In the digital age, it’s possible for marketers to collect more information to power their strategies than ever before. So much data, in fact, that it’s beyond the capacity of human marketing professionals alone to make sense of it all. But the majority of that data is underutilized in most marketing organizations. And a mere six percent of marketers say their current tools and approaches are working sufficiently well, according to one survey.
Machine learning systems can study massive volumes of data to uncover correlations, make predictions, and identify patterns. And unlike previous technology innovations that have changed a particular aspect of marketing – search engine optimization or programmatic media buying, as examples – machine learning has the potential to transform nearly every aspect of the function, from customer intelligence and market research to pricing and promotion to distribution and service. In fact, 80% of marketing executives believe artificial intelligence will revolutionize marketing over the next five years. More than half (55%) expect AI capabilities to have a greater impact on marketing than social media ever had, according to a 2016 survey.
Amazon, already a master of machine learning, is well known for its AI-driven recommendation engine. But in a recent letter to shareholders, CEO Jeff Bezos pointed out that machine learning is also powering the company’s demand forecasting, product search ranking, personalized offers, merchandising placements, translations, and much more.
Marketing – The Ideal Entry Point for Machine Learning
Few corporate marketers have the machine-learning budget of an Amazon. Just one in 10 marketing executives is using AI today, according to a recent survey. But marketing may be the ideal entry point for machine learning in the enterprise where it can be applied to optimize internal performance, improve customer engagement, and uncover new areas of growth. Just think of all the customer and marketplace data streaming into companies today – point-of-sale transactions, online purchases, click-through rates, browsing behavior, social media interactions, mobile device usage, geolocation data. And as more products become Internet-connected, those data volumes will increase further.
Marketers can turn to machine learning for better customer segmentation, categorizing customers into much smaller groups with similar behaviors and preferences. Machine learning can help marketers deliver predictive campaigns that anticipate consumers’ responses with greater accuracy and precision over time, increasing the effectiveness of marketing campaigns.
Machine learning can supercharge brand intelligence efforts, enabling companies to scan and analyze not just traditional news and social media sources but other data – structured and unstructured, online and off – about a company. As media attention and spend shifts from text and static images to video, machine learning can help CMOs scour visual media for brand exposure. Companies spent some $60 billion on global sponsorships in 2016, for example, and machine learning can verify the return on that investment.
Machine learning systems can also spot trends before they become readily apparent They will be used to alert marketers to customer defections before they happen based on analysis of churn patterns, predict the next best offer to make, determine the optimal price for sales conversion, or forecast the lifetime value of a customer or product line.
Remember Human Judgement
But care must be taken. Machine learning can be astonishingly good at helping marketers see – and react to – patterns in data they would otherwise have missed. But not every new pattern needs to be used. Sending congratulatory messages or offers to women who aren’t ready to reveal their pregnancy is a real-world case in point.
If used prudently with an added dose of human judgment, machine learning will be a powerful new tool for marketing. Paradoxically, it may be that machine learning is what enables marketers to truly understand the humans on the other side of their strategies.
For more on humanizing your marketing with machine learning, see 5 Steps to Your Customer’s Heart with Emotionally Aware Computing.