Maven Cafe Rewards Challenge

Maven Rewards Challenge

Project Objectives

1. Track the overall performance of offers sent, viewed, received, and completed.

2. Analyze customer engagement with offers across demographic groups, including age, income, and gender.

3. Understand how sales trends evolve over time (e.g., over 30 days), identifying peaks and drops in offer effectiveness

4. Provide insights into customer loyalty by tracking long-term customer engagement trends and membership patterns over time.

5. Offer a high-level view of the customer base, breaking down customer distribution by age, income, and gender, which helps align marketing strategies with customer demographics.

Business Impact:

The insights from this report enable the business to:

• Optimize future marketing campaigns by tailoring offers to the right demographic groups.
• Improve customer targeting by identifying which income or age groups respond better to different types of offers.
• Enhance offer strategy based on real-time data, making adjustments to improve conversion rates and customer satisfaction.
• Understand the key drivers of offer success and ensure that resources are being directed towards the most effective marketing channels and customer segments.

1.Which Income Group Completed More Offers?

• Key Observations:
  • The $51k - $70k and $71k - $90k groups viewed and completed more offers compared to other groups, which might suggest that people in these income brackets are more engaged with offers.
  • The $90K+ group completed fewer offers than expected, which could indicate that higher-income individuals are either less interested or require different types of incentives to engage with offers.
  • The No Income group shows significant engagement with viewed and received offers.
• Actionable Insights:
  • Tailor offers more strategically based on income. For instance, larger discounts or more valuable rewards could be targeted at higher-income customers to boost completion rates.
  • Develop lower-value offers or loyalty rewards for customers in lower income brackets to sustain their engagement.

2. Which Age Group Completed More Offers?

• Key Observations:
  • The 51-65 and 35-50 age groups lead in offer interactions, with higher numbers of viewed and completed offers compared to other age groups.
  • The 18-34 group has fewer completed offers despite viewing and receiving a reasonable number. This indicates a gap between interest and conversion for younger audiences.
• Actionable Insights:
  • Younger customers (18-34) may require more personalized or dynamic offers, perhaps utilizing digital engagement strategies to increase their completion rates.
  • For the 51-65 and 35-50 groups, continue focusing on offers that cater to their preferences, such as loyalty programs, product recommendations, or reward-based incentives.

3. Customer Membership by Month

• Key Observations:
  • Membership peaks in August and remains high in October and November. This could be linked to seasonal promotions or events driving higher customer acquisition during these months.
• Actionable Insights:
  • Leverage the periods of peak engagement (like August) by launching targeted campaigns and offers. This will help further drive customer engagement when membership is already growing.

4. Customer by Year

• Key Observations:
  • There is a steady increase in customer membership, with significant growth between 2015 and 2018. The number of customers almost doubles between 2016 and 2018, indicating successful strategies during this period.
  • The growth in 2016 and 2018 stands out as a key indicator of when customer acquisition efforts were most successful.
• Actionable Insights:
  • Continue analyzing what strategies worked well during these years and replicate them or introduce similar tactics (e.g., popular offers, marketing campaigns, or partnerships).

5. Who Completed More Orders? (Gender)

• Key Observations:
  • Female customers completed slightly fewer offers than male customers.
  • There is a significant number of customers marked as "Unknown", which may affect the accuracy of gender-based targeting strategies.
• Actionable Insights:
  • Consider campaigns targeted at female customers to increase their engagement and offer completion rates.
  • For customers marked as "Unknown", improve data collection processes (e.g., gender information at sign-up) to ensure more precise segmentation and analysis.

6. Total Customer by Gender

• Key Observations:
  • The Male customer segment is larger (8484), followed by the Female segment (6129). There is a significant portion (2175) classified as Unknown.
  • The large Unknown segment could point to missing data in the customer database.

7. Total Customer by Age Group

• Key Observations:
  • The 51-65 age group represents the largest portion of the customer base (5146), followed by the 75+ group (3984) and the 35-50 group (3437).
  • The younger group (18-34) has a smaller presence (2256), suggesting lower engagement or acquisition of younger customers.
• Actionable Insights:
  • Focus efforts on acquiring and engaging younger customers, potentially through digital channels and promotions tailored to their interests.
  • Maintain or expand efforts to engage with the 51-65 age group, as they are currently the largest customer segment.

8. Total Customer by Income Group

• Key Observations:
  • The largest customer segments are in the $51k - $70k and $30k - $50k income ranges, with 5006 and 4034 customers, respectively.
  • The No Income group also represents a sizable portion of the customer base (2175), which could include students, retirees, or unemployed individuals.
• Actionable Insights:
  • Since mid-income groups ($30k - $70k) dominate the customer base, focus on designing offers that cater to their financial preferences, such as affordable rewards, loyalty points, and discounts.
  • Consider tailored offers for the No Income group, which may include promotions on essential goods or discounts to encourage continued engagement.

9. Offer Metrics (Offer Sent, Viewed, Received, Completed)

• Key Observations:
  • The number of offers completed is high compared to those received, suggesting strong engagement with offers that customers were exposed to.
  • However, there is a significant gap between offers sent (307K) and offers viewed (58K), indicating potential issues with communication channels, targeting, or offer visibility.
• Actionable Insights:
  • Improve targeting strategies or communication channels to increase the number of offers viewed.
  • Analyze the methods used for offers that were completed successfully to replicate that success across other channels.

10. Which Age Group Completed More Offers?

• Key Observations:
  • Discount offers have the highest completion rates, especially for the 35-50 and 51-65 age groups, where the completion rate is 92% and 68%, respectively.
  • Bogo offers perform best for the 51-65 and 35-50 groups (65% and 58%).
  • Younger age groups (18-34) show high completion rates for discount offers (88%), while older age groups (75+) have lower completion rates for all offers, particularly for bogo offers (40%).
• Actionable Insights:
  • Focus on discount-based offers for the 18-34 and 35-50 age groups to sustain their high engagement levels.
  • For the 75+ age group, test offers that may be more relevant, such as simpler discounts or direct rewards, as they seem less responsive to bogo offers.

11. Offer Status by Income Group

• Key Observations:
  • For higher-income groups like $90k+, the majority of offers sent (72K) resulted in high view rates (98%) and completion rates (6K completed).
  • The $71k-$90k and $51k-$70k groups have the highest completion rates across all income brackets.
  • The No Income and lower-income ($30k-$50k) groups received fewer offers and have lower completion rates.
• Actionable Insights:
  • Target higher-income groups with a larger volume of personalized offers, as they are highly responsive and complete offers at a higher rate.
  • For lower-income groups, introduce simpler offers, such as direct discounts, which may increase their engagement levels.

12. Offer Performance by Channel

• Key Observations:
  • The EMS channel had the highest number of offers sent (32K), followed by WE (13K), but this doesn't necessarily translate into the highest completion rates.
  • The WEM and WMM channels had fewer offers sent but a relatively higher completion percentage.

13. Offer Type Completion Status

• Key Observations:
  • Discount offers lead in all metrics, with 30K offers received and 17K completed, indicating strong interest and follow-through with this offer type.
  • Informational offers have the lowest completion rate, as expected since they are not direct action-based offers.
• Actionable Insights:
  • Continue prioritizing discount-based offers as the primary promotional strategy since they consistently show higher engagement and completion.
  • Informational offers should serve more as supplementary tools for customer engagement rather than a primary offer strategy.

14. Sales Trending ($) Over 30 Days

• Key Observations:
  • There are distinct spikes on days 15 (64K), 8 (51K), and 22 (78K), indicating specific days or events driving increased sales.
  • Sales dip between these peaks but remain above 40K on most days.
• Actionable Insights:
  • Investigate what specific promotions, events, or offers coincided with the spikes on days 8, 15, and 22 to replicate those strategies in future periods.
  • Maintain consistency in promotional efforts between peaks to keep sales steady on non-event days.

15 Channel Effectiveness

• Key Insights:
  • WEMS: Most effective in terms of Offer Completed, with a high number of Offer Viewed and Offer Received as well.
  • WEM: Shows similar trends but slightly lower completion rates compared to WEMS.
  • EMS: Moderate effectiveness across all metrics, with a visible drop-off between Offer Viewed and Offer Completed.
  • WE: Least effective with low numbers in all categories, indicating a lower engagement and conversion rate.

16. Reward Type Popularity

• Key Insights:
  • $5 Reward: The most popular, with 60,350 rewards sold.
  • $10 Reward: Follows closely with 70,190 rewards, indicating a strong preference for higher-value rewards.
  • $2 and $3 Rewards: Less popular, with 15,468 and 18,668 rewards sold, respectively.

17. Customer Offer Acceptance by Duration

• Key Insights:
  • Day 10: Highest completion rate (87%) with a significant number of offers sent (33,992) and completed (8,737).
  • Day 7: A close second with a completion rate of 77%, indicating a strong customer response within the first week.
  • Day 5 and 4: Lower completion rates (52% and 51%), suggesting that customers are less likely to accept offers beyond the first week.
  • Day 3 and 2: Minimal engagement with lower completion percentages, indicating that customers need more time to decide.

18. Reward Type Preference

• Key Insights:
  • $5 Reward: Highest completion rate (86%), making it the most popular and effective reward type.
  • $10 Reward: Despite high engagement in viewing (14,014) and receiving offers (15,251), the completion rate is lower (50%).
  • $2 Reward: Although it has a relatively high completion rate (83%), it has fewer total rewards completed (9,334).
  • $3 Reward: Moderate performance with a 70% completion rate, showing that mid-range rewards have a balanced appeal.

19. Rewards Trending Over 30 Days

• Key Insights:
  • Initial Spike: A noticeable spike occurs around Day 2, with 5,418 rewards distributed, followed by a drop.
  • Mid-Month Peak: Another peak is observed around Day 18, with 10,784 rewards, suggesting a promotional event or increased engagement period.
  • End-of-Month Decline: A steady decline towards the end of the month, indicating either market saturation or the end of a promotional campaign.

20. Average Day Metrics

• Key Insights:
  • Avg Day (Offer Viewed): 6.50 days, indicating that customers typically take about a week to view an offer.
  • Avg Day (Offer Completed): 7.25 days, slightly longer than the viewing period, suggesting a quick decision-making process after viewing.

Overall Report Summary:

• Offer Effectiveness by Income Group: Higher-income groups ($51k-$90k+) respond well to both bogo and discount offers, with extremely high completion rates. Lower-income groups require simpler, more accessible offers to increase engagement.

• Offer Effectiveness by Age Group: The 35-50 and 51-65 age groups are the most responsive to offers, particularly discount-based offers. Younger customers (18-34) also respond well to discounts but less so to bogo offers.

• Channel Performance: The EMS channel dominates in terms of volume, but further analysis is required to optimize its conversion rates. Channels like WEM and WMM show promise with higher offer completion.

• Offer Type: Discount offers consistently perform better than bogo or informational offers, indicating that customers are more likely to complete straightforward offers that provide clear value.

• Sales Trends: Specific days see dramatic increases in sales, which correlates with successful promotions or events. Further analysis is needed to identify and replicate the strategies used on those peak days.

• Demographics: The 51-65 age group and middle-income groups are the most active and engaged customers. However, there are opportunities to better engage younger customers and potentially provide more effective offers to high-income individuals.

• Offer Performance: Customers in the $51k - $70k income range and 51-65 age group are particularly responsive to offers, both in terms of viewing and completing offers. Younger customers show interest but are less likely to complete offers.

• Growth Opportunities: Focus on increasing engagement for female customers, customers with unknown gender, and younger demographics. Additionally, there are opportunities to refine offer strategies based on the timing of customer membership growth and seasonal engagement trends.

This dashboard effectively highlights how demographics, income, and gender impact customer engagement with offers and promotions, providing clear insights into where future marketing efforts should be focused. This dashboard provides a comprehensive view of offer performance by demographic segment and channel, offering a clear path for optimizing future campaigns and promotions.