Artificial Intelligence () has made the transition from once being a glorious manifestation of sci-fi imagination to today emerging as a technological reality capable of disrupting industries.
In an increasingly hypercompetitive business environment, the marketing function is no exception to the application of . In fact, in a recent PwC study, 72% of the marketers interviewed, consider as a “business advantage”.
When actionable data is considered the fulcrum for growth, the modern marketer barely utilises 5% of the customer-centric data – that often exists in straitjacketed silos – at his disposal.
This is where Artificial Intelligence Marketing comes into the picture. It is the calibrated use of customer data – from online and offline sources – and computational concepts such as Machine Learning to predict customers’ digital actions or inactions (on web or mobile app platforms), enabling businesses to intelligently target the right customers with the right content across the right channel, and at just the right time.
Here are 4 ways in which Marketing can be leveraged within the marketing automation ecosystem to craft and deliver highly differentiated customer experiences at scale:
If the customer is king, content is your anointed messenger to influence decision-making. allows marketers to adopt a data-driven approach with the objective of making predictive sense of their digital customers’ diverse behaviours across channels and devices. By analysing historical browsing and transactional patterns, marketers can identify relevant customer segments.
These segments can be then be targeted with laser-focused personalised and contextualised content through appropriate channels of communication, such as emails, browser push notifications, app push notifications, or in-app messages, to nudge them along their journey towards conversion.
further allows marketers to easily embed high-sentiment keywords in these messages that have resulted in a conversion event based on key metrics such as open and click rates relevant to each customer, chronicled over a period of time.
Do they react better to vanilla text messages? Or, do they react better to emojis, images, and GIFs?
Higher the degree of personalisation, higher the chances of campaign success.
For instance, in the context of e-commerce, advanced analytics allows marketers to identify a customer segment that reacts favourably to price drop sales. can then help target micro-segments with the right campaign content based on previous products viewed, items added to cart, or purchased.
Send Time Optimisation:
Marketers also need to target the right audiences at the right time. allows marketers to identify customer segments that respond to a particular campaign at specific times based on historical behaviour. Over a period of time, the system establishes a degree of predictability around the customers’ reactions and this learning input is fed back into campaign intelligence.[…]