Geojobr 3min 7-8-13_v2
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The document outlines an experiment to determine user characteristics that distinguish high bill-sharing activity users from low activity users on a bill-sharing platform. It involves mining user data, defining activity tiers, using logistic regression to correlate characteristics with activity levels, and recommending areas of focus like encouraging Facebook login to increase user conversion based on the findings.
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Geojobr 3min 7-8-13_v2
- 2. Nationally 7.6% of employable US citizens are unemployed
- 3. Nationally 7.6% of employable US citizens are unemployed Over 3 million jobs available
- 10. Question: Can we encourage user behavior that will increase conversion (bill-sharing activity)?
- 11. Question: Can we encourage user behavior that will increase conversion (bill-sharing activity)? Experiment: Determine what parameters most distinguish high activity vs low activity users.
- 12. Question: Can we encourage user behavior that will increase conversion (bill-sharing activity)? Experiment: Determine what parameters most distinguish high activity vs low activity users. Goal: Recommend areas of focus that may help increase conversion.
- 13. STEP 1 Mine data for distinguishing user characteristics Example: gender, number of friends, invitation status… STEP 2 Define high activity and low activity How often does a user list an expense to be shared? What are the tiers of reporting frequency? STEP 3 Determine parameters most predictive of a high activity user Logistic regression to correlate user characteristics with activity level STEP 4 Make recommendation %50 more high than low activity users connect through FB, so try to encourage or make it easier for individuals to login through FB Experimental Procedure
- 14. Data mining Data munging Exploratory analysis, logistic regression and data visualization
- 15. Krystal St. Julien PhD candidate: Stanford Biochemistry Current Bay Area Trivia Champions Precisioncupcaking.blogspot.com
- 22. Defining demand: Demandstate = #jobs/#unemployed * date_score date_score = #list_days/#jobs #list_days = Σ (today_date – post_date[job])Upto 50 jobs
Editor's Notes
- Goal: Recommend a strategy to bring in more users that look like other “highly engaged” individuals or recommend a strategy to make “less engaged” users more engaged.
- Goal: Recommend a strategy to bring in more users that look like other “highly engaged” individuals or recommend a strategy to make “less engaged” users more engaged.
- Goal: Recommend a strategy to bring in more users that look like other “highly engaged” individuals or recommend a strategy to make “less engaged” users more engaged.