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Before marketers can explore the potential AI has for personalization, they need to ensure their data is in good shape PHOTO: Jason Briscoe

When Google CEO Sundar Pichai declared the company's core focus had moved from mobile-first to Artificial Intelligence (AI), it became clear the AI revolution was no longer imminent — it was already here.

Smart assistants help organize our lives. Self-driving cars cruise the roads. And Apple is rumored to be building chips that embed AI into multiple devices. 

This rapid development offers a substantial opportunity for businesses to improve products, services and experiences.

Unsurprisingly, marketers are among the first in line to leverage smart technology. After all, AI’s capacity to track and adapt to individual behavior makes it a valuable tool. Used well, it enables marketers to deliver highly personalized campaigns. 

But AI-based marketing will only be as good as the data that fuels it, and few brands have their data in optimal shape.

So how is AI impacting marketers, and what can they do to ensure their data is fit for purpose? 

What AI Means for Marketing

Although everyone is eager to embrace AI, hype has made its meaning and uses difficult to decipher. Is it machine learning? Is it algorithms? Is it the materialization of the interactive home robot we were promised in the 1950s?

In a way it’s all of the above. But essentially, AI is a label applied to tech that automates tasks which previously relied on human cognitive ability. 

For marketers, its core use is simple: it covers any area that requires data-based decision-making. Many have already started to harness AI’s power: using it to optimize campaigns in real time, trade ads programmatically, and instantly deliver messages to consumers across a range of channels. 

Yet while these uses can save time and labor, effectiveness isn’t guaranteed. To be successful, marketers must build their efforts on a strong foundation of comprehensive data which helps them understand consumers and provide tailored, unified messaging — which isn’t something every company has. This goal is attainable in the era of connectivity.

Forming a Complete Customer Picture

With over half (62 percent) of US consumers owning at least one Internet of Things (IoT) connected device — such as a smartphone, TV or vehicle — user data is more abundant than ever. And when combined with other data sources, such as offline purchase records and in-store footfall, marketers can gain unprecedented insight into individual activity.

The problem lies in putting this data into action. As information is gathered from multiple online and offline sources it often falls into isolated silos, typically separated by channel. This makes it hard for marketers to create a complete view of specific consumers and their behavior, which also means they have a limited basis for their AI-fueled efforts. As a result, automated messages end up being not only irrelevant, but disjointed across channels.

To counter this, marketers must find a means to bridge silos and combine data streams, such as constructing a centralized data hub. In creating a single repository which gathers all data, marketers can pull the fragmented strands of consumer journeys together and produce an all-encompassing picture of individuals, including what they like, where they go, their unique needs and the kind of messages they find most relevant.

Using such insight, marketers can leverage the full potential of AI tech: delivering tailored messages that maximize consumer experiences and boost ROI.

Keep an Even Balance

Before marketers get carried away, however, it is important to note that with AI’s personalization potential comes responsibility. 

For instance, to promote the release of global blockbuster "Alien: Covenant," unsuspecting viewers were given a preview of nail-biting scenes from the movie. They were then addressed by name — and told to run. While this personalized experience, used by the UK’s Channel 4, was perfect in this case — when the aim was to shock and frighten — in the context of another product or everyday service, it’s easy to see how customers could considered it too creepy. 

Context is key with personalization and marketers need to make sure AI efforts strike the right balance.

Privacy is another factor to watch. Usage of consumer data is a hot topic — especially with the recently established EU-US Privacy Shield and imminent General Data Protection Regulation (GDPR). When the GDPR comes into force in May 2018, all businesses that deal with data from European citizens will need to comply. To maintain user trust and meet regulations, marketers need to carefully monitor areas such as data bias, application and algorithm transparency, and ensure compliancy throughout their practices.

In spite of the obstacles, the lure of AI-driven efficiency will convince marketers to dip their toes in the AI-fueled marketing waters sooner rather than later. By connecting silos and streamlining insight — while monitoring privacy and balanced personalization — marketers can ensure their data management places them at the head of the AI revolution.