In this article we'll explain how to interpret the percentage of accuracy that you see in the Insights section of Morpheus MMM platform.
The accuracy percentage in Marketing Mix Modeling (MMM) indicates how well the model predicts actual sales based on given marketing activities and other data. A higher percentage means the model's predictions are closer to real outcomes.
Why accuracy isn't 100%
MMM can't achieve 100% accuracy due to the inherent uncertainties in statistical models. The accuracy depends heavily on the quality of the data and the assumptions used.
To improve the reliability of the model's predictions, it's crucial to consider external factors like market conditions, competition, and customer preferences etc.
Factors Influencing MMM Accuracy
Several factors contribute to the accuracy of an MMM model:
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Data Quality: Accurate MMM modeling relies on high-quality data, including sales figures, marketing expenditures, and other relevant variables.
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Granularity of Data: More detailed data, such as breakdowns by product, region, or channel, typically leads to more accurate results.
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Proper Attribution of Marketing Spend: Accurately attributing marketing expenditures to specific channels or campaigns helps determine their true impact on sales.
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Incorporation of External Factors: Including external influences like seasonality, events (e.g., pandemics), and economic indicators improves the model's ability to predict the impact of marketing activities.
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Ongoing Validation and Optimization: Regularly validating and updating the MMM model ensures it remains accurate and relevant as business and marketing environments change.
What is Good Accuracy
An accuracy percentage between 80-95% is generally considered good. If the model's accuracy falls below this range, it's advisable to review and improve the data quality by checking the factors mentioned above.
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