2024: Week 8 - Prep Air Loyalty

Challenge by: Jenny Martin

For this week's challenge, Prep Air have asked for some What If? Analysis. They're considering 2 different systems for rewarding customer loyalty and want to understand how that might impact cost and how many customers might benefit from the program.

Inputs

  1. Prep Air Customer Details - the team were able to add additional information to Week 5's input 

  2. Prep Air Loyalty schemes 

  3. Prep Air Loyalty Costings 

Requirements

  • Input the data
  • To be part of either Prep Air Loyalty Scheme, Customers must have flown in the last year (on or after 21st February 2023)
  • Create a parameter so that the number of flights a customer has taken is either bucketed into groups of 5 or groups to 10
    • e.g. if the parameter selected is 5, the groupings will be 1-4, 5-9 etc
    • if the parameter selected is 10, the groupings will be 1-9, 10-19 etc
  • Create a field to categorize customers based on the selected parameter, called Tier
  • Estimate the average number of flights a customer takes per year 
  • Filter the Prep Air Loyalty dataset to the selected parameter value
  • Join the Prep Air Loyalty to the Customer dataset in a way that each customer also experiences the benefits of lower Tiers
    • e.g. a Tier 2 customer gets all the benefits of Tier 0, Tier 1 and Tier 2 
  •  Split out the Benefits and make sure that each Benefit has its own row
  • Join on the Costing dataset
  • Calculate the Yearly Cost of each Benefit
    • e.g. if the Benefit Cost is per flight then make sure to multiply it by the Avg Number of Flights that customer takes in a year
  • Total up the Yearly Cost for each Tier and count the Number of Customers in Each Tier
  • Output the data

Outputs

5 Tier Grouping Output

  • 3 fields
    • Tier
    • Year Cost
    • Number of Customers
  • 6 rows

10 Tier Grouping Output

  • 3 fields
    • Tier
    • Year Cost
    • Number of Customers
  • 3 rows
After you finish the challenge make sure to fill in the participation tracker, then share your solution on Twitter using #PreppinData and tagging @Datajedininja, @JennyMartinDS14 & @TomProwse1

You can also post your solution on the Tableau Forum where we have a Preppin' Data community page. Post your solutions and ask questions if you need any help! 

Popular posts from this blog

2023: Week 1 The Data Source Bank

Image
 Created by: Carl Allchin Welcome to a New Year of Preppin' Data. These are weekly exercises to help you learn and develop data preparation skills. We publish the challenges on a Wednesday and share a solution the following Tuesday. You can take the challenges whenever you want and we love to see your solutions. With data preparation, there is never just one way to complete the tasks so sharing your solutions will help others learn too. Share on Twitter, LinkedIn, the Tableau Forums or wherever you want to too. Tag Jenny Martin, Tom Prowse or myself or just use the #PreppinData to share your solutions.  The challenges are designed for learning Tableau Prep but we have a broad community who complete the challenges in R, Python, SQL, DBT, EasyMorph and many other tools. We love seeing people learn new tools so feel free to use whatever tools you want to complete the challenges.  A New Year means we start afresh so January's challenges will be focused on beginners. We will use dif
Read more

2023: Week 2 - International Bank Account Numbers

Image
Challenge By: Jenny Martin For week 2 of our beginner month, Data Source Bank has a requirement to construct International Bank Account Numbers (IBANs), even for Transactions taking place in the UK. We have all the information in separate fields, we just need to put it altogether in the following order: Inputs A list of the transactions, with information about the receiving bank account  A lookup table for the SWIFT Bank Codes  Requirements Input the data In the Transactions table, there is a Sort Code field which contains dashes. We need to remove these so just have a 6 digit string ( hint ) Use the SWIFT Bank Code lookup table to bring in additional information about the SWIFT code and Check Digits of the receiving bank account ( hint ) Add a field for the Country Code ( hint ) Hint: all these transactions take place in the UK so the Country Code should be GB Create the IBAN as above ( hint ) Hint: watch out for trying to combine sting fields with numeric fields - check data types Re
Read more

How to...Handle Free Text

Image
Free isn't always a good thing. In data, Free text is the example to state when proving that statements correct. However, lots of benefit can be gained from understanding data that has been entered in Free Text fields. What do we mean by Free Text? Free Text is the string based data that comes from allowing people to type answers in to systems and forms. The resulting data is normally stored within one column, with one answer per cell. As Free Text means the answer could be anything, this is what you get - absolutely anything. From expletives to slang, the words you will find in the data may be a challenge to interpret but the text is the closest way to collect the voice of your customer / employee. The Free Text field is likely to contain long, rambling sentences that can simply be analysed. If you count these fields, you are likely to have one of each entry each. Therefore, simply counting the entries will not provide anything meaningful to your analysis. The value is in
Read more