Datasets Comparison
Kansas City and Las Vegas
The scope
Complete an in-depth analysis of the website’s data as provided. Create a dashboard and explain the results using a minimum of 3 data points (measures) and three cross-references (dimension) points (ie. Entrance rate, exit rate, page and bounce rate, time spent on the page).
Drawing on a competitive website, pick a different city’s data set, and compare similar data points. An example of this would be picking a city with a similar population size in similar geography (east coast vs. west coast)
You are required to explain why the results are the way they are and make recommendations to either fix/enhance key parts of the website in order to improve performance.
Datasets (1) Kansas City (2) Las Vegas
Deliverables
Proof of Analysis
All the rationale used to develop the assignment and to perform the analysis methodology.
Client Report Presentation
A brief summary of what was done analytically to the client’s data set to prep it for analysis.
Present comparison analysis from similar city selected and summarize the results in a Dashboard format, making it clear what the opportunities for improvement are (Top 3).
Based on your Top 3 findings, present recommendations that will improve your client’s web site performance.
Dataset#1 — Kansas City
Understanding the data
Data volume: Approx. 321,886 records (Feb 2014 — Oct 2015)
Fields in Data
•Row Ident — Primary Key (PK) 1- 321,886 (the same number of fields)
•Page Title — the name of the webpage
•Month — month description
•Year — year description
•Year Month — concatenate information (year + month)
•PageViews — number of pageviews (not unique)
•Unique Pageviews — number of pageviews (unique user)
•Average Time on Page — the average amount of time all users spend on a single page
•Entrances — shows how many users began their session with that page
•Bounce Rate — the percentage of users who landed on a page and immediately left
•Exit Rate — the percentage of users who left the website from that page
•Search Exit Rate — the percentage of users who left the website from that page
Descriptive Analysis
Dataset#2 — Las Vegas
Understanding the data
Data volume: Approx. 37,466 records (Jan 2015 — Oct 2019)
Fields in Data
•Page_Title — the name of the webpage
•Pageviews — number of pageviews (not unique)
•Unique_Pageviews — number of pageviews (unique user)
•Avg__Time_on_Page — the average amount of time all users spend on a single page
•Entrances — shows how many users began their session with that page
•Bounce_Rate — the percentage of users who landed on a page and immediately left
•F__Exit — the percentage of users who left the website from that page
•Month_Begininng — Month of the observations
•ObjectId — Primary Key
X! — DATA CLEANING
•Column Month_Beginning — Transformed in date — were removed time info 00:00:00
- Column Avg__Time — value “<00:00:01” removed
Analysis Process
Comparison Analysis // Time Series
Comparison Analysis (1)
Comparison Analysis (2)
Comparison Analysis (3)
Comparison Analysis (4)
Top Findings (1)
Top Findings (2)
Challenges
References
•United States Census Bureau
https://www.census.gov/glossary/#term_Populationestimates
•Learning hub website — Devin Pickell (G2 Crowd) — March 2020
https://learn.g2.com/data-analysis-process
•Pageviews vs Unique Pageviews
https://help.scribblelive.com/hc/en-us/articles/213583643-Pageviews-vs-Unique-Pageviews
•Bounce rate definition
https://en.wikipedia.org/wiki/Bounce_rate
•Google Analytics Help — Bounce Rate
https://support.google.com/analytics/answer/1009409?hl=en
•Benchmarking Average Session Duration: What it Means and How to Improve It
https://databox.com/average-session-duration-benchmark
Thanks! ;-)
