Artificial intelligence marketing
Artificial intelligence marketing (AIM) is a form of marketing leveraging artificial intelligence concept and model such as machine learning and Bayesian Network to achieve marketing goals. The main difference resides in the reasoning part which suggests it is performed by computer and algorithm instead of human.
Behavioral targeting
Behavioral targeting refers to reaching out to a prospect or customer with a communication based on implicit or explicit behavior shown. Understanding of behaviors is facilitated by marketing technology platforms such as web analytics, mobile analytics, social media analytics and trigger based marketing platforms. Artificial intelligence marketing provides a set of tools and techniques that enable behavioral targeting.
To improve the efficiency of behavioral targeting, machine learning is used. Also, to prevent human bias in targeting customers based on behaviors and do this at scale, artificial intelligence technologies are used. The most advanced form of behavioral targeting with the help of artificial intelligence is called Algorithmic Marketing.
Collect, reason, act
Artificial intelligence marketing principle is based on the perception-reasoning-action cycle you find in cognitive science. In marketing context this cycle is adapted to form the collect, reason and act cycle.
Collect
This term relates to all activities which aims at capturing customer or prospect data. Whether taken online or offline these data are then saved into customer or prospect databases.
Reason
This is the part where data is transformed into information and eventually intelligence or insight. This is the section where artificial intelligence and machine learning in particular have a key role to play.
Act
With the intelligence gathered from the reason step above you can then act. In marketing context act would be some sort of communications that would attempt to influence a prospect or customer purchase decision using incentive driven message
Again artificial intelligence has a role to play in this stage as well. Ultimately in an unsupervised model the machine would take the decision and act accordingly to the information it receives at the collect stage.
Machine learning
Machine learning is concerned with the design and development of algorithms and techniques that allow computers to "learn".
As defined above machine learning is one of the techniques that can be employed to enable more effective behavioral targeting
Concerns
As mentioned in the behavioral targeting article :
"Many online users & advocacy groups are concerned about privacy issues around doing this type of targeting. This is an area that the behavioral targeting industry is trying to minimize through education, advocacy & product constraints to keep all information non-personally identifiable or to use opt-in and permission from end-users (permission marketing)."
See also
References
Further reading
- A.I. for Marketing Navigator
- Baesens Bart, Stijn Viaene, Dirk Van den Poel, Jan Vanthienen, and Guido Dedene. (2002), "Bayesian Neural Network Learning for Repeat Purchase Modelling in Direct Marketing", European Journal of Operational Research, 138 (1), 191–211.
- Lou Hirsh (2002), "How Artificial Intelligence Decodes Customer Behavior", CRMDaily.com.
- Yahoo Research Center Machine Learning.