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Hunt progression analytics

Use analytics snapshots and exports to understand how participants move through a Treasure Hunt.

In this article, you'll see how to measure Treasure Hunt performance with the current OmniLab reporting surfaces and when to switch from dashboards to exports for deeper analysis.

What you can measure today

The current Treasure Hunt reporting workflow is strongest for:

  • overall hunt activity at campaign or touchpoint level
  • completion and participation patterns over time
  • exported participant or form datasets for deeper analysis
  • dashboard snapshots you need to share with other teams

Use exports for deeper journey analysis

If you need a custom object-by-object view or a tailored progression analysis, the most reliable approach is to export the underlying data and analyze it outside OmniLab.

Match the question to the reporting surface

QuestionBest place to lookWhy it works
How much overall activity did the hunt generate?Campaign AnalyticsBest for the top-level performance view over a date range.
How did engagement change during the activation?Campaign AnalyticsGood for trend snapshots and stakeholder reporting.
Which participants completed the hunt or submitted form data?Participants exportsBest when you need record-level detail.
Which form answers came from the hunt?Participants -> Participation forms dataBest for operational follow-up or spreadsheet analysis.
Do I need a custom route or object analysis?Export the data to CSVBest when you need to slice the hunt more deeply than the dashboard view.

Use the dashboard for the fast read

Start with campaign analytics when you want the quickest answer to questions like:

  • Was the hunt active enough during the campaign period?
  • Did engagement rise after a placement change or launch push?
  • Is the overall experience worth extending, repeating, or promoting harder?

This is the right surface for daily checks, team updates, and top-level performance snapshots.

Use exports for the deeper read

Exports are the better choice when you need to:

  • identify the participants behind the results
  • hand off data to another team
  • analyze form submissions in a spreadsheet
  • build a custom view of progression or completion outside the dashboard

The current backoffice export pattern is straightforward:

  • use Analytics when you want a PDF snapshot
  • use Participants or Participation forms data when you want CSV detail

See Exports & reports for the broader export workflow.

What to look for in the results

Treasure Hunt analytics are most useful when they help you improve the real-world route:

  • In Sequential hunts, look for the first stage where participants seem to fall away.
  • In Any Order hunts, compare whether some locations attract more activity than others.
  • If AR objects underperform, review device support and on-site testing before you change the creative concept.
  • If completion is low, review the difficulty of hints, questions, and physical placement together rather than in isolation.

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