AI video production

A HeyGen Batch Mode workflow from brief to client delivery

Batch generation removes repetitive creation work. It does not remove the need for input control, naming, QA, version tracking, and a clean handoff.

Quick answer

Define one row per intended output, lock naming before generation, test a small sample, generate the batch, review every final against the source row, download approved assets with a manifest, and deliver only an explicit approved set. Archive rejected and superseded versions separately.

Use Batch Mode for controlled variation

HeyGen describes Batch Mode as a way to create many single-scene avatar videos with different scripts, avatars, or voices in one bulk job. It is a strong fit for personalized messages, ad variations, localized lessons, and repeated updates that share a structure.

Use Studio instead when each video needs multi-scene storytelling, individual layout work, or unique visual timing. Batch Mode is a production line: it performs best when inputs are standardized and variation is intentional.

Good batchPoor batch
50 product updates with one variable segment10 unrelated narrative videos
Localized one-scene training introsCourses with different scene structures
Avatar or voice A/B variantsVideos needing frame-level edits
Personalized outbound messagesInputs with unreviewed customer data

Make one source row the contract for one video

Create a production sheet before opening the generation interface. Each row should be sufficient to identify the intended output and approve it later.

Put the output key at the start of the HeyGen project title. When 80 nearly identical titles appear in a folder, that stable key is what lets the spreadsheet, rendered output, feedback thread, and local filename agree.

Run a deliberately difficult pilot

Do not test only the easiest row. Generate three to five cases that cover the boundaries: the longest script, the hardest names, multiple languages or voices, punctuation-heavy copy, and each intended aspect ratio.

  • Confirm pronunciation of names, acronyms, numbers, URLs, and brand terms.
  • Check that script length feels natural for the channel.
  • Verify crop and safe areas in every aspect ratio.
  • Review caption line breaks and on-screen timing.
  • Get stakeholder approval on the template before spending the full batch.

Fix input rules, not just the sample. If “ACME-2” is pronounced incorrectly, add a pronunciation convention to the sheet and update every affected row before generating again.

Review outputs against their source rows

Generation success means the file rendered. Approval means the file matches the brief. Use two passes:

Automated or clerical checks

Human playback checks

Record feedback against the output key. Never rely on “the third one in the folder.” Sort orders change, and regenerated outputs can appear beside older versions.

Download an approved set, not the whole workspace

  1. Mark approved rows in the production sheet.
  2. Move or filter approved projects into a clear HeyGen folder if your workspace process supports it.
  3. Download the required standard, captioned, subtitle, or alternate assets.
  4. Rename files using the output key and version, for example Q3-DE-014_v2_captioned.mp4.
  5. Export a manifest containing the output key, HeyGen video ID, filename, language, duration, and approval state.
  6. Package client-facing files separately from source sheets, rejects, and internal notes.

HeyGen’s workspace guidance recommends folders, filters, and search for organization, and Batch Mode places generated items in a batch folder. Use that grouping during production, but create a local delivery package that does not depend on the client having access to your workspace.

campaign-q3-delivery/
  01-approved-masters/
  02-captioned/
  03-subtitles/
  manifest.csv
  delivery-notes.txt

If downloading one video at a time becomes the bottleneck, compare manual, CLI/API, and extension methods. For retention beyond the delivery, apply the restorable HeyGen backup workflow.

Use exceptions to improve the next batch

After delivery, count failure types rather than merely noting that QA took too long. Useful categories include input typo, pronunciation, wrong locale, template/crop, caption layout, render failure, filename mismatch, and stakeholder change.

Turn recurring failures into gates. A pronunciation failure becomes a required pronunciation field; filename confusion becomes an output-key validator; late copy edits become an explicit “Ready” approval before generation. That is how batch production becomes faster without making quality depend on luck.

Sources and further reading