Click-bait

A case study in digital data analytics. Particularly product analysis, user behaviour and campaign analysis.

Campaign analysis is almost everywhere in the data world, especially in marketing, digital, UX and retail industries - and being able to analyse views, clicks and other digital behaviour is a critical part of a data analyst's skillset.

Some questions I investigated include:

User behaviour

• Number of users
• Number of unique visits by all users per month
• How many times was each product viewed?
• Number of events for each event type?
• Percentage of visits which have a purchase event?
• Percentage of visits which view the checkout page but do not have a purchase event?
• Top 3 pages by number of views
• Number of views and cart adds for each product category?

Product funnel analysis

• Top 3 products by purchases
• Average conversion rate from view to cart add?
• Average conversion rate from cart add to purchase?
• How many times was each product added to cart?
• How many times was each product added to a cart but not purchased (abandoned)?
• How many times was each product purchased?

Campaign analysis

• Identify users who have received impressions during each campaign period and comparing each metric with other users who did not have an impression event
• Does clicking on an impression lead to higher purchase rates?
• What is the uplift in purchase rate when comparing users who click on a campaign impression versus users who do not receive an impression? What if we compare them with users who just an impression but do not click?
• What metrics can you use to quantify the success or failure of each campaign compared to eachother?

Report

Included below is a single page infographic detailing some important insights from my analysis.

Tools used:

• PostgreSQL (Data cleaning, exploratory data analysis)
• Excel (Report creation)
• MS Word (Infographic)