Notes

Python (3.10+ recommended)

Selenium (for automated browsing)

webdriver-manager (to automatically handle browser driver installation)

BeautifulSoup4 (optional, for post-cleaning HTML)

pandas / json / logging (for saving structured data)

dotenv (to store API keys or config values if needed)

MongoDB or text storage libraries (depending on how you store data later)



Phase 1 – Weeks 1 to 4: Setup and “About Us” Section

In the first four weeks, the main goal is to build the Selenium environment, define scraping rules, and complete the “About Us” section.
During Week 1, I will begin by analyzing the entire website structure and identifying all pages under the “About Us” section, such as Who We Are, Member Directory, Leadership, Contact Staff, and MBA Store. I will create a structured list of URLs for these pages and prepare a sitemap file (e.g., urls_about_us.csv).

In Week 2, I will set up Selenium WebDriver with Chrome, configure headless mode, and build the first working script to extract visible text content. The script will handle JavaScript-heavy elements using explicit waits and scrolling actions where necessary.

In Week 3, I will focus on cleaning and structuring the scraped content by removing unwanted text like menus, footers, and advertisements. Each cleaned record will be stored with metadata such as category, subcategory, URL, and scrape date.

Finally, in Week 4, I will review the “About Us” dataset for accuracy, handle any missing pages or errors, and document the scraping approach for future sections.

Phase 2 – Weeks 5 to 8: Membership, Find a Member, and News & Events

The next four weeks will be dedicated to all member-related and event-related pages.
In Week 5, I will scrape the entire “Membership” section, including pages like Member Benefits, How to Join, Councils & Committees, Refer a Member, and the Membership Application PDF. Each page’s content will be extracted and stored as structured text.

In Week 6, I will clean the membership data, remove formatting issues, extract important details (like links or contact information), and verify completeness before saving.

In Week 7, the focus will shift to the “Find a Member” section, where I will scrape pages like Member Directory, Buyer’s Guide, and Member Login. Since some of these pages might use dynamic search forms, Selenium will be configured to handle form submissions and paginated results properly.

In Week 8, I will scrape the “News & Events” section, including Events Calendar, Become a Sponsor, Publications & Press Releases, and Blog. For this section, I will ensure the script captures multiple event posts and their detailed pages, and the resulting dataset will be stored and verified.

Phase 3 – Weeks 9 to 12: Education, Advocacy, and MBA Store

During Weeks 9 to 12, I will focus on the “Education,” “Advocacy,” and “MBA Store” sections.
In Week 9, I will scrape the full “Education” section, which includes pages such as Scholarships, Courses, Education Programs, and Resources or Webinars. I will make sure that tabbed or expandable content is fully loaded before extraction.

In Week 10, I will clean and standardize the education data by removing unnecessary elements and ensuring the text is in a consistent structure. Optionally, I may use a lightweight LLM to summarize overly long text sections for clarity.

In Week 11, the “Advocacy” section will be covered, focusing on pages such as Policies & Issues, Legislative Updates, Campaigns, and Support MBA Advocacy. Since these pages may resemble blog articles, special care will be taken to extract both text and any linked references.

In Week 12, I will scrape the “MBA Store” section, which includes Merchandise, Publications, and Digital Products. I will extract product titles, descriptions, and URLs, ensuring that even dynamically loaded product grids are captured.

Phase 4 – Week 13: Integration and Validation

In the final week, I will combine all cleaned data from every section into a single structured dataset.
I will validate that all URLs from the original sitemap were scraped successfully and handle any missed pages. Then, I will export the cleaned data into a unified JSON or MongoDB collection with consistent fields for category, subcategory, content, and metadata.

A detailed final report will be created summarizing all completed scraping tasks, encountered challenges, solutions implemented, and recommendations for future maintenance or integration with the chatbot system. This report will include folder structure, data samples, and scraping logs.