Introduction

It’s both an exciting and an intimidating time to be a marketer. On one hand, AI is top of mind for organizations, offering the potential to deliver enormous gains in terms productivity, business impact, and customer experiences. On the other hand, with nearly every martech vendor now claiming to offer “AI-powered personalization,” it’s difficult to separate meaningful innovations from all of the noise.

As we experience everyday at Movable Ink, even marketers who have already invested in AI technologies struggle to understand the differences between solutions, their strengths and shortcomings. The truth is, not all AI tools, even those that look similar, are designed to solve the same problems. That’s where much of the confusion lies.

Fortunately, with a bit of clarity and context, those differences become much easier to identify. This guide is designed to break down some of those distinctions and ultimately help marketers navigate the AI martech landscape with a bit more confidence.

Why Is Personalization So Important?

In marketing, personalization is the practice of creating tailored experiences, messages, and recommendations for customers based on their behaviors, preferences, and past interactions. In leveraging data and insights, brands aim to ensure that each person receives content and offers specifically relevant to them–thereby transforming otherwise generic experiences into more meaningful, impactful engagement.

It makes sense, too. In competitive marketplaces, personalization allows brands to move beyond one-size-fits-all marketing and communicate more effectively and authentically. It helps to deepen customer relationships, increase satisfaction, and build loyalty–with the ultimate goal of improving conversion, retention, and advocacy.‍

‍Personalization has proven to deliver measurable results across the customer journey. Here are some of the most consistent indicators of success:

• Conversion Rates: Personalized messages can lift conversion rates by 20% or more, according to several industry studies. When content reflects a customer’s interests, they’re more likely to take action.

• Customer Engagement: Personalized content often drives higher email open rates, more clicks, and longer visits to digital properties. In fact, more than 50% of consumers are willing to share information on products they like to get personalized discounts. 
• Customer Retention: Personalized communication helps reduce churn. Research shows that customers are more likely to stick with brands that speak to them as individuals, not just segments.
• Customer Lifetime Value (CLV): Personalization drives repeat purchases and lasting loyalty, with 60% of consumers claiming they’re more likely to return to a brand after a personalized shopping experience

Key Assumptions About Personalization

Personalization has become a cornerstone of modern marketing, but its maturity across organizations varies significantly. Success depends on technology solutions, internal strategies and team readiness, customer data, and marketing content. Personalization should adapt based on the channel, engagement level, message relevance, and customer preferences. 

While basic personalization might include a name or birthday, advanced personalization evolves with the customer, consistently delivering deeper, more meaningful, and sometimes surprising connections. Realizing that consumers are not always linear in their purchasing journeys, AI personalization can help guide people down paths of exploration.

Getting Personalization Right is Hard

Personalization at scale is challenging. Brands typically rely on a patchwork of tools that don’t always integrate seamlessly. And though they may have plenty of customer data in their warehouse or CDP, that doesn’t always equate to information that’s relevant or actionable. 

Customer preferences can shift quickly too, making predictive modeling difficult. Beyond recurring purchases like groceries or household items, predicting customer behavior–especially when recent engagement signals have lapsed–is somewhat of a guessing game. And choosing the right time and channel to deliver personalized experiences adds additional layers of complexity.

Requirements for Success

To succeed with personalization, brands must leverage applicable customer data the best they can, invest in the right tools, and align strategies with specific business goals. They should take a focused approach when customer signals are strong, while remaining flexible in situations where interests are uncertain. Striking the right balance between short-term performance and long-term relationship-building is essential to delivering personalization that drives both immediate impact and lasting value for brands.

Marketers would also benefit from understanding that, depending on what they’re trying to achieve, there are actually two distinct approaches to personalization—reactive and proactive. It’s critical for marketers to understand  what those two approaches are, their unique capabilities, and why brands need both to be effective.

Two Approaches to Personalization

Reactive Personalization

Reactive personalization is what marketers are probably most familiar with and have been utilizing in various forms for many years. It involves responding directly to explicit customer-initiated signals or actions. This approach prioritizes real-time or near-real-time responses to customer intent and emphasizes engagement across both inbound and outbound interactions. Typical channels include websites, mobile apps, and triggered communication journeys, ensuring customers receive immediate and contextually relevant experiences aligned with their latest explicit or implicit interests.

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Proactive Personalization

Proactive personalization is marketer-driven and designed for outbound channels. Instead of responding to immediate actions, it attempts to anticipate what a customer may be interested in using historical profile data, broader audience trends, and the content a brand needs or wants to communicate. It’s closely related to the same kind of ad serving technology that powers platforms like Meta Ads, Google Display Network, and programmatic media buying, systems designed to determine which message to show to which person, and when. Similarly, Da Vinci applies this logic to scheduled email campaigns, dynamically deciding which content to serve each individual recipient based on what’s most likely to drive engagement. This approach supports broader marketing goals like brand awareness, product discovery, and long-term retention, turning email into a smarter, more strategic channel.

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Characteristics of Each Approach

Reactive personalization has powered inbound digital experiences for over 15 years. It relies on customer behavior and logic-based decisioning to provide tailored journeys in real time. Its strengths lie in short-term actions—like addressing abandoned carts or browsing behavior.

Proactive personalization, by contrast, excels in outbound communication. It doesn’t rely solely on recent activity. Instead, it also uses signals from aggregated behavior and historical data to rekindle interest and guide messaging across large audiences—especially in email. It’s adaptive and improves over time, helping brands maintain engagement and deliver long-term results.

Brands Need Both Personalization Approaches

To achieve meaningful personalization at scale, brands must embrace both proactive and reactive strategies. Relying solely on customer-initiated engagement isn’t enough, especially when, in our experience, only 15–20% of a typical customer base interacts with the brand in a given year. And often, those interactions are sparked by large-scale email campaigns designed to drive traffic back to owned digital properties like websites or mobile apps.

That’s where proactive personalization plays a critical role. It helps marketers reach broader audiences, re-engage inactive customers, and guide them toward digital experiences. Once there, reactive personalization can take over—leveraging real-time behavioral data to deliver contextually relevant experiences through triggered journeys and content updates.

In essence, proactive personalization is a key driver of reactive personalization that responds to customers in real time. Together, both approaches create a balanced strategy that serves both short-term performance goals and long-term objectives like customer discovery and message frequency optimization.

Brands that successfully utilize both approaches are best positioned to boost engagement, identify customer interests, respond to intent signals, and ultimately drive stronger business outcomes in today’s dynamic marketing environment.