Dividing a video into labeled sections so viewers can navigate directly to the content they need.
Video chaptering is the practice of dividing a video into named, navigable sections — like a table of contents for video. Instead of scrubbing through a 30-minute recording to find the part about pricing, a viewer can click directly on the "Pricing" chapter and jump straight there. It is the difference between flipping through a textbook page by page and using the table of contents to go directly to chapter 7.
Chapters are defined as a list of timestamps and labels associated with a video. The player displays these as markers on the timeline and often as a clickable list. When a viewer clicks a chapter, the player seeks to that timestamp.
Chapters can be created manually (a human watches the video and notes key timestamps) or automatically using AI that analyzes the audio transcript and visual changes to identify topic boundaries. Manual chaptering is more precise but time-consuming; automatic chaptering scales to large video libraries without human effort.
Chapters also have SEO implications. Search engines can use chapter data to create "key moments" in video search results, allowing users to jump directly into the relevant section from the search results page. This increases click-through rates because searchers can see that the video addresses their specific question.
Longer videos benefit enormously from chaptering. Training videos, webinar recordings, town halls, and product tutorials often contain 20 to 60 minutes of content, but individual viewers typically need only a specific section. Without chapters, viewers either scrub impatiently (and often give up) or watch content they do not need. With chapters, they find what they need immediately, which improves satisfaction and completion of the relevant section.
For businesses, chapters increase the utility of every video in your library. A single 45-minute webinar recording becomes five or six individually addressable pieces of content.
host.video automatically generates chapters for every upload using AI analysis of the content. No manual timestamp entry required — upload a video and chapters appear in the player, ready for viewers to navigate.