AI is not as scary as it seems

Artificial Intelligence (AI) is one of these terms people hear about, and even talk about, but is not always understood. Today’s automation platforms ensure marketers don’t require in-depth knowledge of how AI works, instead, they can focus on the possibilities it presents.

AI’s image hasn’t been particularly good. People envisage a time when robots become sentient and take over the world. Or in today’s reality, many marketers might be fearful that AI is on track to take over their jobs. In truth, AI can be very basic – for example, AI controls what ends up in your spam inbox.

In essence, AI and the machines that use it will only ever be able to operate within the strict parameters set by programmers. Machines can’t decide they want to learn a new skill and go teach themselves. Your Alexa will play you music and help with recipes – it isn’t trying to take over the world.

AI can enable the marketer to operate at greater speed, accuracy, and efficiency. Using AI means marketers can scale the number of campaigns and journeys they deploy, but without having to make these decisions manually. AI determines which campaign to send to each customer, based on the different scenarios it has been trained to respond to. AI models can quickly analyse behavioural data and determine the next-best-action, optimising marketing automation.

This is where machine learning comes in. AI becomes more successful the more data it has to learn from. This is nigh-on-impossible for a human to perform, so the implications for marketers are game-changing. Instead, marketers can concentrate on what matters most: communicating with customers and nurturing relationships.

A crystal ball
Predictive analytics can analyse thousands of customer journeys, allowing the AI to accurately predict key moments in the customer lifecycle. If you’re a marketer who has organised your data and is already offering personalised communications, AI and automation can take this to a whole new level.

Combined, AI and automation can help understand how each individual customer behaves, predict how they will act in the future, and automate relevant messages to those customers at the right time. This is all about predicting behaviour and then taking specific actions to support, or influence customers through the next steps in their journey.

For marketers, a great opportunity is to use AI to help identify and grow your most important customers. A predictive model picks up behaviours of current VIP customers and uses this information to determine who among the rest of your customer base is likely to become a VIP. Using personalised communications, you can segment and nurture these customers into becoming VIPs quicker and easier.

Travis Perkins, a builder’s merchant, used AI and predictive analytics to increase its VIP customer segment by 65%. In this example, the VIP model searched for patterns of behaviour that reflected the behaviour of current VIPs. This allowed Travis Perkins to use multi-channel communications to engage those customers, encouraging them to join this VIP customer segment. Machine learning ensures these algorithms are constantly evolving and becoming more accurate to provide even better insights for your brand.

Increasing VIPs means increased engagement and increased spending – so they are an important segment for any brand. The same was true for Travis Perkins, which saw an overall increase in its VIP segment to 5.3% of its customer base.

Predictive analytics can be used at multiple points of the customer lifecycle. AI can also be used to help reduce the risk of customer churn by identifying customers showing patterns of behaviour that show they may eventually stop purchasing from your brand. These customers will then be automatically targeted with personalised, individualised and contextualised promotions to restore loyalty.

The role of AI in marketing will continue to expand. With brands experimenting with everything from chatbots powered by natural language processing to spotting customer trends. Additionally, AI can be used to maintain the quality of data in a customer relationship management system, identifying customer records where errors or duplicates may exist.

This is good news and nothing to be scared of. Marketers don’t need to retrain as data scientists or programmers or feel at risk in their roles. For marketers, AI can be your new best friend, and predicting customer behaviours is much easier than you think. 

Rachael Kotadia is marketing director at RedEye.