According to Salesforce fourth edition of the “State of the Connected Customer” report, 54% of customers say marketing messages aren’t as relevant as they’d like.

We’ve all been there and received an email, ad or offer that was clearly based on some broad customer segmentation, but the content is completely irrelevant or just tone-deaf. It certainly doesn’t instil confidence or loyalty. And it leaves you wondering if the company knows anything about you at all.

That seemingly harmless transgression may have been easy to pass off in the past. But customers expect so much more these days. And they’re prepared to move to a competitor who can give them the customer experience they demand.

So as a business, how do you keep on top of that? How do you craft relevant communication that makes every customer feel understood and valued?

Segmentation alienating customer

Focus on the individual, not the collective

If you rely on a ‘one-size-fits-all’ approach and segment customers by categories such as gender, age, or income, your interactions will alienate those who don’t fit that mould. As humans move through time, their behaviour and preferences change. Trends and external sources influence us.

That shift in behaviour cannot be reflected if you rely on general customer personas or traditional segmentation. But these behavioural changes will be abundantly clear from analysis of a person’s purchase history. And from the types of products they have recently interacted with.

If businesses can shift to using more timely digital transactional data, they open endless possibilities to interact in a much richer, more meaningful way. Having real-time capability in place is essential to do this.

Be aware of your customer’s digital personality

Every digital interaction tells a story about a customer’s behaviour. It can define their digital personality and what sets them apart as individuals. From the moment they log into an app or website, what screens they check, who they engage with, what they buy, their preferred style of engagement, etc. This data allows companies to uncover new and exciting segmentations. And in turn deliver highly relevant interactions, offers and messages to keep these customers happy.

When companies start to analyse this data, they tap into endless opportunities to learn what people truly want at that time. By continuously testing with different options, companies can learn more information about the individuals they interact with. Plus, it leads to customer experiences that set them far apart from the competition.

Test dynamically

Test dynamically and let new customer segmentations unfold in real-time

The concept of running a classical machine learning model was historically based on collecting enormous amounts of data. Setting a standard deviation, grouping a particular set of items together and coming up with a test.

But you don’t have to do that. There are people who behave outside that narrow band of what you have defined. You can still provide them with unique interactions. And that’s the difference here. You move beyond the assumption that all people must fit within that narrow band. You can set up your initial engagement or interaction, with or without prior data. It will learn dynamically about all the nuances and how people behave over time. Meaning you are no longer restricted to a standardized view.

Imagine the new knowledge, insight and customer segmentations companies would uncover by continuously running experiments and learning from their customers’ real-time actions? It would certainly make for much more personalized, contextually relevant customer interactions.