3 Campaigns That Prove the Power of Linking Klaviyo Data With Ads

Your email platform knows your customers better than your ad platform ever will.

Meta and Google see clicks, conversions, and whatever behavioral signals they can gather from their own ecosystems. Klaviyo sees who opens every email, who clicks through, who buys repeatedly, who’s about to churn, and who’s been loyal for years. That’s a fundamentally richer picture.

Most brands keep these systems separate. Email does email things. Ads do ads things. But when you connect them, something interesting happens. Your ads get smarter. Your targeting gets sharper. And your performance improves in ways that neither platform could achieve alone.

Here are three real campaign examples that show what’s possible when you stop treating Klaviyo and paid media as separate worlds.

Campaign One: Turning Email Engagers Into High-Value Prospecting Seeds

The brand: A DTC skincare company doing around $5M annually, spending heavily on Meta for acquisition.

The problem: Their prospecting campaigns had plateaued. Lookalike audiences based on purchasers were getting stale. Cost per acquisition had crept up 40% over six months, and ROAS was declining. They needed fresh signals to feed Meta’s algorithm.

The insight: Their Klaviyo data showed a segment of email subscribers who were highly engaged (opening and clicking consistently) but hadn’t purchased yet. These weren’t customers, but they also weren’t cold. They’d raised their hand, shown interest, and were actively paying attention. That behavior suggested intent, even without a transaction to prove it.

The execution: They exported a list of email subscribers with more than five opens and at least two clicks in the past 60 days, excluding anyone who had already purchased. They uploaded this as a custom audience to Meta and built a lookalike from it.

The hypothesis was that people who behave like engaged-but-not-yet-converted subscribers would be better prospecting seeds than existing customers. Customers might have bought for a gift, during a sale, or for other reasons that don’t indicate ongoing interest. Engaged non-purchasers had demonstrated repeated, active attention .

The results: The lookalike audience from engaged email subscribers outperformed their standard purchaser lookalike by 35% on ROAS. Cost per acquisition dropped 22%. The campaign ran for three months before performance started to normalize, at which point they refreshed the seed audience with updated engagement data.

Why it worked: Meta’s algorithm is only as good as the signals you give it. By using email engagement as a proxy for purchase intent, they gave the algorithm a higher-quality seed. Engaged subscribers share behavioral traits (curiosity, attention, responsiveness) that correlate with eventual conversion.

Campaign Two: Suppression That Saved Spend and Improved Experience

The brand: A subscription snack company with a strong retention rate and a large base of active subscribers.

The problem: They kept showing acquisition ads to their existing subscribers. Customers complained. Internal team members saw the ads constantly. And the spend was wasted: these people were already paying monthly for the product.

Platform-based suppression wasn’t cutting it. Meta’s customer list matching is imperfect, and people use different emails across platforms. The result was that a significant portion of their ad budget was targeting people who couldn’t possibly convert because they were already customers.

The insight: Klaviyo had the cleanest, most accurate view of who was an active subscriber. Every customer with an active subscription was tagged, and Klaviyo knew their email, phone number, and other identifiers. That data could be used to build a suppression list that was more complete than what they’d assembled from Shopify exports alone.

The execution: They set up a recurring export of all active subscribers from Klaviyo (using Klaviyo’s built-in integrations and a simple automation) and uploaded it to Meta as an exclusion audience. The list refreshed weekly to account for new subscribers and cancellations.

They also created a second exclusion list: anyone who had purchased in the past 30 days, regardless of subscription status. The reasoning was that a recent purchaser doesn’t need to see acquisition ads. If they want to buy again, email or organic search will bring them back.

The results: Ad spend efficiency improved by 18% within the first month. They were no longer paying to reach people they already had. Customer complaints about seeing repetitive ads dropped to nearly zero. And ROAS on prospecting campaigns improved because the algorithm wasn’t “learning” from conversions that were actually existing customers.

Why it worked: Suppression is often overlooked because it feels like optimization rather than growth. But wasted spend is wasted spend. Cleaning up your exclusion lists is one of the fastest ways to improve efficiency, and Klaviyo often has better data for this purpose than Shopify or ad platforms alone.

Campaign Three: Re-Engaging Lapsed Buyers With Coordinated Ads and Email

The brand: A DTC coffee company with strong first-purchase volume but a troubling drop-off after 90 days.

The problem: A large segment of one-time buyers was going dark. They’d purchased once, received the product, and then never returned. Standard win-back emails were performing poorly (low open rates, minimal conversions). The segment was disengaging from email entirely, which meant Klaviyo alone couldn’t reach them.

The insight: These lapsed customers were unreachable via email, but they were still online. They still scrolled Instagram. They still searched Google. Just because they’d stopped opening emails didn’t mean they’d forgotten about the brand. They’d just tuned out the channel.

The execution: They built a Klaviyo segment of customers who had purchased once, more than 90 days ago, and had not opened any of the last ten emails sent to them. This was the “email-unreachable lapsed buyer” cohort.

They exported this segment and uploaded it to Meta as a custom audience. Then they ran a dedicated campaign to this audience with creative specifically designed for win-back: messaging that acknowledged the gap (“It’s been a while”), a compelling reason to return (a new product they hadn’t tried), and a modest incentive (free shipping, not a steep discount).

Simultaneously, they triggered a coordinated Klaviyo flow. When someone from this segment clicked on the Meta ad (tracked via UTM parameters), they entered a reactivation flow with personalized follow-up. The ad did the work of grabbing attention. Email did the work of closing the sale.

The results: The win-back campaign achieved a 4.2x ROAS on the Meta spend, significantly above their prospecting benchmarks. More importantly, 23% of the lapsed customers who converted went on to make another purchase within 60 days, suggesting the campaign re-engaged them genuinely rather than just capturing a one-time discount purchase.

Why it worked: Email and ads are often treated as either/or. This campaign treated them as partners. The ad reached people who had stopped listening to email. The email flow nurtured people whose interest was reignited by the ad. Coordination made both channels more effective than they’d have been alone.

The Common Thread

All three campaigns share a core principle: Klaviyo data made the ads smarter.

In the first example, email engagement became a signal for prospecting. In the second, customer status became a filter for exclusion. In the third, lapsed behavior became a trigger for re-engagement. None of this is possible if you treat your email platform and ad platform as separate systems with separate goals.

The tactical execution varies. Sometimes you’re exporting lists. Sometimes you’re using integrations. Sometimes you’re coordinating timing across channels. But the underlying idea stays the same: the richest data about your customers lives in your email platform, and that data can inform how you spend your ad dollars.

Making It Work

If you want to run campaigns like these, a few things need to be in place.

Clean, well-maintained segments in Klaviyo. The quality of your ad targeting depends on the quality of your segments. If your lists are messy (outdated tags, poor hygiene, inconsistent definitions), your exports will be messy too.

Regular syncing between platforms. Customer behavior changes constantly. A weekly refresh of your key audiences (subscribers, recent purchasers, engaged non-buyers, lapsed customers) keeps your targeting current. Manual one-time exports get stale quickly.

Coordinated creative and messaging. If someone sees an ad and then gets an email, the experience should feel intentional, not disjointed. Align the offers, the tone, and the timing.

Measurement that connects the dots. Track how email-sourced audiences perform relative to other targeting. Use UTM parameters to see when ad clicks lead to email-driven conversions. Build a picture of how the channels work together, not just how each performs in isolation.

Tools That Help

Klaviyo’s native Meta integration allows some level of audience syncing directly, though the functionality has limits. For more control, you may need to export and upload manually or use a connector tool.

Menza can help you identify which customer segments are most valuable by analyzing your Shopify data alongside Klaviyo engagement. If you’re not sure which cohorts to prioritize for ad targeting, querying your data directly can surface the answer faster than building reports by hand.

Zapier or Make (formerly Integromat) can automate the process of exporting Klaviyo segments and updating Meta custom audiences on a recurring basis. Worth setting up if you’re running these plays at any scale.

Triple Whale or Northbeam can help you attribute conversions across channels and understand how email-sourced ad audiences perform over time. Useful for validating whether these strategies are actually working.

Your ad platforms will never know your customers the way your email platform does. The opportunity is in bridging that gap: using what you already know to make your paid media work harder. These three campaigns are examples, not templates. The specific tactics will depend on your brand, your customers, and your data. But the principle holds: connect the systems, and both get better.