Firms have so far used a mix of human intuition and traditional analytics to engage with their customers. But the advent of artificial intelligence (AI) and more sophisticated data interpretation is heralding a new era of business-customer interaction.
Instead of merely responding to expressed needs and wants, firms will proactively anticipate them, reaching a level of foresight never experienced before. This will revolutionise the nature of customer interactions and reshape industries.
Here are ten predictions as to how the multifaceted applications of AI – including generative AI – will transform marketing, and examples of how such changes are already underway.
1. Predictive analytics will anticipate clients’ desires
Forget mere lead scoring. AI-powered predictive analytics will anticipate desires before they are articulated. AI might craft multifaceted client profiles, predicting not just purchasing behaviours but also emergent needs. It will capture biometric signals, such as eye movement on a webpage or scroll speed, to decode a user's unsaid preferences and emotional reactions.
Consider the titan of streaming, Netflix. It already employs sophisticated machine-learning algorithms to anticipate viewers’ preferences. Beyond the shows a user has watched, it looks at subtler cues like when they paused a show, which episodes they skipped and how long they pondered over a particular title.
Such intricate data points allow Netflix to predict not just what a viewer might watch next, but also emerging content preferences. It can then tailor its original programming accordingly.
2. AI-driven content will birth next-generation storytelling
AI’s growing role in content generation will focus on resonance. AI might tailor content narratives in real-time, adapting to live user interactions. Such content will be based not just on overt actions but also on underlying subconscious preferences and unspoken sentiments of users.
In this regard, OpenAI stands out as a trailblazer. Its advanced language models have begun to lay the groundwork for content that dynamically adapts to user input by detecting underlying user sentiments and responding accordingly.
For example, these models can dynamically create short stories, adapt characters or even propose plot twists, while ensuring the narrative resonates with the user's unspoken preferences. Such innovations promise a future in which content, be it in literature, gaming or virtual experiences, can foster a high level of emotional connection between producers and end consumers.
3. Programmatic advertising will become more precise and predictive
The future of programmatic advertising promises not just precision but also contextual relevance. Ads will adjust to live situational contexts, beyond an analysis of explicit clicks and page views. Instead, AI will interpret implicit behaviours – like the time spent hovering over an ad or the subtle patterns of navigation – to understand and align with the deeper, unspoken interests of the audience.
Google Ads is at the forefront of this transformation. Beyond analysing explicit cues such as clicks, its algorithms are now delving into more implicit patterns like how long a user hovers over an ad or the trajectory of their digital navigation. This paves the way for ads that not only align with users' current interests but also predict their futures ones.
4. Hyper-personalisation will apply to the entire digital journey
With AI, personalisation will mean crafting entirely unique digital experiences that account for the complexity and ambivalence of every individual. Beyond analysing click-through rates and purchase histories, AI will seek to understand the emotional landscapes of users. To this end, it will draw from nuanced data points like interaction speeds, mouse movements or even biometric feedback where available.
Spotify serves as a pioneering example of this trend. Its algorithms can interpret data points like the pace at which songs are skipped and even the time of day tracks are played. This allows it to discern whether a user might be seeking energetic tunes for a workout or mellow sounds to unwind.
Moreover, by correlating listening habits with life events, such as the addition of lullabies potentially indicating a new baby in the family, Spotify can suggest relevant content beyond just music. With its tailored digital journey, the Spotify experience can feel like a trusted friend who knows your evolving tastes and life phases.
5. Seeing through the user's lens will move from talk to reality
Advanced visual recognition holds promise for deeply intuitive product recommendations. Beyond recognising products and brands, AI will interpret implicit visual cues from user-generated content. For instance, photo backgrounds, clothing colours or even subtle moods conveyed in images can reveal unsaid preferences or sentiments. All this will inform more nuanced marketing strategies.
Pinterest offers a compelling glimpse into this trend. The platform's ability to interpret the array of visual content uploaded by its users has given rise to highly intuitive product and style recommendations. For example, a user pinning serene landscapes might enjoy suggestions related to mindfulness practices or calming home decor, aligning with their aesthetic leanings.
6. Email marketing will set conversations, not campaigns
AI could transform email marketing from broadcast-like campaigns to conversations that feel like a dialogue. Beyond open rates, AI will employ sentiment analysis on user responses. Even when users don’t actively engage with an email – no clicks, no direct responses – their passive interactions can provide AI with insights.
HubSpot is a prime example of the transformative power of AI in converting generic campaigns into meaningful dialogues. The company uses AI to assess passive interactions, like the duration an email remains open or the frequency of revisits. This allows it to decipher interest (e.g. contemplation).
7. Chatbots will pave the way for more ubiquitous meaningful engagement
The allure of chatbots will transcend mere 24/7 availability. AI-driven chatbots will increasingly capture and understand the emotional undertones of user queries by discerning unsaid feelings, such as frustration or excitement. By responding with empathetic undertones, chatbots will foster a deeper, more human-like connection without ever saying that they understand emotions.
Intercom, for instance, is harnessing AI to transform chatbot interactions from transactional exchanges to meaningful dialogues. The company’s advanced AI-driven chatbots not only respond to user queries but also gauge the emotional nuances behind them.
Furthermore, by referencing past interactions, its chatbots provide users with a sense of continuity, akin to conversing with a familiar contact. They can also address unspoken needs, such as offering a tutorial when a user appears confused about a feature.
8. Voice will usher in a new mode of digital interaction
As AI becomes more adept at voice recognition, it will also tap into the emotional undertones of voice inputs. Firms will then be able to tailor responses or offers that resonate with a user’s emotional state at that moment, be it hesitation, excitement or doubt.
Take Amazon's Alexa. Its sophisticated AI continually refines its understanding of a user's emotional state through subtle variations in tone, pitch and pacing. Whether detecting a hint of hesitation or sensing excitement in a user's voice, Alexa tailors its responses accordingly.
For instance, someone sounding rushed might receive more succinct answers, while a relaxed user might receive a more detailed response. This exemplifies the burgeoning potential of voice-driven AI in reshaping digital interactions.
9. Dynamic pricing and market dynamics will converge
Dynamic pricing may evolve into a living system, mirroring real-time market nuances. AI won’t just track sales and stock. Using a confluence of news, social media sentiment and other subtle indicators, it will grasp the “mood” of the market and be able to shape pricing accordingly.
Uber's dynamic pricing model offers a glimpse into the future. Instead of adjusting prices according to mere demand and supply, the company’s AI system is designed to discern subtler cues from the environment.
If there’s a surge in social media posts about a big event, AI can predict a spike in demand. It can also detect users’ hesitations when prices soar and fine-tune them to maintain customer satisfaction, thus striking a balance between business profitability and customer-centricity. While controversial, this approach showcases the potential of AI to adjust to the market's ever-changing pulse.
10. Sales forecasting will meld instinct with insights
While AI will predict market trends, the human touch will infuse these forecasts with grounded realities. The harmonious confluence of AI insights and human intuition promises a future of balanced, robust sales strategies.
Salesforce exemplifies this fusion of human instinct with AI-driven insights in the domain of sales forecasting. Aside from analysing vast amounts of sales data, its Einstein AI platform can incorporate nuanced signals, such as buyer hesitation.
While its AI system offers predictive insights, the final decision often lies with the human sales strategists who bring their intuition and experience into play. This way, Salesforce ensures that its sales strategies remain both data-driven and attuned to the real-world concerns of its clients.
From seeing beyond the overt to hearing the unsaid, the next frontier of marketing is less about speaking and more about listening – listening to the whispers of the market and the muted desires of clients. As we stand poised to leap into this new world, we must be guided not just by profit but by transparency and ethical stewardship. Firms will need to tread with caution in light of data privacy concerns. Transparent data handling practices, regulatory compliance and trust will be critical. Those who master this will not just navigate but define the future, setting the gold standard in the AI-augmented world of sales and marketing.
A version of this article appeared first in The European Business Review.
Edited by:Isabelle Laporte
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