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Markov Chain Attribution

Which campaigns and channels are contributing the most to your conversions? Attribution modeling can help answer this question, pinpointing the most effective touchpoints so that you can optimize investments in future marketing campaigns.


However, since user journeys often involve many twists and turns until the user reaches conversion, it can sometimes be difficult to accurately assess which touchpoints had the most impact. Choosing the right attribution model is therefore very important and can make a huge difference in the long run.




Traditional models all have one big flaw in common: They are based on static rules and don’t let the content of the data influence how the attribution process is applied. This means that none of these models are able to capture the complexities of user journeys, nor can they unveil how combinations of touchpoints affect buyers and their chances of converting.


Markov chain attribution allows us to model the probability of a user transitioning between specific states, showing us which touchpoints are the most important and which paths are most likely to lead to conversion. Inversely, we can also see which touchpoints have a lesser impact on conversion.




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