Acquigo constantly optimizes campaign parameters using its self-learning algorithms on three levels.
Variables used to micro-segment customers
Values of variables used to micro-segment customers
Recommended Action
Variables used to micro-segment customers
Acquigo considers hundreds of behavioural variables to micro-segment customers – something that is humanly impossible!
Acquigo's algorithms are so powerful that they statistically pick out the variables that have the greatest influence in creating micro-segments.
Acquigo does this consistently, ensuring all the variables used for micro segmenting customers are indeed significant every time.
Value of variables used to micro-segment customers
Once these variables have been identified, the next step is to determine the value range for each variable used to define each microsegment.
Considering customer-heterogeneity, changing business dynamics, customer behaviours and preferences, this criteria can change from day to day!
Acquigo regularly optimizes the value of variables used to micro-segment customers.
Recommended Action
No two customers are the same. Which is why there is the need to optimize recommended actions constantly.
Acquigo does this by spotting subtle differences within micro-segments and tweaking the recommended action to make sure it is highly relevant.
For example, if 1000 customers have less than 30 days to renew their policies, Acquigo does not send them all reminders to renew.
Instead it sends an "engagement" campaign to customers who usually renew their policies right on the policy lapse date.
A "retention" campaign to those who usually renew their policies two weeks before the policy lapse date.
And a "winback" campaign to those who normally renew their policies a month after the policy lapses.
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