The internet is flooded with so many ads, many of them blur together.

When every brand is competing for attention, relevance becomes the strategic advantage. Personalization is how teams earn it—matching messages, creative, and offers to what prospects actually care about in the moment.

But not all marketers are at the same personalization level. Some use it as a cross-channel growth lever, fueled by connected data, dynamic creative, and smarter automation. Meanwhile, others are still relying on a handful of familiar tactics with limited clarity on what's driving results.

StackAdapt's latest personalization research points to a widening maturity gap between marketers who report using advanced personalization techniques and those who dabble with the basics.

So what are marketers more advanced at personalization doing differently?

Many programs stall due to friction where channel silos, fragmented data, disconnected tools, measurement gaps, and privacy constraints shape how (and where) data can be used. The marketers pulling ahead are building personalization as a system.

Following are five practices that consistently separate personalization leaders from laggards.

1. Go Beyond Email and Scale Personalization in Paid Media

Email is still the workhorse of personalization. In fact, 47% of brand marketers say personalized email is their main driver of engagement and conversions.

But more advanced marketers don't stop there. They use the same "right message, right person" mindset in paid media, where relevance is often the difference between being ignored and being remembered.

That's why 32% of brands plan to use display, native, and video advertising to deliver more relevant experiences in the year ahead—and why 42% are already using dynamic creative optimization (DCO) to personalize ads based on the viewer.

What you should do:

• Start with two to three audience signals you can reliably act on (e.g., intent, geography, context, lifecycle stage).
• Use an advertising platform with DCO capabilities to build modular creative (e.g., headline, image, value proposition, call to action) that can swap based on those signals.
• Test a tight set of messages or offers to learn what truly moves performance, instead of creating endless permutations that are impossible to measure.

2. Invest in Connected Tools

Personalization tools only deliver real value when they're connected. That's one reason 73% of brands in mature stages of personalization are more likely to use customer data platforms (CDPs) to unify customer data and inform campaigns.

What you should do:

• Choose a system of record, such as a customer relationship management (CRM) tool, CDP, or data warehouse, and treat it as the source of truth for audiences.
• Standardize five to 10 audience definitions your team agrees on (e.g., high-intent prospects, lapsed customers, repeat buyers).
• Build a clean handoff from analytics to activation to reporting so performance can be tied back to the same audience logic.
• Set governance early. Define who can create segments, what data is approved for use, and how changes are documented.

3. Build a Privacy-First Data Mix

Relying on a single data source—whether it's first-party or third-party data—puts a ceiling on personalization.

The strongest programs blend signals to stay relevant without overstepping privacy boundaries. Marketers advanced in their personalization efforts are two times more likely to use both first- and third-party data for targeting.

Having "better data" means having the following.

• Clear consent and retention rules
• An audience taxonomy your team can actually operate (e.g., prospecting, mid-funnel, retention)
• Regular audits to remove what's outdated, duplicative, or no longer useful

In practice, a privacy-first mix can look like:

• First-party data: Recent site or product interest paired with CRM status (e.g., new lead vs. customer vs. churn risk)
• Third-party data: Consented intent or context segments to expand reach beyond your known audience
• Contextual signals: Page category and content signals to tailor messaging without relying on identity

4. Test Emerging Channels

Personalization maturity shows up where teams are willing to apply it. Leaders don't treat personalization as something to perfect in a single channel; they expand the number of places they can deliver relevance, then learn quickly what scales.

The data backs that up: 33% of brand marketers advanced in personalization use connected TV (CTV) to personalize campaigns, compared with 14% of less-advanced marketers.

A simple way to start is to run one focused pilot.

• Pick one emerging channel (CTV or digital audio).
• Choose one personalization dimension you can execute cleanly, such as geography, placement alongside relevant content, or a broad audience tier (e.g., new vs. returning).
• Define what success means up front, whether that's incremental reach, brand or site lift, or cost per qualified visit.
• Run a test for four to six weeks with a learning agenda (i.e., what you're trying to prove, what you'll change next, and what would justify scaling).

5. Operationalize AI and Tie It to Measurement

Many teams experiment with AI in pockets—a few audience insights here, some copy help there—while far fewer integrate it end to end.

In StackAdapt's research, only about one in five brands and agencies say they've fully integrated AI across channels (21% and 22%, respectively).

That deeper integration matters because it changes what teams can prove. Some 79% of brands that fully integrate AI across channels say they can accurately measure personalization's impact on revenue, compared with just 14% of those not using AI.

What you should do:

• Use AI to identify patterns and high-performing segments humans might miss.
• Generate and prioritize modular variations that feed DCO inputs.
• Shift spend across audience tiers based on performance signals.
• Flag changes early and automate routine analysis so teams act faster.

Start Simple

Personalization at scale is getting more achievable as AI and automation reduce the manual lift. But the teams pulling ahead still win the same way—by connecting the fundamentals.

When data flows cleanly into the right tools, creative is built to adapt, and measurement ties outcomes back to audiences and messages, personalization becomes a repeatable system instead of a one-off tactic.

You don't need to overhaul everything at once. Pick one tactic from this article to implement this quarter—expand beyond email, tighten your data mix, run a CTV/audio pilot, or operationalize AI for measurement—and use the results to earn your way into trying the next tactic.