Website Performance Analysis

LINK TO GITHUB

https://github.com/franklintheanalyst1/franklintheanalyst1/blob/main/MY%20POWERBIPROJECT.pbit

TOOL USED

Power Bi

SOURCE ATTRIBUTION

Shahriar's Sight Academy[Udemy: Data Analysis Career Path; 72 days of Data Analysis Bootcamp]

INTRODUCTION

In today's digital age, understanding website performance is crucial for optimizing user experience and increasing conversion rates. Analyzing key metrics such as page views, session duration, bounce rate, and conversion rate can provide valuable insights into user behavior and website efficiency. This project aims to create an interactive and insightful dashboard using Power BI to visualize website performance metrics.

BACKGROUND & MOTIVATION

The dataset contains different visitors to a specific website, analyzing their user behaviors which would help in optimizing the website performance, user experience and boost conversion rates. I am excited to use Power Bi in creating an insightful dashboard on this project.

DATA COLLECTION

The dataset contains 5870 visitors . Key metrics to analyze include page views, session duration, bounce rate, conversion rate, visitor type, exit pages, traffic source and location.

DATASET LIMITATION

• Convert the variables Bounce_Rate and Conversion_Rate into percentage format and reduce the decimal points to zero.

• Assign the data category "City" for the variable Location.

ANALYSIS

Data Preparation

• Download the dataset from the resources section.

• Load the website_performance_analytics.csv dataset into Power BI.

• Convert the variables Bounce_Rate and Conversion_Rate into percentage format and reduce the decimal points to zero.

• Assign the data category "City" for the variable Location.

Dashboard Creation

• Assign the title “Website Performance Dashboard”.

• Use the variable Exit_Page as the key filter within the title bar.

• Assign KPI cards for the variables Page_Views, Session_Duration, Bounce_Rate, and Conversion_Rate. Summarize the data values as average values.

Create the following visuals:

• Two donut charts to show average Bounce_Rate and Conversion_Rate by Visitor_Type separately.

• A bar chart showing average Conversion_Rate by Traffic_Source.

• A map chart showing average Conversion_Rate by Location.

• A table chart with the columns Visitor_ID, Page_Views, Session_Duration, and Conversion_Rate. Summarize Page_Views, Session_Duration, and Conversion_Rate by their average values. Sort Conversion_Rate values in descending format. Include cell elements within all the columns except Visitor_ID. Filter the top 100 visitors by average Conversion_Rate.

RESULTS

• KPIs include 5 average page views, 296 seconds average session duration, 49.7% average bounce rate and 5.13% average conversion rate.

• For average bounce rate, there were 50.75% returning visitors and 49.25% new visitors.

• For average conversion rate, there were 49.76% returning visitors and 50.24% new visitors.

• For average session duration by traffic source, the highest was Organic, followed by Direct traffic, Social media and Referral traffic in that order.

CONCLUSION

This comprehensive dashboard using Power Bi provides a clear overview of website performance metrics. This dashboard will help in identifying trends, understanding user behavior, and making data-driven decisions to optimize website performance.

REFERENCES

1. Shahriar's Sight Academy[Udemy: Data Analysis Career Path; 72 days of Data Analysis Bootcamp]

2. Official Microsoft Power BI documentation for best practices and tutorials.

   - Reference: [Power BI Documentation](https://docs.microsoft.com/en-us/power-bi/)

3. Understand key performance indicators (KPIs) for website analysis, such as bounce rate, average session duration, and conversion rate.

   - Reference: "Measuring the User Experience" by Tom Tullis and Albert Albert.