In4mation Insights Coding Challenge

Ming Zhong
2019/10/28

Variables of Interest:

  • Expect_Price: survey price that one people want to pay
  • Max_Price: Max price that people is willin gto pay
  • Recommend: Whether people will recommend to purchase
  • Likely_to_buy: Whether people is going to buy
  • Rating: Rating of the product
  • Use_occassion: number of times using the product within one day
  • Age, Gender, Ethinicity: Demographical Features

Purpose of Study

  • Explain the patterns of use
  • Including but not limited to a focus on the likelihood to buy measure

Descriptive Statistics(Check the Design of the Test)

  • Gender
Var1 Freq
Female 48
Male 52
  • Ethnicity
Var1 Freq
Hispanic 35
Non-Hispanic Black alone 17
Non-Hispanic Other 22
Non-Hispanic White alone 26

Descriptive Statistics(Check the Design of the Test)

  • Age Distribution
Var1 Freq
(18.9,30.8] 66
(30.8,42.6] 62
(42.6,54.4] 28
(54.4,66.2] 24
(66.2,78.1] 20

For ethnicity and age, the number of count in each cell is not the same.

Descriptive Statistics(Product A and B)

  • Product Tested in two Session
Var1 Freq
A 100
B 100
  • Average Measurment for Product A and B
Product avg_Use_occassions avg_Expect_Price avg_Max_Price avg_Rating Recommend Likely
A 20.87883 3.532609 8.577778 3.841500 48 42
B 26.82733 4.571429 9.461538 5.135833 53 54

In general, Product B is preferred in terms of all metrics.

Descriptive Statistics(User Profile-Age)

  • Likely to Buy

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Descriptive Statistics(User Profile-Age)

  • Recommend

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Descriptive Statistics(User Profile-Gender)

  • Likely to Buy

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Descriptive Statistics(User Profile-Gender)

  • Recommend

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Descriptive Statistics(User Profile-Ethnicity)

  • Likely to Buy

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Descriptive Statistics(User Profile-Ethnicity)

  • Recommend

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Correlations between Measures

Aggregate the data into session level(200 rows in total)

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  • Use Occassion,Rating, Expected Price and MAx_Price are positively highly correlated.

Correlations between Measures

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  • Age doesn't stand out.

Interesting Pattern