B-roll logging is the process of reviewing raw video footage, selecting usable clips, or even adding metadata (tags, markers, etc.) to make them searchable during video editing.
The goal of b-roll footage is to supplement the main footage: the talking-head, the interview, the screen recording. And b-roll logging means you can actually find it when you need it.
For editors and creators, this is the difference between scrubbing through 3 hours of footage to find that one coffee shop shot or finding it in seconds. That’s why b-roll logging is important.
In this article, you’ll find the common workflows editors use, why they are a bottleneck, and automatic b-roll logging tools that can save several hours.
Most YouTube editors fall into 1 of 3 workflows when logging b-roll. And while they all work, they are not perfect.
The most common approach is importing footage into your video editing tool (Premiere Pro, DaVinci Resolve, or Final Cut Pro), scrubbing through the video, and cutting the clips you want directly into the timeline.
This is fast to get started, doesn’t require extra tools or prep work. But this is not actually logging. This is just editing.
So, the clips are still there with zero context until you watch them to know the content. And the next time you need a similar b-roll, you’re back to scrubbing through the same raw footage.
Other editors may prefer to transcribe the video footage if it’s in interview style and drop it into a Google Doc.
Transcription tools handle the heavy lifting, so getting the text is quick. The problem is what comes after.
Even with transcription tools, you still have to sift through text and find at what time it appears in the video. You also need to keep the whole doc tidy, so that you can find things if and when you need them.
Then there’s the folder approach with nested directories, descriptive filenames, and maybe thumbnail previews so you can visually scan what’s inside.
This b-roll organization method holds up fine when your library is small (tens of hours of footage). But after a certain point, you’ll probably spend more time babysitting the folder structure than actually editing.
Those 3 methods require a lot of time that most editors don’t have.
Manually logging 1 hour of raw footage takes multiple hours, which would be better spent on the actual edit.
And most of that work doesn’t carry over between videos, either. Everything you organized for the last video won’t help you find clips if you work on a similar video in the future.
Markers and metadata are trapped inside the project files of your video editing software. If you need a specific b-roll clip 6 months from now for a similar video, you won’t be able to search for it!
This means you have to crack open old timelines and scrub through primary footage and b-roll all over again. This wasted time managing and looking for b-roll compounds.
And every new video adds footage to the pile, making it harder and harder to find.
Fortunately, there are AI tools to analyze and tag video footage. You feed them your b-roll videos, and get back the description of what’s in each clip.
Video Asset Manager works by analyzing your b-roll videos and produces a timestamped description of everything in them. A 20-minute clip comes back with entries like “person walking through a crowded market” at 0:42, “wide aerial of city at sunset” at 3:15, “hands assembling a product on a desk” at 7:50.
This is a new level of detail that makes it easier to know what the whole video is about. Scene by scene, with timestamps, descriptions of actions, and objects available without you having to waste time watching the video.
These analyses also ties b-rolls to the video script using the Video Director feature.
Paste your script into the app, select the section that needs b-roll, and tell it what you’re looking for in plain language (“drone shot over mountains”, “close-up of hands on keyboard”, etc).
Then the AI suggests the most relevant clips from your analyzed videos, ranked by how well they fit the description, allowing you to search by what’s actually in the video, not by whatever you named the file.
With this feature, you can go from a script to a shot list in minutes!
One of the best things about Video Asset Manager is that each video only needs to be analyzed once. Once analyzed, the text is stored in a database on your Mac and used in the future for when you are looking for b-rolls.
Footage you shot months ago can become useful if it matches what you need right now. Solving the problem of data being tied to project files inside your video editing software, and being hard to find.
Video Asset Manager works with whatever footage you have, your own shoots, or stock footage you’ve grabbed from places like Pexels.
There are other tools in this space, too, like Eddie AI and Jumper. They each work differently, and the right pick depends on your NLE and how you want your data stored. If you’re curious about tools that handle other editing jobs too (cutting silence, audio cleanup, captioning, etc.), we put together a guide on the best AI tools for video editing.
Expect to spend around 2 to 3 hours for every 1 hour of raw footage. This includes watching, taking notes, and organizing clips. Tools like Video Asset Manager that do automatic b-roll logging cut this to minutes with the help of AI.
Yes, tools like Video Asset Manager use visual recognition and language models to analyze what’s in each shot and generate descriptive analysis. The quality depends on the AI model, but modern models do a surprisingly good job at describing footage in useful detail.
It saves time during video editing because you find the right clip in seconds instead of scrubbing through folders looking for b-roll. It makes your footage reusable across projects: those stock footage clips and personal b-roll shots you logged stay searchable.