This article appeared in MartechView. Read it in full here.
Beyond segmentation: AI and real-time data finally deliver truly personal experiences, aligning brands with consumer values and intent.
Marketers have been chasing personalization for years, but what was long touted as tailored outreach was just segmentation in disguise: grouping consumers into broad demographic-based categories rather than engaging them based on unique values, intent, or preferences. Personalization either missed the mark entirely, offering generic, one-size-fits-all messaging, or it veered into creepy territory, with ads that stalked users across the internet after searching for a specific product just once. Despite years of attempts to get it right, true personalization has struggled to become a reality.
Why? There are several reasons. Firstly, legacy technologies and traditional datasets lacked the sophistication required to go deeper than surface-level signals. Marketing teams used to be forced to work with fragmented, outdated data that painted only a partial picture of the consumer or reflected their past preferences, not today’s reality. Certainly, data lagged the up-to-the-minute view required to stay ahead of consumers and their reaction to 24-hour news cycles and unprecedented uncertainty.
But even with better datasets and tools at marketers’ disposal today, human limitations can still derail the progress of achieving personalization. Some marketing professionals tend to fall back on flawed assumptions and rely on broad demographics like gender, age and income instead of more nuanced insights like an individual’s values. Some marketers are either hesitant to embrace new technologies like AI and machine learning to power an understanding of individual consumers, or don’t know how to use this technology effectively and safely. In fact, nearly half of marketers admit they don’t know how to use generative AI safely, and don’t know how to get the most value out of it. This could result in missed opportunities to create full-picture, individualized experiences at scale.
But AI is here to transform brand teams and ad agencies. Understanding the distinction between predictive and generative AI and learning how best to use each in the right context is necessary to keep pace. Thanks to AI and its ability to analyze vast amounts of data and connect marketers with consumers based on rich, real-time information, brands can now tap into who people actually are and how they behave, not just drive insights based on what they clicked on last week.
Consumers want to see ads that align with their values and show up in places where they already spend time online, versus one that makes assumptions based on their age or zip code. One feels relevant, the other feels lazy, and consumers can tell the difference. Recent case study data underscores how powerful personalization can be: one brand saw a 20% increase in conversion to a premium product when 88% of website visitors received a personalized experience. So, when done right, personalization isn’t just a marketing tactic, it’s a strategic advantage.
Today, with AI and advanced, real-time data, marketers can achieve what’s long been considered the dream outcome: personalization that truly feels personal. So, let’s dive into what it takes to make the promise of AI-driven personalization a reality.
Old Rules, Out. AI, In.
Whether marketers like it or not, they have come to a turning point. Some might be reluctant to ditch the playbook they have become so accustomed to over the years, including broad segmentations, static personas, and a lot of guesswork. We’re now in a time where AI is understood in the mainstream, and with 71% of consumers now expecting individualized experiences, brands are under pressure to rise to the occasion. Marketing professionals need to embrace the inevitable, which starts with AI. For some, that might mean letting go of long-standing assumptions about who their audiences are and what they are looking for. Instead, they must trust that safe AI can uncover real consumer truths.
AI offers more than just efficiency for marketing teams; it provides a depth of opportunities for customer engagement. Unlike traditional segmentation, AI allows a real-time, nuanced view of a consumer by tying ground truth to a massive wealth of real-time behavioral information. That real-time basis enables marketers to connect with people not just based on actions, but in the context of who they are and what they care about right now.
When exploring possibilities for personalization with AI, the best approach is to start small, such as by testing a personalized social campaign for a specific audience. This provides the opportunity to demonstrate value to your team and build confidence in the results. Once you see the impact, it becomes easier to scale those efforts across more and more channels to gradually build towards a fully personalized, AI-forward marketing strategy.
Turning Real-Time Insights into Impact
The success of AI-powered personalization doesn’t just depend on the technology itself, but on the quality of data feeding it and the way the end-product translates to activation. When AI is fed outdated or incomplete information, the insights it produces can quickly become irrelevant or misleading. AI models that learn from fresh inputs can help marketers move beyond generalized insights and respond directly to the real conditions their customers are navigating.
Consider retail purchasing behavior, for example. If a brand relies on general back-to-school spending data to predict this year’s patterns and shape this year’s campaigns, it will most likely miss the mark completely. Individual consumers’ preferences and priorities will change distinctly due to pressures like inflation, a new political administration in office, and new cultural perceptions. A once loyal customer may be cutting back on non-essentials due to tariff-related price fears; another may reevaluate brand choices based on ethical or political values that weren’t previously as influential.
This is why individual, real-time data is critical. Best-in-class AI models use current behavioral signals to reflect what specific people are thinking and feeling today, not six months ago. And identifying specific consumers who align with a certain brand strategy and are most likely to engage enable marketers to take meaningful action, and activate personalized, high-impact campaigns that will resonate with today’s consumers.
Achieving Personalization that Lives Up to Its Name
For too long, personalization has fallen short of its promise, relying on outdated technology, tactics, stale data, and general assumptions. Marketers have access to richer, real-time insights due to how accessible AI has become, giving them a chance to move beyond those legacy methods and deliver the personalized, individual experiences consumers have been expecting all along.
By combining high-quality data with deep psychographic consumer intelligence, brands can finally move away from boring, generic messaging for good — avoiding blending in with the hundreds of other generic ads consumers are exposed to daily. In summary, the key is not knowing what consumers clicked on last week, but what makes them engage with a brand, and what their current actions and values tell us about what they will do next. The tools are here, the data is available, and it’s an exciting time for marketers to ensure personalization lives up to its promise finally.
