This repository contains the practical application assignment for Module 5. Additional details are provided in this activity's Juniper Notebook.
Notebook link: https://github.com/ksolivenhub/BH-PCMLAI-Module5/blob/de536bc25e102c975dfbb53ca70b43e1b0e814d1/prompt-ksoliven-fin.ipynb
- There is a higher percentage of people not accepting Bar Coupon.
Delta is at 17.62%
- The acceptance rate of people going less than 3 times monthly is more likely than more than 3 times monthly
Acceptance rate at ~81%
- Compared to all others who accepted the Bar Coupon, those who go to Bar once (1) monthly and over the age of 25 have a significant presence in the data set
Acceptance rate at ~28%
- The acceptance rate of people who went to the Bar once (monthly) and does not have a passenger kid has a significant presence in the data set
Acceptance rate at ~48%
For this data sample, it is not affected by Age or Marital Status as the values are equal
- An observation made is that Bar > 3 does not contain most of the data sample entries
Based on this sampled data, Drivers who accepted the coupons could be hypothesized as follows:
- Bar < 3 contains most of data sample entries
- Most drivers that go to the bar less than thrice (3) monthly is more likely to accept/use the coupon
- Drivers are more likely to accept/use coupon if they have a Kid as a passenger
Core question: What are the best performing coupon groups?
- Are the coupon expiration dates effective?
- What is the best time/season to release the coupons for marketing?
- Who to send the coupons?
- This is based on the following factors:
- Income
- Marital Status
- Has Children
- Education
- Gender
- Age
- This is based on the following factors:
*Based on the sampled data and the overall results of this analysis from Q1 to Q3, the following assertions can be made:
- The Coupon types that have the best performance (based on analyzed features) are the following:
Restaurant(<20)
Coffee House
Carry out & Take away
- The
higher the Coupon validity duration
, the higher chance that consumers will accept the coupon- A likely scenario is if the expiry is too long, the acceptance rate will decrease
- The condition above most likely have an ideal threshold/range to maintain a positive acceptance rate
- There is not enough data to predict this parameter
- A likely scenario is if the expiry is too long, the acceptance rate will decrease
- The data set provided for this activity contains useful information to predict consumer behaviour in a
Sunny
weather- There is a positive correlation between temperature and coupon acceptance
- For the best performing Coupon groups, it is ideal to offer them between
10 AM to 6 PM
as a high coupon acceptance were observed Cheap Restaurants and Coffee House
have similar characteristics relative to time and temperature on a Sunny day- Visits are more frequent before noon (7AM to 10PM) on a warm temperature
- After 6 PM, visits for these parameters are also seen during the cold temperature range
Carry out & Take way
is not dependent on temperature- To maximize potential profit, any marketing campaign related to these best perfoming coupons should primarily target the following consumers:
- Age between
21-31
and50+
- Marital Status of
Single, Unmarried, and Married Partners
No Children
- It would be interesting to explore/confirm if this parameter's acceptance rate is indeed higher when driving with Kids
- Income is below
$62,500
and above$100,000
- Age between
- Consider that the following types of establishments will generate the most coupon acceptance rate and leverage this knowledge to the owner's advantage
Restaurant(<20)
Coffee House
Carry out & Take away
- Use the predicted parameters above to improve success rates of Coupon marketing campaigns
- Gather more data related to coupon acceptance in other weather/time conditions to create a full view of which businesses are running successful campaigns.
- Explore the Trip Attributes in relation with Coupon and User Attributes as this was not incorporated on this analysis.