Over the past number of years, artificial intelligence (AI) – as well as machine learning – in marketing have come a long way. However, many marketers who are making use of today’s programmatic and social platforms in order to reach their audience are not utilsing0 the full power of the algorithms that these platforms are able to offer or the vast amounts of consumer data which they collect.
Many marketers apply traditional media tactics, metrics as well as segmentation models to a digital world. However, data and algorithms are far better as opposed to any human – no matter how experienced or insightful – in spotting and targeting the correct consumer with a message or experience which leads to a conversion. The reason for this is very straightforward: the platforms have the power to analyse data at unimaginable scale and also to identify patterns which would escape the human eye.
While there are clear benefits for implementing artificial intelligence – improving operational efficiencies as well as obtaining a better understanding of the customer are only two – it can also be a formidable task to embark on.
Quality Of Data
One of the key considerations that digital marketers need to keep in mind, when implementing machine learning, is that through this type of learning, they are able to take data from multiple channels and then turn that into actionable predictions and recommendations.
However, the biggest success factor is not the algorithm behind these insights but rather the quality of the data which feeds into it. Retailers which do not have their data estates in order run the risk having underwhelming outcomes from their AI investment. This is something that must be considered.