF and traffic layer ON exceeds alpha (0.05), indicating no significant change in G2N and OCARA values between control and test groups.
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I had to test the significance of the impact od ConsumerSDK on our G2N metrics for tier1 and tier2 cities. I employed A/B testing to determine the same.
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Rapido
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Data Analyst
Product Analyst
Python
SQL
Md Aamir Sohel Ansari
Strategic and Result Oriented Data Analyst
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Aamir2786/marketing_analytics