Since channels include Ad sources, organic search, mail and social sites, data identification is not consistent across all sources.
Currently models are applied based on total conversion irrespective of user’s repeat purchase. Since data is not user-centric, it is hard to differentiate first purchase from repeat purchases.
Most models practiced today are either Single Source or Fractional, and both have their own limitation. Algorithmic Attribution Model assigns conversion credit across all touch points preceding the conversion.
Plumb5, with its customer-centric integrated platform, solves all the current challenges of arriving at an accurate attribution model
Plumb5 scripts monitor all incoming traffic irrespective of the channels (even email) and records and assigns value to each interaction, for every individual user. Since data is stacked by user, data is filtered for users who have successful transactions. This helps us identify all sources that these users have visited, and that have contributed to the purchase goals.
Plumb5 integrates with your store in order to tag transaction behavior of each individual user. This helps in identifying the purchase touch-points of the user. Understanding the first purchase touch-point is crucial, because all sources contributing to subsequent purchases are attributed differently, to understand influencing sources to conduct effective retention campaigns
With Plumb5, you can set scores for behavior parameters like page depth, page type, event type, time spend, frequency. This allows in assigning values for sessions that involved high interactions which could be influencing the purchase decisions. This helps us to identify effective touch-points irrespective of their occurrence.