Today’s marketers need Machine Learning because Marketing Automation, which uses traditional rules or segment based modelling and tools, isn’t working very well.
Typically, the average conversion rate from rules-based marketing is 3 to 5 percent.
The reason for these low conversion rates is that most Marketing Automation systems put your customers into ‘persona buckets’ or into predefined segments – and then keep them there.
However, in real word, customers rarely conform to these predefined assumptions. And if these assumptions are wrong then you will never be able to engage with your customer effectively.
Most Marketing Automation systems are also non-responsive, meaning if a customer rejects or ignores the offer, the same offer or type of offer keeps getting sent. But the problem with segment driven, Marketing Automation systems is not just the low conversion rates they deliver.
Rules-based Marketing Automation systems are actually fuelling consumer frustration and increasingly creating brand damage.Because as more and more organisations put Marketing Automation into their business with rules that are unresponsive or dumb, it is creating more and more clutter in customers’ inboxes. And this results in more and more customers disengaging from brands and hitting the ‘delete’, ‘dump’ and ‘unsubscribe’ buttons.
Instead, businesses should be able to send personalised offers and messages that predict and respond to your customers’ behaviour so that if customers don’t like an offer or don’t respond to it, then they don’t get it again.
These offers need to be real time and contextualised, meaning that if a customer is in a particular place then show them offers that reflect where they are and make those offers easily and instantly redeemable.
Machine Learning is based on learning about your customers through the response data and knowing whether an offer was taken up, a reward was redeemed or a communication read.
The feedback loop allows the Machine Learning algorithms to learn whether what was served to the customer was right or not and continuously refine and optimise a business’ engagement with a customer.
And even if that offer was not right that is still useful feedback that needs to be fed back into the Machine Learning engine so that you don’t serve that same offer again.
This Machine Learning also creates enormous efficiencies because you no longer have teams of campaign managers generating and managing hundreds of offers – many of which are actually delivering negative ROI.
So instead of sending out 100 offers, you can send out 30 offers but each one of those 30 offers will have a much higher conversion.
And not only is that a much better use of a business’s time and energy but it will also surprise and delight your customers when they start to receive offers that actually matter to them.
Businesses of the future need to build intelligent engagement programs that use Machine Learning capabilities to unlock the power of their data and improve ongoing engagement.
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