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Technologies such as real-time data, artificial intelligence and prescriptive analytics, have made it possible to take this kind of hyper-personalised approach to customer communications.
Technologies such as real-time data, artificial intelligence and prescriptive analytics, have made it possible to take this kind of hyper-personalised approach to customer communications.

How to hyper-personalise your digital communications


By Ross Sibbald, Commercial Director, Striata - Jun 26th, 09:46

There was a time, not all that long ago, when personalising digital communications simply meant addressing your customers by name. We’ve come a long way since then. Today’s customers expect to receive communications that are relevant, arrive at the right time, and via the channel, they’re most comfortable using.

Technologies such as real-time data, artificial intelligence, and prescriptive analytics, have made it possible to take this kind of hyper-personalised approach to customer communications.

That said, it still has to be implemented in a considered manner that puts the customer experience top of mind.

Beyond broad strokes

At this point, it’s worth noting that hyper-personalisation doesn’t mean ignoring traditional marketing segmentation based on demographics, geographics, and psychographics. Instead, it should be viewed as taking them to the next level.

If you imagine customer profiling (segmentation) as a broad strokes approach, hyper-personalisation is more fine-tuned, focusing on the micro details that are missed when grouping people into market segments.

So, rather than just focusing on a customer’s personal data such as their name, organisation, title, and possibly even historical purchase data, a hyper-personalised approach incorporates real-time and behavioral data to build a next best offer or action that is highly relevant and is delivered at the optimal time.

A great example of how hyper-personalisation might work can be found in the retail space. Ordinarily, you might be sent an email with monthly specials based on your age, where you live, and what you’ve bought previously.

With hyper-personalisation, the retailer can send you tailored messaging based on your personal preferences, previous spending patterns, and even the weather outside.

Of course, being able to deliver this level of hyper-personalisation requires massive amounts of data. Traditional data gathering methods simply won’t work here.

Fortunately, new technologies allow organisations to gather and use behavioral data in real time to define the best offer or next action for each individual customer.

An exclusive club

Despite the obvious benefits of hyper-personalisation, comparatively few organisations have embraced the concept.

While there are a few pioneering outliers -- including Amazon, Spotify, and Starbucks -- who have embraced hyper-personalisation, research from WebEngage shows that 90% of organisations are still using more traditional forms of market segmentation.

That means any organisations looking to get on board with hyper-personalisation still have a chance to be pioneers in the space.

Doing it right

But if an organisation is going to implement hyper-personalisation, it has to take the right approach.

Here’s what this approach might look like in recipe form:

Recipe for hyper-personalised messaging

Dry Ingredients
Personal data
Transactional data (must be real-time)
Behavioural data (must be real-time)

Data analytics application (of your choice)
Artificial intelligence application (of your choice)
Application Platform for message generation and delivery

Mix the dry data ingredients together in the data analytics app
Feed this mixture into the artificial intelligence app to create offers per individual
Transfer the output to the message generation app
Use the message delivery app to deliver the hyper-personalised message to each customer

Reaping the benefits

Get this recipe right and there are serious benefits to be reaped.

Not only are customers willing to trade data for a more personalised experience (83% of consumers are willing to share their data to enable a personalised experience), a Salesforce study found that 51% of consumers expect that companies will anticipate their needs and make relevant suggestions before they even make contact.

An organisation that successfully leverages data to provide enhanced customer engagement will build brand loyalty and trust. Companies that are not on track to do this risk a higher level of customer churn. According to research, 41% of US consumers admit having moved away from their preferred brands due to a lack of personalisation and trust.

Businesses that successfully implement hyper-personalisation can expect greater customer retention, improved loyalty and increased spend from more engaged customers.

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