AI unleashes hyper-personalisation, hyper-relevance
By Tom Kaneshige, CMO Council Chief Content Officer. Can AI and machine learning bring about the promise of one-to-one marketing at scale? It’s already happening for a lot of brands.
By Tom Kaneshige, CMO Council Chief Content Officer. Can AI and machine learning bring about the promise of one-to-one marketing at scale? The short answer: It’s already happening for a lot of brands. Every day, every minute, every second, millions upon millions of customers receive super relevant messages, individually crafted, over the right channel and in their moment of need.
“The leading edge of customer strategy to grow customer value today is AI-enabled personalisation,” says Tom O’Toole, associate dean for executive education at Northwestern University, Kellogg School of Management, and senior advisor for McKinsey, on the Proof of Concept podcast. “Demonstrably, personalization works because of relevance … and AI allows us to be extremely hyper-relevant to the individual.”
AI-enabled personalisation — or simply AI personalisation — takes many forms. Perhaps the most obvious are product recommendations and targeted ads based off of prior purchases, online intent behaviour and patterns in the data. When a customer visits a website, for instance, the AI algorithm taps into an array of data sources to serve up relevant and unique information that increases the odds of them hitting the buy button.
On the frontlines of AI personalisation, smart chatbots equipped with natural language processing and sentiment analysis tailor conversations to individual customers, not merely spout generic, scripted responses. If this makes you wonder about the marketing potential for ChatGPT, you’re not alone. (For more, check out Can CMOs Capitalize on ChatGPT?)
O’Toole also envisions Fitbits and wearable medical devices, such as glucose monitors, advising people on how to live healthier lives. Before setting out on a day-long hike, would you dismiss a personal (and private) message that your blood sugar level is dangerously low? In a B2B scenario, AI analysing Internet of Things data on a tractor can help a farmer operate more efficiently and profitably.
“AI personalisation enables us to create hyper-relevance and even, to coin a term, predictive relevance, meaning we can discern something that’s going to be relevant to the customer before she or he even realises they’re going to need it,” O’Toole says. The goal is to move from episodic transactions to a continually connected customer relationship.
Data capacity is key
But before CMOs can harness the power of AI personalisation, marketers need baseline customer data capabilities. These range from having individually identifiable customers, to associating all transactions with the same customer, to tracking ongoing flow of data. That is, you have to be a high-velocity data marketer. In a recent report from CMO Council and GfK, we define the high-velocity data marketer as a marketing organisation that can quickly acquire real-time, relevant data signals; produce data insights that detect sudden disruptions in customer and market behaviour; and close the gap between data and insights, insights and action.
Unfortunately, there are too few high-velocity data marketers. Nearly two-thirds of all marketers are only moderately confident (or worse) in their data, analytics and insights systems. To learn more about how to become a high-velocity data marketer, download the free report from the global CMO Council. One of the hallmarks of a high-velocity data marketer is the pervasive use of AI and machine learning, especially in personalisation. Our study found that 30% of top data marketing performers use AI in multiple systems, whereas only 4% of bottom performers say the same thing. AI is a clear line of demarcation, but there’s still a long way to go.
The good news is that AI personalisation has become more accessible to companies of all sizes, thanks to SAAS tools becoming widely available. After years of hype about AI transforming marketing, followed by lacklustre adoption, the tide indeed appears to be turning. Demand Spring released a report showing that 41% of B2B marketers planned to use AI tools last year – a leap from 18% in the year prior. “This is not about operational or technical efficiency — it’s about growing customer value,” O’Toole says. “When we connect connected customer relationships with ongoing, real-time flow of information with AI personalisation, it changes the whole ballgame.”
*This column was first published on CMOCouncil.org.
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