This is a Power BI project on marketing analysis of an imaginary online retail business call Shop Easy.
Shop Easy is facing reduced customer engagement and conversion rates since January 2024. They need help to conduct a detailed analysis and identify areas for improvement in their marketing strategies.
Disclaimer: All datasets and reports do not represent any company, institution or country, but just a dummy dataset to demonstrate capabilities of Power BI.
- What is the current state of the decline in customer engagement and conversion rates over the observed period?
- Which areas can be improved to enhance customer engagement and conversion rates?
- What insights can be drawn from customer reviews?
ShopEasy's database structure as seen below consists of 6 tables: customers, products, geography, customer_journey, customer_reviews, engagement_data. Data is assumed for a 3 years period from 2023 to 2025.
- SQL: ETL, data cleaning
- Python: sentiment analysis
- Power BI: visualizations
After processing the necessary data, the data model consists of 3 fact tables and 3 dimension tables as shown below. The dimension tables are all joined to fact tables with a one-to-many relationship.
The report comprises 3 pages:
- Customer Engagement
- Conversion Rate
- Customer Reviews
You can interact with the report here
- A consistent decline in both the number of views and the likes-to-views ratio was observed from January 2024 to December 2025.
- The distribution of views across the three content types—Blog (34.7%), Social Media (33.2%), and Video (32.1%)—was relatively balanced. However, the Blog category exhibited a sharper decline in views compared to the other two content types.
- The likes-to-views conversion funnel experienced a significant drop, starting at 3.75% in January 2024 and steadily decreasing to only 0.01% by December 2025, with a steep downward trend throughout the period.
- The average conversion rate was 8.52%, with significant fluctuations month-to-month throughout the period. A consistent pattern emerged in both years, where conversion rates peaked in September (16% in 2024, 15.15% in 2025) and hit their lowest in November (5.08% in 2024, 4.48% in 2025).
- When categorizing products by price: high-priced (> $200), mid-priced ($50–$200), and low-priced (< $50), the high-priced group consistently saw the highest number of purchases.
- Interestingly, products with the highest conversion rates—Surfboard (16.44%), Ski Boots (13.11%), Hockey Stick (11.67%), and Baseball Glove (11.29%)—belonged to the category with lower view counts.
- Over the course of two years, there were 923 reviews with an average rating of 3.67 on a scale of 1 to 5.
- Sentiment analysis of the reviews reveals that the majority of positive reviews were associated with higher ratings, while negative reviews, linked to lower ratings, slightly outnumbered neutral reviews, which generally had mid-range ratings.
- Among the positive reviews, customers aged 48 and above contributed the most, particularly at the 4-star rating level.
- The top products with the highest conversion rates did not appear among those with the highest ratings. Notably, the Surfboard, which had the highest conversion rate, received the lowest rating among all products.
Marketing efforts face significant challenges in both the number of views and the likes-to-views ratio. I recommend the following actions:
- Increase advertising and enhance SEO strategies to reach a broader audience of potential customers.
- Research trending content to boost engagement and improve the likes-to-views ratio.
To improve conversion rates, the following strategies are proposed:
- High-priced products (>$200) show strong potential and should become a key focus for marketing investment.
- The customer segment aged 48 and above shows the highest number of positive reviews, suggesting the need for targeted campaigns to further engage this group. Additionally, reviews from younger age groups should be analyzed to create more appealing content for them.
- Products with high conversion rates are not currently attracting high views or ratings. Focus on increasing engagement with these products and gathering customer feedback to improve their ratings.