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Maven Cafe Reward Report

Tools used in this project
Maven Cafe Reward Report

Power Bi Report

About this project

Project Goal:

As a Senior Marketing Analyst, the primary objective is to leverage the sample data to identify key customer segments and provide recommendations on promotion strategies.

Data Preparation: In Power Query, I carried out data cleaning and transformation tasks, including removing duplicates, extracting, and splitting columns. Customers aged 118, with neither income nor gender information, were identified as unrealistic and treated as outliers, thus excluded from the data model. I segmented customers' ages into five groups:

  • [Young Adult] (18-34 years)
  • [Middle Age Adult] (35-49 years)
  • [Older Adult] (50-64 years)
  • [Senior] (65-79 years)
  • [Elderly] (80+ years)

Additionally, I grouped customers' annual incomes into three categories based on their value:

[Low Income] ($0-44K)

[Middle Income] ($45-84K)

[High Income] ($85K+).

Recommendation:

  1. Continue the marketing program - Launch offers targeted at the Older Adult and Senior age groups with middle and high incomes. These customers tend to have a high completion rate.
  2. Personalize offers for different customer segments to ensure they resonate with the customers' lifestyles, incomes, or preferences.
  3. Adjust the offers for the Elderly Group - This group has the highest income, average transaction value, and conversion rate, so they tend to prefer the most exclusive products. Since they are the oldest clients and prioritize their health, caffeine is generally inadvisable for them. Therefore, include exclusive caffeine-free or low-caffeine products that could be attractive to this group.
  4. Emphasize quality in offers for Older Adults and Seniors, as they are less interested in rewards compared to younger groups.
  5. Customize offers for younger age groups with low incomes to motivate them to make purchases more frequently. Utilize reward-based offers to attract Young and Middle-Age Adults, as these groups are more responsive to rewards.
  6. Encourage active purchasing and loyalty among recent members by providing them with extra discounts or exclusive rewards for new members.
  7. Segment and Reward Frequent Shoppers: Since the peak is at 5 transactions, this indicates a strong core of engaged customers. Implement a loyalty program that offers rewards or incentives when customers reach this threshold (e.g., after their 5th purchase). This could include discounts, exclusive offers, or bonus points to encourage repeat purchases and push customers to the next transaction level.
  8. Tailor offers for men to boost sales in this gender group. Rewards could be particularly attractive.
  9. Focus on promoting discounts, as this type of offer leads to higher completion rates and generates less reward value.
  10. Use as many communication channels as possible, as this approach leads to a higher conversion rate.
  11. Focus on long-term offers lasting 7 /10 days, featuring a $3 reward with a minimum spend requirement of $7 to qualify.

Additional project images

Discussion and feedback(1 comment)
comment-1877-avatar
Samuel Adanu
Samuel Adanu
3 days ago
Great Work Joanna, Congratulation for being selected among the final 5 finalist. I would like to know from you if you will be willing to explain the step-by-step process of creating this dashboard via a virtual meeting with me. I will be happy to learn how you accomplished this task. Hoping to read your response soon. Regards, Samuel
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