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Demo with Sample Data

Experience MMM Analysis Results

Below are MMM analysis results using sample data from 5 advertising channels. Explore channel ROI, adstock effects, and budget optimization in the same dashboard used by our product.

R\u00B2 Score

0.920

Model Fit

MAPE

8.5%

Prediction Accuracy

Channels

5

Channels

Best ROI

2.8x

リスティング広告

How to read: Estimated contribution of each channel to total sales. Longer bars indicate higher contribution, helping identify which media is most effective.

How to read: The return ratio per unit invested. Values above 1.0 indicate positive revenue contribution; below 1.0 suggests the channel needs cost-efficiency review.

How to read: The residual rate of advertising effect (\u03B1 value). Higher values mean the effect persists longer, continuing to influence sales in subsequent weeks.

How to read: Shows diminishing returns on additional investment. As the curve flattens, further spending yields diminishing returns.

Key Insights from This Demo Data

  • Search ads have the highest ROI (2.8x): Most cost-efficient channel with room for increased investment as it hasn't reached saturation
  • TV CM has outstanding adstock effect (\u03B1=0.82): Advertising impact persists for 8+ weeks, contributing to long-term brand building
  • Display ads show negative ROI (0.7x): Budget optimization recommends reducing from \u00A57M to \u00A53M
  • YouTube ads combine high ROI (2.4x) with moderate adstock: A channel where increased spending can drive further results
  • Recommended reallocation within total budget of \u00A511M: Concentrate investment in high-ROI channels (Search +113%, YouTube +83%) and significantly reduce low-ROI channels (Display -80%)

Ready to analyze your own data?

Simply upload a CSV to run automated Bayesian MMM analysis. Get channel-level ROI and optimal budget allocation.