Campaign Library

A living catalog of how we group paid cohorts for ad campaign app analytics—so media, product, and analytics share names before the next briefing.

Soft-lit analytics workspace suggesting campaign review

How we sequence a campaign engagement

Each step produces an artifact your media and product partners can keep after we leave.

Signal inventory

We list every campaign parameter you already collect—UTMs, network click IDs, deep links, MMP joins—and note where they disagree.

Cohort draft

We propose named campaign families with inclusion rules, exclusions, and the primary post-install metric each cohort is meant to move.

Contrast pass

We compare activation, retention, or conversion across priority creatives and channels and flag journeys that stall after paid open.

Briefing package

You receive a written readout or memo your stakeholders can reuse in media planning—without waiting for a dashboard redesign.

Example campaign cuts

Illustrative cohorts we often start from for Thailand-based growth teams. Final taxonomies are tailored in the audit.

  • Acquisition — first open

    Focus: Paid installs measured through first meaningful open and early session quality

    Signal: Click ID / network param joined to first_open and session_start

    Review cadence: Twice weekly during active buys

  • Activation — key action

    Focus: Campaigns judged on completion of the promised in-app action

    Signal: Attributed install plus primary conversion event within agreed window

    Review cadence: Weekly creative and channel contrast

  • Re-engagement — return paths

    Focus: Push, email, and paid remarketing that bring dormant users back

    Signal: Campaign tag on reopen with exclusion of organic reopen noise

    Review cadence: Bi-weekly retention and fatigue notes

  • Unknown / thin tagging

    Focus: Traffic missing reliable campaign parameters

    Signal: Null UTMs, broken deep links, or conflicting MMP joins

    Review cadence: Tracked as a coverage KPI, not a growth channel