With the rapidly evolving world of digital marketing, firms are constantly searching for new ways to engage consumers, personalise interactions and optimise their time and efforts. Enter Artificial Intelligence (AI). This has been an absolute game-changer for marketing automation, revolutionising the way brands communicate with audiences.
It’s no longer science fiction. From chatbots and predictive analytics to hyper-personalised mail campaigns and intelligent customer segmentation, AI solutions are turning marketing campaigns smarter, faster and more efficient.
Traditionally, marketers employed data-driven insights, segmentation by hand, and A/B testing to tweak their strategies. AI accomplishes this on a much larger scale by scanning huge volumes of consumer data in real-time, finding patterns, and delivering customised content with unparalleled precision.
Bryce Hall, associate partner at strategy and consultancy firm, McKinsey & Company, says the initial wave of excitement and novelty around generative AI is evolving into an intentional focus on how to create value from these technologies.
“Executives are rightfully looking for a return on their AI investments,” he explains. “In many cases, they are paring back their strategies from trying to apply gen AI everywhere to prioritising the domains that have the greatest potential.
“We’re now far enough into the gen AI era to see patterns among companies that are capturing value.”
One significant difference, he notes, is that these companies focus as much on driving adoption and scaling as they do on the up-front technology development. This is not just hand-waving. Instead, they are following specific management practices that enable them to be successful – such as developing a clear road map for scaling, establishing and tracking KPIs, and driving change management by ensuring senior leaders are actively engaged in driving gen AI adoption.
“The fact that so many companies continue to struggle with these management practices is a testament to the fact that they’re not so simple to get right,” Hall says.
“In addition, companies that report capturing value from gen AI are ‘rewiring’ their business processes to effectively embed gen AI solutions while appropriately incorporating.”
Key AI technologies transforming marketing automation
- Chatbots & Conversational AI – AI-powered chatbots are revolutionising customer interactions by providing instant, personalised responses and guiding users through the sales funnel.
- Predictive Analytics – AI algorithms read historical data to forecast future consumer actions, enabling marketers to anticipate trends and optimise campaigns. Predictive analytics helps businesses budget effectively and optimise ROI.
- Personalised Content & Email Automation – AI enables hyper-personalised content delivery by studying user behavior and preferences. AI-based email marketing tools can personalise subject lines, offers, and content to optimise open and conversion rates.
- AI-Powered SEO & Content Generation – Search engines have grown smarter, and AI-based content creation tools like GPT-4 can help marketers create well-written, SEO-friendly content faster than ever. It can help keep brands top of mind in an increasingly competitive online marketplace.
- Automated Social Media Marketing – AI tools like Hootsuite and Sprout Social monitor social media trends, suggest best posting times, and even craft auto-responses to maintain audiences’ interest.
AI enhances efficiency by reducing time spent on monotonous marketing activities, giving teams the liberty to focus on strategy and imagination. It can dramatically improve customer experience through personalisation-driven interactions, making experiences more relevant and efficient. AI can also empower marketers to make better-informed decisions, optimise campaigns and boost conversions with data-led insights. On top of all this, it makes it possible for small and large enterprises to grow their marketing activity, leveraging advanced strategies without having to use huge teams or significant resources.
Michael Chui, senior fellow at McKinsey & Company notes that things are moving fast in the field of AI. “But even as we try to keep up with the pace of technological advancements, we are also learning that AI only makes an impact in the real world when enterprises adapt to the new capabilities that these technologies enable,” he says. “That’s what we are hearing in our individual conversations with business leaders, and it is also reflected in the global data we have collected in our latest survey.”
The use of AI has continued to increase, he explains, and more companies are using AI in a growing number of business functions. They are using gen AI to reinvent aspects of their enterprises: marketing and sales, product and service development, service operations, corporate IT, and software engineering. They are also increasingly reporting top-line and cost benefits from deploying gen AI solutions. And many are now using gen AI in their daily lives.
Chui adds: “Interestingly, it’s C-level executives who are leading in their own use, but their employees could be much more ready to use gen AI at work than their C-suite leaders expect.”
What 5 big brands are doing with AI in marketing automation
Amazon: Amazon uses AI to deliver personalised shopping experiences by analyzing customer browsing, purchasing history, and preferences. Its recommendation engine suggests products based on these insights, increasing conversion rates and average order value. The system also adapts in real-time to customer behavior, creating highly relevant recommendations that improve customer satisfaction and drive sales.
Netflix: Netflix’s AI-driven recommendation system uses data from user activity, like watched content and ratings, to suggest personalised shows and movies. This enhances user engagement by offering tailored content, leading to longer viewing sessions. Netflix’s machine learning algorithms continuously refine recommendations, keeping the platform addictive and customer-centric.
Spotify: Spotify utilises AI for personalised playlists, such as ‘Discover Weekly’ and ‘Release Radar’, which curate music based on user listening habits. AI algorithms analyse music preferences and listening patterns to recommend songs, keeping users engaged and enhancing the overall experience by introducing them to new music they are likely to enjoy.
Nike: Nike uses AI to personalise customer experiences both online and in-store. Through its Nike Training Club app, AI recommends workouts based on user preferences and fitness goals. Additionally, Nike’s website and app offer personalised product suggestions, with AI analyzing purchase history, browsing behavior, and even social media activity. This ensures customers receive relevant recommendations, improving engagement and boosting sales.
H&M: H&M uses AI to optimise email marketing by sending personalised product recommendations based on customer browsing behavior, purchase history, and style preferences. AI analyzes customer data to deliver relevant and timely promotions, increasing engagement and driving sales while enhancing the customer experience by presenting them with products they’re more likely to buy.
The future of AI in marketing
While AI offers immense benefits, it also presents challenges. Data privacy concerns, algorithm biases, and the risk of over-automation are key issues that businesses must address. Marketers must balance automation with human oversight to ensure ethical AI usage and maintain brand authenticity.
It’s a technology that will only become more sophisticated, integrating deeper with augmented reality, voice search and customer sentiment analysis. As technology continues to evolve, businesses that embrace AI-driven marketing automation will stay ahead in the competitive landscape.
Alexander Sukharevsky, senior partner and global co-leader of QuantumBlack, AI by McKinsey, says: “The more we see organisations using AI, the more we recognise that it takes a top-down process to really move the needle. Effective AI implementation starts with a fully committed C-suite and, ideally, an engaged board. Many companies’ instinct is to delegate implementation to the IT or digital department, but over and over again, this turns out to be a recipe for failure.”
There are several reasons for this, he explains. The first is that getting real value out of AI requires transformation, not just new technology. It’s a question of successful change management and mobilisation, which is why C-suite leadership is essential. It’s also a potentially expensive transformation, requiring intensive use of sometimes scarce resources and talent.
“A lot rides on how those resources are made available,” he explains. ”And that’s an executive-level call requiring nuanced decision-making that reflects the balance organisations must strike between efficient resource use and broad empowerment – a balance that must be constantly reevaluated as the technology and organisation evolve.
“As organisations become more fluent with AI, it will essentially become embedded in all functions, leaving leadership to focus on higher-level tasks like impact monitoring and talent development rather than on implementation.”
Investing in education and training is going to be essential, suggests Conor Coughlan, CMO at software firm Armis.
“But, as modern marketers, I’m confident that we can all easily bridge the gap between traditional marketing practices and AI-driven or powered strategies, ultimately making the best use of the AI tools and technologies to enhance our programs and overall decision-making.”
In theory, the array of AI tools available promises to simplify our lives, he explains. “Time will tell. But I believe the future is undoubtedly bright. Just as we previously transitioned from analogue to digital, marketers will pivot once more to adapt to this new world.”
