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.
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.
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.
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.
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.
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.
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).
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.
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.
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.
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.
Joerg Niessing is a Senior Affiliate Professor of Marketing at INSEAD. He is co-director of INSEAD programmes Leading Digital Marketing Strategy and B2B Marketing Strategies.
First Published: Nov 30, 2023, 11:00
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