Right Message, Right Time: How AI is Transforming Modern Marketing
Written by
Jacob Zweig, Managing Director
Published
April 1, 2025
Today’s customers don’t just want personalized experiences—they expect them. Whether shopping online, engaging with content, or exploring new services, people are looking for brands that understand their needs and speak to them on an individual level.
The problem? Traditional batch-and-blast marketing simply doesn’t cut it anymore. Generic messages sent to broad audiences risk being ignored—or worse, driving customers away.
To stay competitive, brands must move beyond one-size-fits-all campaigns and embrace AI-driven personalization. By harnessing the power of first-party and third-party data, businesses can gain deeper insight into customer behavior and deliver targeted, real-time messaging that increases engagement, drives loyalty, and boosts long-term value.
At OneSix, we help companies put data to work—building smarter, adaptive marketing strategies that deliver the right message to the right customer at exactly the right time. By integrating AI into their marketing strategies, our clients are unlocking measurable, data-backed results:
Fueling Personalization with First- & Third-Party Data
Data is more than just a business asset—it’s the foundation for delivering relevant, high-impact customer experiences. By combining first-party and third-party data, brands can unlock deeper insights, close data gaps, and build smarter, more personalized marketing strategies.
Higher-Quality Insights for Better Customer Profiles
First-party data—collected directly from customer interactions across websites, apps, and transactions—offers high-quality, trustworthy insights into individual behaviors, preferences, and purchase history. This rich data allows brands to build detailed customer profiles and target specific segments with precision.
When paired with third-party data, which provides broader market context and behavioral trends, these profiles become even more robust. The result is a more complete view of each customer and better-informed marketing decisions.
Enhanced Experiences and Differentiated Value
First-party data helps identify customer needs, pain points, and preferences in real time—allowing brands to deliver timely, relevant offers and personalized recommendations. This not only improves the customer experience but also builds long-term loyalty.
Third-party insights enhance this by offering visibility into external factors—like competitive activity, seasonal trends, or consumer behaviors across other platforms—enabling brands to refine their value propositions and stand out in a crowded market.
Smarter Targeting and Hyper-Personalization
A combined data approach allows brands to fine-tune their targeting strategies. First-party data provides individual-level detail, while third-party data offers a broader lens into market behavior.
Together, they enable hyper-personalized campaigns—whether it’s tailoring product recommendations, suggesting relevant content in real time, or customizing messages for specific audience segments across digital channels.
Predictive Analytics That Drive Growth
While first-party data offers a historical lens into customer behavior, third-party data adds predictive power when fed into AI models. This combination supports:
- More accurate demand forecasting
- Dynamic pricing strategies
- Early identification of churn risks
- Personalized offers delivered proactively
By leveraging both datasets through AI, brands can make smarter, faster decisions that anticipate customer needs and drive revenue growth.
Smarter Engagement Through AI
AI is fundamentally changing how brands understand, target, and engage with their audiences. From acquiring new customers to deepening relationships with loyal ones, AI-driven models enable personalized, data-informed strategies that deliver measurable results across the customer journey.
Customer Segmentation Modeling
Segmentation powered by AI goes far beyond traditional demographic-based grouping. For unknown or prospective users, techniques such as clustering and lookalike modeling allow brands to generalize insights from known customer behaviors to broader audiences across digital platforms. These models help define high-value segments and guide user acquisition strategies.
For known users, AI enables dynamic segmentation based on up-to-the-moment behavioral data, allowing for hyper-targeted messaging that evolves as the customer does.
Real-World Example
A retail brand may use lookalike modeling to identify new prospects who mirror the behavior and preferences of their most valuable customers, tailoring digital advertising to attract high-intent buyers.
Customer Propensity Modeling
Propensity models leverage a wide range of data—including behavioral, contextual, and third-party inputs—to predict the likelihood of specific customer actions. These models help marketers identify which customers are most likely to purchase, upgrade, convert, or churn, allowing for more effective targeting and optimized marketing spend.
With AI, marketers can prioritize offers, customize messaging, and allocate resources based on real-time intent rather than static assumptions.
Real-World Example
A SaaS company could use propensity scoring to identify which website visitors are most likely to sign up, and immediately serve personalized trial offers through digital ads or email campaigns.
Real-Time Personalization
When engaging with known customers, AI plays a critical role in determining what to do next. By combining models such as Lifetime Value (LTV), churn prediction, and next-best-action optimization, brands can understand likely customer behavior and tailor marketing strategies accordingly.
Next Best Action (NBA) models go beyond traditional rule-based decision systems by dynamically adapting to real-time data and customer context. Rather than relying on static flows or pre-defined triggers, AI-driven NBA strategies evaluate a wide range of inputs—behavioral signals, preferences, environmental context—to surface the most relevant message, offer, or action at any given moment.
These models continuously learn from customer interactions across digital and physical touchpoints, enabling real-time personalization at scale. Whether it’s identifying the best time to send a message, recommending the right offer, or selecting the most effective channel, AI helps ensure each interaction is relevant, timely, and impactful.
Real-World Example
A leading casino implemented a real-time marketing engine, built on Next Best Action modeling, to personalize offers based on both in-casino activity and online behavior. The result was increased engagement, a 10% increase in player visits, and a 6% boost in player profitability. Explore the full case study →
The Future of Marketing Is Personalized
AI is no longer a nice-to-have—it’s a competitive necessity. In a marketplace where timing, relevance, and experience are everything, AI-driven personalization empowers brands to meet customers where they are with messaging that resonates.
From smarter segmentation and predictive targeting to real-time personalization and next-best-action optimization, AI enables marketing strategies that are more adaptive, impactful, and customer-centric.
Get Started
Ready to move beyond generic campaigns? OneSix helps companies turn data into meaningful customer experiences that drive loyalty and long-term value. Get in touch with us for a consultation.
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