總結

使用 pandas 分析行銷活動

Jill Rosok

Data Scientist

資料集

marketing = pd.read_csv('marketing.csv')
print(marketing.head())

      user_id date_served    channel          variant  conv  \
0  a100000029  2018-01-01  House Ads  personalization  True   
1  a100000030  2018-01-01  House Ads  personalization  True   
2  a100000031  2018-01-01  House Ads  personalization  True   
3  a100000032  2018-01-01  House Ads  personalization  True   
4  a100000033  2018-01-01  House Ads  personalization  True   

  language_displayed language_preferred    age_group  
0            English            English   0-18 years  
1            English            English  19-24 years  
2            English            English  24-30 years  
3            English            English  30-36 years  
4            English            English  36-45 years

前處理

特徵工程
修正資料中的錯誤

行銷指標

$$ \text{Conversion rate} = \frac{\text{Number of people who convert}}{\text{Total number of people who we market to}} $$

$$ \text{Retention rate} = \frac{\text{Number of people who remain subscribed}}{\text{Total number of people who converted}} $$

顧客分群

marketing.groupby(['channel', 'age_group'])\
                                ['user_id'].count()

轉換率下滑？

house_ads = marketing[marketing['channel'] == 'House Ads']

language = conversion_rate(house_ads, 
                           ['date_served', 
                            'language_displayed'])

你分析了一個 A/B 測試

提升率（Lift）
t 檢定

祝你好運！

使用 pandas 分析行銷活動