Maven Fuzzy Factory Data analysis using MySQL and visualize by Tableau.
Six tables are:
Orders: Store the purchases that customers are placing.
Order_items: Various orders that customers could purchases more than items.
Order_item_refunds: When customers are complaining and are issued a refund.
Products: Products name.
Website_page_views: Log of page view that a user saw when they were on eCommerce website.
Website_sessions: Where our traffic is coming from and traffic sources.
Before jumping into the project, I would like to briefly cover some web/digital marketing buzzwords :-
UTM parameters: Are small pieces of code that are added to the end of a URL used to track the source of the traffic
By tracking them, businesses can see which of their paid marketing campaigns are most effective.
They can also see how different traffic sources and campaigns are performing in terms of website activity and conversions.
------------- ------------------------------------------------------------------------- -------------------------
| utm_source | Identifies which site sent the traffic and is a required parameter. | utm_source=google |
| ------------| ----------------------------------------------------------------------- | ------------------------|
| utm_campaign| Identifies a specific product promotion or strategic campaign. | utm_campaign=spring_sale|
| ------------|-------------------------------------------------------------------------|-------------------------|
| utm_content | Identifies what specifically was clicked to bring the user to the site, | utm_content=logolink or |
| | such as a banner ad or a text link. It is often used for A/B testing | utm_content=textlink |
| | and content-targeted ads. | |
------------- ------------------------------------------------------------------------- -------------------------
Traffic Sources Analysis
Website Performance Analysis
Channel Portfolio Management
Business Patterns and Seasonality
Product-Level Analysis
User-Level Analysis
Data Driven Report
Key Tables : website_sessions, orders
- Find the Top Traffic Sources
- Traffic Source Conversion Rates
- Bid optimization based on the device type
Key Tables : website_sessions, website_pageviews
- Analyzing Top Referral Sources & Website Pages & Entry Pages
- Analyzing Bounce Rates
- Building Conversion Funnels
Key Tables : website_sessions, orders
- Analyzing Channel Portfolio
- Comparing Channel Characteristics
- Cross Channel Bid Optimization
- Impact of Bid Changes
- Analyzing Free Channels
Key Tables : website_sessions, orders
- Analyzing Seasonality
- Analyzing Business Patterns
Key Tables : website_sessions, website_pageviews, orders, order_items, order_item_refunds
- Product Sales Analysis
- Product Launch Sales Analysis
- Product Level Website Analysis
- Product Pathing Analysis
- Product Conversion Funnel
- Cross Sale Analysis
- Portfolio Expansion Analysis
- Quailty issues & Refunds
Key Tables : website_sessions, orders
- Analyzing Users Repeat Visit
- Analyzing Purchase Behavior (Repeat Channel, New & Repeat Conversion Rates)
Key Tables : website_sessions, website_pageviews, orders, order_items
Observation:
At the end of three years run of the businss, we can see pretty dramatic growth. When we look in the first quarter and now at about 100 times orders
Observation:
Revenue and Margin tends to increase gradually from 2012 to 2015
The company usually has the highest revenue and profit in the last quarters of a year
Session-to-Order Conversion rate, Revenue Per Session, and Revenue Per Order
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Observation:
Volume of Website sessions and orders tend to increase gradually from 2012 to 2015
Conversion rates typically range from about 0.03 to 0.9, which is between 3% and 9% of sessions converted into orders. This ratio is considered good and acceptable throughout the observation range