Introduction to Machine Learning for SEO
- Marketing and SEO Implementations of fuzzy matching
- Practical: Rewrite titles and meta descriptions
- Practical: Clustering images based on color
SEO & Marketing Metrics
In shortThe share of impressions that result in a click (clicks divided by impressions). In SEO it shows how often searchers choose your result when they see it.
Click-through rate (CTR) is the percentage of times a result, ad or link is clicked out of the times it was shown. In organic search it is calculated as clicks divided by impressions, and Search Console reports it per query, page, country and device. It tells you how attractive and relevant your result looks to people who see it in the results.
If a page appears 2,000 times in search results for a query and gets 100 clicks, its CTR for that query is 5%. CTR is shaped by position (higher results get more clicks), by what else is on the page (ads, AI Overviews, rich results, People Also Ask), and by how well your title and snippet match the searcher’s intent.
Search engines also learn from clicks. Google’s query augmentation patents describe using implicit signals such as click-through rate and long clicks, alongside explicit feedback, to judge which augmented queries perform well. MLforSEO treats CTR as one of several implicit user feedback signals rather than a ranking lever on its own.
A recipe page ranks in position 3 for a high-volume query but has a lower CTR than pages at positions 4 and 5 on similar queries. The snippet shows a generic title, while competitors show ratings and cooking times as rich results. Adding Recipe structured data and a title that includes the cooking time addresses both gaps.