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Roadmap


Roadmap for ChannelAttribution Pro


TITLE
DESCRIPTION
EXPECTED RELEASE
Integrate customer journeys in HTA modelEnhance the hidden touch attribution model by incorporating channels for which clicks and/or impressions are available at the customer journey level, as well as channels for which impressions are only available in aggregated form at fixed time instants.Feb, 2024
Markov model with external variablesImprove Markov model including external variables. External variables could include any information related to customer and the journey that can be collected through first-party cookies or other methods. Examples: distance in time between each touchpoint in a customer journey and the conversion state, type of device used by customer, type of browser used by customer, geographic region of the customer etc..Apr, 2024
Improve the customer journeys generation process of HTA model when customer journeys are not availableImprove the hidden touch attribution model including costs for each channel and correlations between number of clicks or impressions for each channel and the observed conversions.Jun, 2024
Speed-up computation for Markov modelReduce computational burden for problems with a high number of channels with respect to number of paths.Aug, 2024
Compare HTA vs MMMCompare the hidden touch attribution model and media-mix model in a simulated budget allocation problem based on real data.Oct, 2024
Compare MTA vs MMMCompare multi-touch attribution models and media-mix model in a simulated budget allocation problem based on real data.Dic, 2024