AdInsights Dashboard

This project is a web-based dashboard that provides interactive visualizations and analysis of digital advertising performance data. It uses a dataset of 10,000 rows, containing ad campaign metrics to display key insights into click-through rates (CTR), conversion rates, and other relevant metrics. Users can filter the data by gender, ad type, and location to explore specific segments of the audience.

Features

• Interactive Visualizations: Uses Plotly to create dynamic charts and graphs.
• Data Filtering: Allows users to filter data by gender, ad type, and location.
• Outlier Handling: Implements basic outlier removal for age and income data.
• Key Performance Metrics: Displays key ad performance metrics (CTR, conversion rate, etc.).

Technologies Used

• Python
• Pandas
• Plotly
• Flask
• HTML/CSS

Setup

1. Clone the repository:

   git clone [repository_url]

2. Navigate to the project directory:

   cd ad_dashboard

3. Install the required libraries:

   pip install -r requirements.txt

4. Download the dataset:

   • The dataset, "Dataset: Online Advertisement Click-Through Rates", is available from Mendeley Data.
   • Download it from: doi: 10.17632/wrvjmdtjd9.1
   • Place the downloaded Dataset_Ads.csv file in the project's root directory.

5. Run the application:

   python app.py

6. Open your browser and go to http://127.0.0.1:5000/.

Dataset

This project uses the "Dataset: Online Advertisement Click-Through Rates" dataset, containing 10,000 rows.

Citation:

Tawade, Jagadish; Kulkarni, Nitiraj (2024), “Dataset: Online Advertisement Click-Through Rates”, Mendeley Data, V1, doi: 10.17632/wrvjmdtjd9.1

Future Enhancements

• Implement more advanced filtering options.
• Add predictive analytics features.
• Deploy the application to a cloud platform (e.g., Google Cloud Platform).
• Add more metrics and visualizations.