As digital marketing evolves rapidly, many marketing teams are finding that traditional attribution models no longer provide the full picture needed to optimise campaigns and demonstrate ROI. While last-click and other simple attribution approaches served marketers well in the past, today's complex, multi-channel customer journeys require more sophisticated measurement.
Traditional attribution models face several challenges:
1. Incomplete data due to privacy regulations and platform changes
2. Inability to measure incremental impact across all funnel touchpoints
3. Overemphasis on last-click or last-touch interactions
These limitations can lead to misallocation of marketing budgets and suboptimal campaign performance.
Marketing Mix Modeling (MMM) has emerged as a powerful alternative to traditional attribution.MMM provides a more holistic view of marketing effectiveness across channels and can account for factors that attribution models often miss.
However, it's crucial to implement MMM correctly. The "holdout test" is a critical challenge for MMM. This test involves withholding a portion of data from the model to see if it can accurately predict outcomes for that unseen data. If an MMM fails this test, it may be making unreliable predictions, potentially leading to poor marketing decisions.
1. Implement Robust MMM: Ensure your MMM can pass the holdout test and accurately predict outcomes for unseen data.
2. Focus on Incrementality: Measure the incremental impact of specific marketing activities through controlled experiments and holdout tests.
3. Integrate Online and Offline Data: Connect digital and physical touchpoints for a complete picture of the customer journey.
4. Leverage AI and Machine Learning: Use advanced analytics to uncover patterns and insights in large datasets.
5. Conduct Regular Experiments: Use A/B tests and other experimental designs to validate models and explore new growth opportunities.
6. Calibrate Models Continuously: Regularly update your models with new data and insights to maintain accuracy.
CMOs should be wary of models that can't accurately predict outcomes for unseen data, as this could lead to misallocation of marketing budgets. Regular validation through holdout tests and other methods is crucial to ensure your measurement approach is delivering reliable insights.
There's no one-size-fits-all measurement strategy. Develop custom approaches tailored to your specific business model, sales cycle, and customer behaviours. This may involve combining elements of attribution, MMM, and experimental designs.
By moving beyond simplistic attribution and embracing more advanced measurement
approaches, marketing teams can gain deeper insights, optimise spend more effectively, and better demonstrate the value of their efforts. The key is to continually test, validate, and refine your measurement strategy as customer journeys and marketing channels evolve.
What measurement strategies have you found most effective for your business? How do you validate your models?
Adnan Khan Co-Founder, Stitch
Chair, MA Digital Special Interest Group