Predictive marketing: taking the guesswork out of adverts

Identifying customer profiles has always been something of an art for marketers - with the right technology partner it can now be more scientific.

Another day, another ad platform. Last month, not only did Snap sign a $100 million global content and advertising deal with Time Warner, but Comcast launched a platform for brands to buy ad space in broadcast and TV streaming using blockchain technology.

These announcements are indicative of the speed of both the evolution and rapid rise of ad channels. And more platforms or channels mean more ways for brands to reach potential customers, right?

True, but it also fragments the places where they spend time, forcing marketers to ask the question: ‘where will my customers be next?’ Brands, now more than ever, need to understand the journey their customers are taking and where they are likely to be, not just today, but tomorrow.

>See also: Predictive analytics: the next frontier in business intelligence

Predictive marketing, which applies artificial intelligence to oceans of data to help marketers anticipate the moments a consumer is most likely to take an interest in their products or services, is central to this. And it is soon to become the de-facto model in ad land.

From AdWeek Europe to Cannes Lions, the panels and parties were awash with talk of how artificial intelligence (AI), predictive analytics and targeting, are changing the face of modern marketing.

That’s because it allows brands to deliver cross-device, always-on, always-relevant experiences to a near-infinite number of people, instead of being limited by segments.

Predictive marketing moves away from stats, stereotypes or the constraints of age and gender towards informed messaging decisions that amplify the customer journey.

This is done through AI-driven propensity models based on billions of moments. These models learn about a customer’s future behaviour, based on their previous interactions, such as browsing behaviour, past purchases and interests, as well as metadata about their devices and thousands of other variants. All these aspects combined paint a holistic picture of the entire customer journey and are delivered at scale in real time.

All the data in the world – even your own – is worthless it can be converted to intelligence and applied to your business, giving you better insights into your own customers and prospects than ever before.

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Predictive marketing allows the industry to move beyond gut instinct and use the precise processing of more data than any of us ever dreamt of to enable the right decisions about when and where to deliver advertising.

The data that makes the difference in a predictive world doesn’t come from a purchased data set, it comes from capturing the signals generated by and around your own audience to feed your analytics engine.

It thrives on complex consumer journeys and large volumes of high-speed data, learning more as it goes. And in turn predictive marketers are rewarded with higher levels of engagement, rapidly improving brand KPIs, lower customer acquisition costs and ultimately higher ROI. That’s not to say, of course, that a first-part-data approach is the only way.

Not all data is created equal and there are benefits from a combination of data sources including third party. But marketers who focus solely on what we call ‘rented’ data should beware of its limitations.

AI can help marketers navigate the oceans of data that exist today and anticipate the moments a consumer will be ready to respond to their brand, products and services.

This means they can offer real-time, contextual targeting that allows them to find potential customers and serve ads that are relevant, anticipated, even enjoyed, rather than just irritating – at the right time, on the right device.

>See also: What’s the block with predictive analytics?

What do consumers think of AI? Our recent consumer survey on Perceptions of AI found that nearly two-thirds of people find it an exciting development in technology.

What’s more, in terms of its application, 61% of those surveyed said they were aware of it being used in media, advertising and marketing combined. Out of those aware of its use in advertising, 57% said they viewed it as a positive force.

Continual fragmentation in media and a scattered, always on audience, as well as the swift rise in different devices and platforms, is making marketing increasingly challenging.

If brands want to connect with potential customers in the moments that matter, they need to dial up the analytics, adopt an AI approach, be more scientific and leave the art to their creative colleagues. Only then will they be able to mine masses of data to discover who and where their customers are better than ever before.


Sourced from David Gosen, SVP and managing director at Rocket Fuel

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Nick Ismail

Nick Ismail is a former editor for Information Age (from 2018 to 2022) before moving on to become Global Head of Brand Journalism at HCLTech. He has a particular interest in smart technologies, AI and...