How To Take Full Advantage Of The Power Of Machine Learning In Digital Marketing

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.

Trust Machine Learning

It’s extremely tempting for marketers to take on the notion that they know best when their idea – about who the target customer is – consists of:

• A blend of months-old market research,
• Some historical assumptions about the customer base, as well as
• Educated guesswork.

Research and segmentation may, however, entrench some presumptions which limit the brand’s ability to reach some of the most likely prospects.

At a time when marketers are needing to spend every bit of money that they have, efficiently, it’s best to trust the algorithm in order to identify customers according to a number of different behavioural signals and other markers.. It is then necessary to target them with appropriate messaging using dynamic ads.

Learn from the likes of Netflix and Amazon, which use deep learning to target content to people based on their behavioural preferences rather than age, gender or other demographic factors.

Many marketers will lack the skills and expertise to start leveraging AI technology confidently. The solution is often a blend of recruiting talent in order to bridge the skills gap as well as working with reliable technology partners.  The benefit of both these approaches is that marketers are able to hit the ground running and also be able to accelerate their first move. Speed is critical if a marketer wants to be a disruptor rather than disrupted.

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