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You Think You’re Doing AI-Driven Personalization. Your Customers Disagree.
Most marketers are using AI to amp up their personalization efforts. But in reality, what they've done is layered new technology on top of the same old campaign workflows, and the customer experience on the other end hasn't changed all that much.
True AI personalization requires a different approach. Instead of using AI to create segments or design new journeys, it should enable a shift to individual-level decisioning where content, timing, frequency, and messaging are determined for each customer in real-time.
That’s what Da Vinci is built to do: move from static campaigns to adaptive, one-to-one experiences at scale.
To see if your foundation is ready for it, start with these four questions.
#1: Content: Is your strategy optimized for AI decisioning?
A lot of marketing content is still created for a single send: one campaign, one message, one purpose. That approach has a real cost. It takes time, it’s expensive to produce, and too often, content is used once and never seen again.
❓Ask yourself:
- Do you rebuild creative for every campaign, or can assets be reused in different combinations?
- Is your content flexible enough to be assembled dynamically?
🌟 The Da Vinci Difference
Instead of campaign-based creative, content is stored as reusable building blocks.
Marketers define:
- What assets exist
- How they can be combined
- What rules apply
From there, AI models the customer and understands the building blocks of your content, then matches the two to dynamically assemble the right experience.
Ballard Designs figured this out during a living room promotion where every subscriber received the same offer but opened a completely different email.
Da Vinci personalized hero imagery, product grids, and layouts based on predicted preferences, not just recent behaviors. Some customers saw rugs, others saw lighting, and every single one was matched to the products they were most likely to engage with and buy.
One AI-personalized campaign for a featured chair saw an 11x lift in conversions and a 25x increase in revenue per send compared to the control version.
You’re no longer designing a single “perfect email.” You’re creating a system of assets that can generate many relevant ones automatically.
#2: Audiences: Are you personalizing based on segments or at the individual level?
Segments are only a starting point for personalization.
Even within a group like “loyal customers” or “new parents,” needs and preferences vary dramatically.
❓Ask yourself:
- Does everyone in an audience group get the same experience, or does content adapt at the individual level?
- Are audiences the endpoint, or just a starting point?
If segments determine most of your output, personalization is still happening at the group level.
🌟 The Da Vinci Difference
Da Vinci uses audiences as a starting point, then applies AI to evaluate each individual within that group. Instead of relying on static segments to determine what gets sent, it determines what each person should see based on their behavior, preferences, and intent.
Hibbett felt this shift firsthand. Their team was sending two to three emails a day using outdated segmentation based on past purchases, which meant messages were going to best guesses rather than the right people.
After bringing in Da Vinci, the team moved away from marketer-driven assumptions entirely. Now every customer gets a tailored experience, even if they technically belong to the same audience.
As Kayla Brown, Hibbett's Director of Customer Lifecycle, put it: "Gone are the stale segments. Gone are the marketer preferences where we're making assumptions. And we're truly living in a personalized world now where every customer is getting what they want."
