Connect creative features to advertising performance
Tag image and video ads consistently, then compare the combinations associated with useful business outcomes.
How this works
Tag image and video ads consistently, then compare the combinations associated with useful business outcomes. Creative tags are useful only when the same visual or message feature receives the same label across assets. Comparing tagged performance without controlling the observation context can mistake audience, spend, or campaign differences for a creative effect.
Define a controlled taxonomy, label the exact asset versions, and join them to performance data at a declared grain. Calculate descriptive comparisons deterministically and turn plausible associations into follow-up test briefs. Preserve uncertain labels and confounding factors rather than forcing a simple winner story.
Before you start
Taxonomy
Define observable tags with examples and an uncertain state.
Asset registry
Link media files to exact ad or creative IDs.
Comparable outcomes
Choose mature business measures and relevant campaign strata.
Prepare the inputs
- assets
- Required
Image or video files
Preserve versions and identifiers.
- tag_definitions
- Required
Controlled vocabulary
Avoid overlapping labels without clear rules.
- performance
- Required
Creative-period rows
Include spend, exposure, outcomes, and maturity.
- context_fields
- Required
Campaign, audience, placement
Use them to identify incomparable groups.
- join_map
- Required
Asset-to-ad relationships
Prevent duplicated metrics across reused files.
Implementation, step by step
Design observable tags
- Choose features such as product demonstration, testimonial format, opening question, or text density.
- Provide examples and rules for multi-label and uncertain cases.
Checkpoint: A reviewed tagging guide.
Label the media
- Use available visual analysis and transcript context to propose tags.
- Inspect ambiguous cases manually and keep the exact asset version attached.
Checkpoint: A validated tagged library.
Validate performance joins
- Join ads to assets at the declared grain and reconcile spend and outcome totals.
- Handle one asset used in several campaigns without duplicating account totals.
Checkpoint: A trustworthy joined dataset.
Compare like contexts
- Calculate measures within comparable audiences, placements, periods, or objectives.
- Show sample sizes and uncertainty; do not replace missing outcomes with zero.
Checkpoint: Descriptive tag comparisons.
Investigate apparent patterns
- Inspect representative assets and counterexamples behind strong associations.
- Identify confounding factors and combinations too sparse for useful conclusions.
Checkpoint: A qualified insight shortlist.
Brief new tests
- Translate a pattern into a controlled creative hypothesis with a specific change.
- Keep follow-up results linked to the original insight and taxonomy version.
Checkpoint: An evidence-based testing brief.
Decisions along the way
A tag is visually ambiguous
Use uncertain and request review rather than guessing.
One asset dominates a tag group
Show the concentration and avoid generalizing the pattern.
Tag groups run in different audiences
Stratify or report that the comparison is confounded.
What you will produce
tagged-creative-library.csv
CSVSupports consistent reuse and correction.
Include: asset_id · version · tags · tag_confidence · review_status
creative-pattern-review.md
MarkdownTurns analysis into testable ideas.
Include: comparison · denominator · context · association · confounders · test
Check the result
- Review tag agreement on a sample of media.
- Reconcile joined spend with source totals.
- Check group sizes and concentration.
- Ensure conclusions say associated with rather than caused unless a suitable experiment supports causality.
When something goes wrong
Taxonomy changes halfway through labeling
Version it and recode comparable assets consistently.
Join duplication inflates performance
Repair the mapping before any insight is reported.
A model infers an unseen audience
Remove the inferred tag and use documented targeting context only.
A worked example
SYNTHETIC EXAMPLE · NOT A REPORTED BUSINESS RESULT
Request
Compare demo-led and text-led creatives.
Inputs
Synthetic example. Synthetic two demo videos ran in a warm audience; four text ads ran in cold acquisition.
Expected result
Synthetic expected result. Report the observed measures but flag audience as a confounder. Propose a within-audience test instead of declaring demonstrations intrinsically superior.
Run a small pilot
Start small
A manageable asset library with known mappings and several formats.
Record the baseline
Record manual tagging effort and review disagreements.
Agree success criteria
Agree tag consistency and join accuracy before larger analysis.
Stop or revise
Stop performance conclusions when mapping or comparability cannot be established.
Keep the scope clear
- Tags describe media, not personal characteristics of depicted people.
- Descriptive analysis does not authorize campaign changes.
Check before using
Check taxonomy consistency, attribution, and confounding factors. An association between a tag and results does not prove causation.
Business activities
- Run advertising and acquisition tests
- Review business performance
FROM A RECIPE TO YOUR WORKFLOW
Bring the company context together.
This workflow needs reliable inputs before it needs a better prompt. Moat8 Vault brings working information into a readable archive for the AI tools you use.
For this recipe: Creative files · Controlled tag vocabulary · Creative-level performance data
Start with one recurring task, agree which sources to use, and review the first result with your team.
Discuss this workflow