seo-drift

You can detect SEO drift by capturing a baseline snapshot of page titles, descriptions, and schemas, then running a comparison against current metrics. This rule-based process identifies discrepancies using 17 rules with severity levels from Critical to Info to ensure on-page SEO health.

SEO drift is the unintended change of on-page elements like titles and schemas over time. Rule-based comparison detects these issues by applying 17 rules to compare current page metrics against a known good baseline, assigning severity levels from Critical to Info to flag ranking risks.

Track SEO change history by maintaining a log of page element comparisons over time. You can review this historical data to see how titles, descriptions, and schemas have drifted from their original baseline, helping identify when and where site performance issues were introduced.

Yes, this SEO analysis approach uses Python with BeautifulSoup for parsing page elements and Pandas for managing comparison data. It captures on-page elements like titles and schemas, using SQLAlchemy to maintain history logs for detecting site performance drift.

Yes, by creating a baseline snapshot of SEO-critical elements, it tracks schema and meta description changes effectively. The rule-based comparison evaluates current pages against the known good baseline, making it suitable for content managers monitoring site health across many pages.