What Metadata and Tagging Costs and What Moves the Price
A plain look at what drives the cost of metadata and tagging work on a video library: clip volume, field design, existing mess and review time, so you can budget sensibly.
Daniel Whitfield · · 6 minutes to read
Why metadata work is hard to price from a distance
People often ask me for a single figure for tagging a library, and I understand why. Budgets need a number. The honest answer is that metadata work scales with decisions rather than with gigabytes. Two drives of identical size can take very different amounts of effort, because one holds clips with consistent names and a clear folder history, while the other holds years of exports called final_v2_REAL.
That is why starfyrepo does not publish a flat rate for this module. Pricing starts with an asset review, and the review tells us what the work really involves. Any hands-on file handling for your team is scoped and agreed separately, so you know what is included before anything is touched.
The learning side, where your team practises adding useful metadata to clips and exports, is a different matter from hands-on tagging, and we keep the two clearly apart. This article is about the factors behind the price, not a quote.
Clip volume and how it actually counts
Volume matters, but not in the way most people expect. A thousand short clips from one shoot, all following the same camera naming, can be tagged in bulk with a shared set of values. Five hundred clips from twelve different projects, shot by several operators, need far more individual attention.
When we talk about volume we look at the number of distinct projects, cameras and file types rather than the raw count. A library with one dominant structure is cheaper to work through than one with many small exceptions.
Exports add their own layer. Finished deliverables need fields that footage does not, such as version, approval status and intended platform. If you have many final exports in several formats, expect that to feature in the scope discussion, since each of them is something a colleague will later search for.
- Number of separate projects in scope
- Number of cameras and operators involved
- File types: raw footage, proxies, exports, project files
Designing the fields before filling them
The largest single driver of effort is deciding what to record. A field list that is too long never gets filled in, and one that is too short leaves footage unfindable. Choosing a sensible set, perhaps project, shoot date, subject, location, rights status and version, takes real discussion with the people who search the library.
I usually ask who looks for footage, what they type into the search box, and what they give up on. Their answers shape the fields. Teams that already know these answers move quickly. Teams that have never discussed it need a session or two first.
Controlled vocabularies are part of this. Agreeing that the tag is interview, not talking head or Interview or sit-down, saves hours later. Writing that list down and getting sign-off from the editors is time well spent, and it is time that appears in the price.
The condition of what you already have
Existing mess is the second big variable. Duplicates, unlabelled clips, missing project files and drives nobody dares delete all slow the work. Every unknown clip needs someone to open it, decide what it is and either tag it or flag it for a person who remembers the shoot.
A short audit up front tells us how much of this there is. It is far cheaper to discover that a third of a drive is duplicated before tagging begins than halfway through, when effort has already gone into copies you will delete.
Your own availability matters too. If a producer can answer questions about unclear footage within a day, work flows. If answers take two weeks, the same job stretches out and costs more in coordination, even though the tagging itself has not changed.
- Duplicates and near-duplicate exports
- Unlabelled or unidentifiable footage
- Missing sidecar or project files
Training your team versus doing the work for them
There are two broad ways to spend money here. One is teaching your own people the practice, so they tag as they go and keep the system alive. The other is handing over a backlog for hands-on handling. Most teams need some of each: a catch-up on old material and training for everything new.
Training cost depends on group size, how many modules you combine and whether you want worked examples built around your own shoots. Hands-on handling depends on the factors above. Because they are so different, we scope them separately and never fold one into the other without saying so.
If budget is tight, my usual advice is to train first. A team that tags new material correctly stops the backlog from growing, and the old material can be tackled in stages, starting with the projects people actually ask for.
Reading a scope so you can compare it fairly
When you receive any proposal for metadata work, from us or anyone else, check what it names. It should list the fields to be recorded, the vocabularies to be agreed, the number of projects covered, what happens to unidentifiable clips and who signs off the result. A scope that only says tag all footage leaves too much open.
Ask also what you will have at the end. A good outcome is a documented field list, a short guide your editors can follow, and a library where a search months later returns the right clip. Those are things you can check, which is more useful than a promise of a tidy archive.
Finally, ask what is excluded. Clear boundaries protect both sides, and they make the later conversation about extra work calm rather than awkward.
- Named fields and agreed vocabularies
- Stated number of projects and drives
- Defined handling of unknown footage
- Sign-off step and written guide
The price of metadata and tagging follows a handful of things you can see in advance: how many distinct projects you have, how clean the starting point is, how many fields you want, and whether you need training, hands-on handling or both. Start with an asset review, agree the scope in writing, and decide the fields with the people who search. That keeps the cost understandable and the result findable.
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