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Right now, much of the attention is on how Generative AI tools like ChatGPT, DALL-E and Veo are influencing and changing businesses. Yet there are other advancements that will force an equally seismic shift: the capability to leverage ever more complex data for deep customer insight, hyper-personalisation, the rise of AI co-pilots, such as SAP’s Joule, segmenting customers in real-time, and of course, GenAI, particularly for automating manual processes and content creation. Underpinning these advancements will be one of the most significant developments – a recent and far-reaching piece of AI legislation, the European Union Artificial Intelligence Act (EU AI Act).
As brands venture further into this new AI territory, the view of future innovations and how to implement them can be hazy. Innovation happens so quickly.
So here’s what’s coming over the horizon, influencing how we use AI in marketing.
Data, data and more data
We can’t really talk about the future of AI in marketing without mentioning data. It’s the not-so-secret sauce that both underpins and drives AI to boost customer engagement. And its impact is huge.
AI can swiftly process and analyse massive amounts of data, eliminating the need for manual work and reducing human error in data collection. It converts data on products, sales, and customers into valuable insights that marketers can use to foster genuine engagement. This capability extends beyond retail, benefiting industries such as consumer products, sports and entertainment, utilities, travel and transportation, where understanding customer preferences and behaviours is crucial.
Global confectionery manufacturer Ferrara took this approach to create a modern omnichannel experience for consumers to build relationships with fans across its iconic brands.
Ferrara e-commerce and marketing IT director Dan Bartelsen said: “SAP Customer Experience Technology enables us with customer insights into consumer behaviour that tell us the types of promotions and sweepstakes that they really love. We use this technology to be smarter about how we interact with our fans. We can really have the opportunities to find the people we didn’t know existed that love our brands.”
Investing in customer data solutions from SAP and the SAP Emarsys Customer Engagement tools, resulted in a 59 percent increase in contactable customers and up to 20 percent above the industry email open rates, all while remaining 100 percent compliant with consumer privacy laws.
Meanwhile, global sportswear brand PUMA achieved five times revenue and 50 percent database growth within six months of adoption.
PUMA VP of e-commerce Rick Almeida said: “By leveraging AI and automation against its rich vertical first-party data, Emarsys allows brands like ours to generate greater insights into customer behaviours, create more consistent personalised journeys, and deliver them across all our consumers’ different touchpoints, whether online or offline within one single platform. Our partnership has not only transformed how we communicate with our customers but also allowed our marketing team to spend more time creating better engagement for consumers wherever and whenever they engage with our brand.”
These two examples demonstrate how AI can automate the data integration and consolidation process, dynamically updating a customer data platform as new data comes in from multiple sources. Sources can include ERP solutions, booking engines, commerce or POS platforms, customer service platforms, data warehouses like Snowflake, and data lakes such as those provided by Snowflake and Databricks. Activating this data in real-time with AI ensures a vastly easier true single customer view.
The difference in the future will be in the scale and speed at which all aspects of data management will happen. It is only going to get bigger and faster. This data tsunami, a data-driven approach to customer engagement and the continued adoption of AI technology in marketing means a renewed collaboration between Marketing and IT departments, moving beyond traditional roles. Instead of merely handling requests, IT teams will play an increasingly critical role in building and maintaining sophisticated MarTech stacks, ensuring seamless integration and functionality.
The iconic guitar manufacturer Gibson is already doing things differently. As Gibson head of marketing Sterling Doak explains: “Like many businesses with both DTC (direct to consumer) and B2B operations, we maintain multiple databases. My team (marketing) is now collaborating with our Enterprise Technology team (IT) to prioritise this issue. This has created an opportunity for marketing and technology to work closely on behalf of the business and collaborate in a way we previously did not. Marketing and IT are natural allies in building a robust consumer experience.”
Perfect AI-powered segmentation
Engaging customers across channels and reaching them with the right message at the right time is becoming more challenging for marketers. Traditionally, engagement between Consumer Products (CP) brands and consumers, for example, has been a one-way conversation, with brands pushing advertisements to drive awareness and purchases.
However, solutions like SAP Emarsys are now empowering brands to make every engagement more conversational. With more customer segments available, there is a growing need to address them individually. Without GenAI, this would be an overwhelming task, as creating the content required for true one-to-one conversations across all channels would be impractical.
Customers are often moving targets with multiple services vying for their attention. For example, a consumer may be loyal to a specific utility provider one moment, only to switch to a competitor offering a better deal the next. AI helps brands and services stay agile and responsive to these dynamics, ensuring they can maintain strong customer relationships across various industries.
The goal of direct engagement is to create an interactive, two-way conversation, driving engagement across channels at multiple touchpoints along the customer journey. Perfect AI-powered segmentation enables marketers to engage customers with timely and relevant messages. This is increasingly crucial as consumer behaviour diversifies across sectors like sports and entertainment or travel and transportation, where preferences can shift rapidly.
AI-powered segmentation means marketers will be able to speak to customers in real-time. It ensures that when they push a campaign live, they’re acting on the most up-to-date information, targeting customers based on what they’re currently thinking and how they’re acting in that moment, rather than insights from three months ago. In other words, it will elevate marketing from reactive to proactive.
Mention Me, a leading customer advocacy intelligence platform, is harnessing AI to predict a customer’s propensity for advocacy at any given moment, based on their previous interactions with a brand. When a customer, post purchase, has a high propensity to make recommendations, marketing communications will ask that customer to take certain actions such as refer a friend, leave a review, or post on social media – all of which drive customer-led growth.
If that same customer has a low propensity, they will instead be encouraged to make a second purchase, sign up for the loyalty program, or subscribe to the newsletter to drive deeper loyalty. AI is able to analyse the data and make the call as to whether a customer has a high or low propensity to advocate.
This AI-led approach has already enabled luxury retailer BrandAlley to gain a 23 percent increase in engagement rates and a 25 percent increase in repeat rates in a three-month period with no additional effort from the marketing team.
Next-level personalisation
What enhancements can we expect with AI? We’re talking next-level, hyper-personalisation: using increasingly deeper insights and real-time data combined with customer engagement platforms with embedded AI capabilities to deliver highly customised experiences and messages to individual consumers.
This new era of personalised customer experience will draw on detailed customer data including browsing history and purchase history to power tailored recommendations, personalised omni-channel experiences, and dynamic website content. Ultra-personalised CX goes further – it draws on predictive AI to add predictive analytics and contextual data, such as real-time engagement insights, to the mix to deliver recommendations that anticipate needs and create seamless cross-channel experiences.
Look forward to enhanced insights
AI will transform insights into customer behaviour through predictive analytics. Rather than just looking in the rearview mirror at previous trends, marketers can look into the future and accurately anticipate customer needs.
Using historical data combined with statistical modelling, machine learning and a 360-degree view of the customer, AI can predict what a customer will buy, when, through what channels, how much they will spend and even if they’re likely to churn.
Advances in natural language processing (NLP) will allow AI to better understand and analyse customer sentiments from social media, product reviews and other feedback mechanisms for even deeper insights into customer satisfaction and brand perception.
Alexa, improve my customer service…and marketing
In the future, AI chatbots and virtual assistants will have the potential to offer more human-like interactions and handle complex customer queries. Add to this AI’s ability to be consistent across all communication channels, and customers will receive the same high-quality service whether they reach out via email, chat or social media.
Customer service is just the start. The virtual assistants of the future have the potential to become essential co-pilots for businesses and marketers too.
Take SAP’s AI co-pilot Joule. Joule is an advanced natural language, generative AI assistant embedded into SAP business systems for swifter decision-making and driving operational efficiency across various functions. Expect AI co-pilots and assistants to appear in more of the systems marketers use.
Inspiring a shift change in AI use
One final factor shaping AI in marketing is not a technology development or a tool, but a new piece of legislation – the EU AI Act. Why should marketers in Australia care about a law adopted 15,000 kilometres away? Because this Act’s influence is vast. Not just geographically but also in its scope. It’s poised to become the global AI standard due to the “Brussels Effect” – where multinational organisations follow EU laws globally due to the difficulty of sidestepping them. The Act not only sets the rules around AI but inspires a shift in how organisations approach AI. The impact will be felt by marketers everywhere.
At first glance, the legislation might appear limiting, hindering the application of AI. But by creating an ethical framework that prioritises intellectual property, consumer privacy and data protection, it does the opposite. It gives brand marketing teams the confidence to build an aligned strategy and innovate and experiment with AI responsibly, knowing that their data and IP are safe. It will empower retail brands like never before.
Customer focus – the key to navigating AI
We asked Australian marketers about their use of AI and discovered that 77 percent are increasing their AI investments in the next year to boost customer engagement. These marketers are getting on the front foot, responding to consumers who want to see AI technology and applications improving their retail experiences.
Still almost a third are not upping their investment in AI tools. Why? Most likely because it’s either too difficult, too uncertain or too hard to stay on top of the latest developments.
These uncertainties are why the EU AI Act should give marketers confidence to use AI. Organisations like SAP Emarsys have embraced this Act and are helping by making AI a reliable and trusted part of its customer engagement platform.
Having a customer obsession can also help marketers navigate this rapidly shifting world. Customer obsession means putting customers front and centre of every single action, so that marketers can give them precisely what they want quickly, and seamlessly. At every touchpoint, every time.
When the direction of travel seems uncertain, this focus on customers should be the guiding light. It will help to mitigate uncertainties and ensure marketers stay on track, whatever the future of AI in marketing holds.
Thomas Harris is the chief revenue officer at SAP Emarsys. For more than 10 years, Harris has scaled high-performing teams from a regional to a global level. With a proven track record of driving triple-digit growth and supporting leading global brands to realise their greatest personalisation and omni-channel aspirations, Harris is an expert in the field.
Also, read the other two parts of Harris’ Marketing Mag exclusive three part series on AI.
Part one: AI isn’t about automating tasks, it’s about transforming them.
Part three: The marketers’ roadmap for implementing AI.
