📊 Analyzing Cafe Rewards Offers with Looker Studio

I created a dashboard using Looker Studio to explore a dataset on coffee rewards offers. I'd like to share my approach and findings, and would love to hear your feedback!

The dataset, Cafe Rewards Offers, was provided by Maven Analytics. It contains information about customer interactions with different promotional offers, including demographics, transaction history, and offer completions.

🟢 Question 1: How many reward offers were completed, and which offers had the highest completion rate?

To answer this, I used a table that displays the characteristics of each offer alongside the number of times it was completed. Since the offers don’t have unique names, I included attributes like offer type, difficulty, duration, and channels to help distinguish them.

This required joining two tables:

• 
  Events table – contains records of completed offers


• 
  Offers table – provides characteristics of each offer

I filtered the events table to include only offer completed events and joined it with the offers table. I then used a pie chart to visualize the proportion of completions per offer type.

🧠 Insight:

Offers with the highest completion rates were discount offers that had:

• High difficulty


• Longer duration


• Were delivered via social channels
  

🟢 Question 2: How many informational offers were followed by transactions?

For this, I created a blended data source by joining two versions of the events table:

• One filtered for transactions
  


• One filtered for informational offers
  

I then displayed the result in a table, following a similar structure to the first question.

🧠 Insight:

Informational offers that led to more transactions tended to:

• Have shorter durations
  


• Be delivered through social channels rather than web

🟢 Question 3: How is customer demographics distributed?

I used three pie charts to show the distribution of:

• Age groups


• Gender


• Income levels

These charts use the customers table to display a demographic breakdown.

🧠 Insight:

The largest customer group consisted of:

• Male users


• 
  Undefined age


• Earning $50k–$80k annually

🟢 Question 4: Are there demographic patterns in offer completions?

To explore this, I blended the events table and offers table, filtering for only completed offers. Then, I used pie charts (similar to the previous question) to visualize the demographics of users who completed offers.

🧠 Insight:

Once again, the users with the highest offer completions were:

• Male


• 
  Undefined age


• Earning $50k–$80k annually

🔗 Explore the Dashboard Yourself

You can view the full dashboard here:

👉 Looker Studio Dashboard

Let me know what you think! I'm open to any suggestions on improving both the analysis and the visual design of the dashboard.