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Incrementality testing helps you measure the true causal impact of your marketing campaigns. Instead of relying on correlation-based metrics (like attribution models), it uses controlled experiments to see what really happens when you increase or decrease marketing spend.
Key idea: Incrementality testing answers the question: Would we have seen the same results without this marketing spend?

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How Dema approaches incrementality testing

Dema’s methodology is based on geo-experiments, where we compare treatment regions (where we modify marketing spend) to control regions (where spend continues as usual). This helps isolate the actual effect of marketing.

Lift Test

Treatment regions have ads paused or reduced (holdout treatment) to measure how much performance drops without marketing.

New Channel Test

Treatment regions receive new channel ads to see if it drives incremental sales and profit beyond existing marketing efforts.

Scaling Test

Treatment regions have ad spend increased or decreased to measure the incremental impact of adjusting marketing efforts.
Unlike traditional methods that only focus on sales, Dema’s platform allows you to measure profit impact as well. Since we track NGP2 and NGP3 (Net Gross Profit), we can calculate effective ROAS (epROAS)—a profit-based ROAS that includes costs like returns and marketing spend.

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Three-phase approach to testing

Dema’s testing framework consists of three key phases:
1

Design

Selecting treatment and control regions
  • We use historical data to find similar regions based on marketing activity, sales trends, and seasonality.
Using synthetic control groups
  • Instead of simple A/B splits, we create a weighted blend of control regions that best mimic the treatment region’s past performance.
  • Example: If Los Angeles is a treatment region, our model might determine that 50% of Houston, 30% of Phoenix, and 20% of Denver together best match LA’s historical trends. This makes the comparison more accurate than a random split.
Grouping zip codes by commute zones
  • We recognize that people often shop and commute across city boundaries.
  • Instead of using rigid geographic lines, we cluster zip codes into commute zones where consumers travel frequently.
  • This ensures our treatment and control regions reflect actual shopping behavior.
2

Implementation

Region assignment
  • Dema provides the list of treatment and control regions
  • Ensures alignment with real-world consumer movement patterns
Campaign adjustments
  • Your team adjusts campaign settings in ad platforms
  • Either increasing spend (new channel treatment) or pausing campaigns (holdout treatment)
Test execution
  • The experiment runs for a set duration to collect enough data for analysis
3

Analysis

Once the test is complete, we analyze results using synthetic control modeling:Comparing actual vs. predicted outcomes
  • Check how sales and profitability in treatment regions compare to control group trends
  • Evaluate performance against baseline expectations
Measuring incremental lift
  • Calculate the increase or decrease directly caused by marketing spend changes
  • Isolate true causal impact from other factors
Calculating incremental ROAS and epROAS
  • Unlike standard ROAS based on clicks/views
  • Incremental ROAS isolates true marketing impact
  • epROAS incorporates profit margins, costs, and return rates
By focusing on incrementality, Dema ensures you’re making data-driven decisions based on the actual business impact of your marketing, not just attributed conversions that might have happened anyway.