Summary
The ROAS Table displays return on ad spend progression across different days since install (DSIs). This table view makes it easy to diagnose which segments are profitable, identify where ROAS is underperforming, and compare performance across cohorts or segments.
The dashboard is most useful for
With a time pivot:
For a given filter (e.g. geo = USA, network = Unity, Last 30 days), track how ROAS progresses across D0 → D365
Assess payback speed of recent vs older cohorts
With a segment pivot:
For a given time period (e.g. Last 30 days), identify which segments (e.g. country, network, platform, campaign) are exceeding or missing targets
Spot underperforming campaigns quickly using conditional formatting
Tips and warnings
✅ Use Time pivot to evaluate how fast cohorts approach breakeven at each DSI milestone
✅ Use Campaign / Geo / Network pivots to rank where ROAS is strongest or weakest - conditional formatting makes outliers obvious to further optimise
✅ Sort by ROAS to quickly surface top- and bottom-performing segments
✅ Sort by Spend or Installs first to ensure results are weighted toward meaningful volumes
⚠️ Partially predicted values (*) combine actuals and forecasts - interpret as directional, not definitive
⚠️ Fully predicted values (**) are modeled on historical patterns and carry higher uncertainty
⚠️ Small segments (low spend / installs) may skew CPI or ROAS averages
Advanced Information
What is in this dashboard
Single table with selectable columns
Columns include:
Pivot dimensions (e.g. Campaign, Country, Network, Platform).
Spend, CPI, Installs
ROAS at selected DSIs: D0, D1, D7, D28, D60, D90, D180, D365
Features:
Sortable by any column
Conditional formatting:
0% ROAS = red background
100% ROAS = white
100%+ ROAS = green
Adjustable rows per page
Pagination controls for navigation
How it works
Values shown:
Actuals and predictions at each DSI for ROAS
Aggregated actuals for spend, installs
Weighted average of CPI
Indicators:
No symbol = Fully actualized KPI actuals
* = Partially predicted
** = Fully predicted
Partially predicted:
Within the cohort date range, some install dates have matured to the selected DSI while others have not
Aggregates therefore combine actuals and forecasts
Typically applies to recent cohorts still maturing
Fully predicted:
All values are forecasted (no actual data available)
Typically applies to future cohorts not yet acquired
Aggregation rules:
Spend and installs = Summed across cohorts
CPI and ROAS = Weighted averages across cohorts within the selected timeframe
Available filters
Paid vs Blended (include / exclude organic uplift)
Net vs Gross (with / without platform fees / taxes)
Pivot dimensions:
Default = Campaign + Country
If Time is pivoted, no second pivot can be added
If Time is not pivoted, up to 2 dimensions may be selected (Campaign, Network, Geo, Platform) in any combination
Time groupings: Cohorts may be grouped by daily, weekly, or monthly installs
Date range selector: Quick ranges include Last 7, 14, 30, 6 weeks, 60 days, or 90 days
Segment filters: Views can be narrowed by Geo, Platform, Network, or Campaign, either individually or in any combination