Marketers Combine Media Mix Modeling With Surveys
Enterprise marketers are using a combination of media mix modeling and post-purchase surveys to better understand customer behavior, according to MarTech. This approach helps account for dark social and offline channels that traditional digital attribution methods may miss.
Original reporting · martech.org
Original: “Combining MMM with post-purchase survey attribution”
Read “Combining MMM with post-purchase survey attribution” at MarTech →
How this was written. Clicktag wrote this article with a language model from MarTech’s reporting (model: @cf/meta/llama-3.3-70b-instruct-fp8-fast); it describes that reporting rather than adding to it. The original, linked above, is the full story.
Key points from MarTech’s report
- Enterprise marketers are combining media mix modeling with post-purchase surveys to better understand customer behavior.
- This approach helps to account for dark social and offline channels that traditional digital attribution methods may miss.
- The combination of media mix modeling and post-purchase surveys can provide a more accurate understanding of how different channels contribute to business results.
- Marketers can use incrementality testing to refine their models and improve the overall calibration.
- Survey design is critical to collecting high-quality data and understanding the specific channels and influences that drive customer behavior.
Traditional digital attribution methods have limitations, particularly when it comes to tracking the impact of word of mouth, private messaging, and offline brand exposure. MarTech reported that these methods often fail to capture the influence of these channels on customer behavior.
To address this issue, marketers are turning to a combination of media mix modeling and post-purchase surveys. Media mix modeling analyzes historical spending and revenue data to estimate the contribution of different channels to business results.
However, this approach has its own limitations, particularly when it comes to organic word-of-mouth and dark social channels. Post-purchase surveys can help fill this gap by providing insights into how customers first learned about a brand.
By using survey data, marketers can create structured inputs for their models, which can help to expose halo effects and give more credit to upper-funnel channels. This can lead to a more accurate understanding of how different channels contribute to business results.
The combination of media mix modeling and post-purchase surveys can also help marketers to better understand the impact of offline channels, such as TV, print, and in-person events. MarTech noted that these channels are often difficult to track using digital attribution methods alone.
To further refine their models, marketers can use incrementality testing to compare the results of their media mix modeling and post-purchase surveys. This can help to identify areas where the two approaches disagree and improve the overall calibration of the model.
The design of post-purchase surveys is also critical, as it can impact the quality of the data collected. Surveys that combine structured options with open-text responses can provide richer data and help marketers to better understand the specific channels and influences that are driving customer behavior.
Questions and answers
What are the limitations of traditional digital attribution methods?
Traditional digital attribution methods have limitations, particularly when it comes to tracking the impact of word of mouth, private messaging, and offline brand exposure.
How can post-purchase surveys help to improve media mix modeling?
Post-purchase surveys can provide insights into how customers first learned about a brand and help to create structured inputs for media mix models.
What is the importance of survey design in collecting high-quality data?
Survey design is critical to collecting high-quality data, as it can impact the quality of the data collected and help marketers to better understand the specific channels and influences that drive customer behavior.
