A complex buying process needs an advanced attribution model. A model that is truly multi-channel, attributes based on value and not position and improves with more data.
Our machine learning multi-channel marketing attribution model does exactly that! By not only considering a visit's position in the buying process we use data points such as time on site, page-views and checkout visits to determine the true value of a visit. After training our model on more than 700 million events, we can predict the probability of a purchase after each visit and attribute value accurately.
Know which channels provide the best ROI
Analyze the Customer Journey from Visit to Order
Know which channels are over/undervalued
Know your exact Customer Acquisition Cost
Compare our machine learning attribution model with last click and linear attribution models side by side
Track detailed metrics on each individual touchpoint for every order
Allocate your marketing budget in the most effective way possible
Decide which attribution model to use
Determine which marketing channels to use
With Divvit we know exactly what role each channel is playing and how it contributes to our success. Knowing exactly how your users behave is invaluable when creating a strategy to improve!