How Shopify Stores Can Use Klaviyo and First-Party Data for Better Ad Performance

Most Shopify merchants think of Klaviyo as an email and SMS platform. They set up their abandonment flows, build a few campaigns, and move on. What many don't realize is that Klaviyo is also one of the richest sources of first-party customer data in their entire marketing stack — and that data can dramatically improve the performance of their paid advertising.

In a world where third-party cookies are disappearing, ad blockers are ubiquitous, and privacy regulations restrict how platforms can track users, first-party data has become the most valuable currency in digital advertising. Klaviyo sits at the intersection of behavioral data, purchase history, and customer identity — all collected with consent, all tied to real people.

This guide shows Shopify merchants how to use Klaviyo's first-party data to build better ad audiences, improve match rates, lower customer acquisition costs, and create a flywheel where email marketing and paid advertising reinforce each other.

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What First-Party Data Does Klaviyo Actually Collect?

Before we talk about using Klaviyo data for ads, it's important to understand the depth of what Klaviyo captures. It's more than most merchants realize.

Behavioral Data

Klaviyo's on-site tracking snippet captures detailed behavioral signals:

• Active on Site — Tracks when identified users are browsing your store
• Viewed Product — Logs every product page visit, including product name, price, and URL
• Added to Cart — Records cart additions with product details
• Started Checkout — Captures checkout initiation events
• Placed Order — Full purchase data including items, quantities, total value, discount codes, and shipping details

Engagement Data

Beyond on-site behavior, Klaviyo tracks how customers engage with your marketing:

• Email opens and clicks — Which campaigns and flows drive engagement
• SMS interactions — Replies, opt-ins, and click-throughs
• Form submissions — Pop-up signups, quiz completions, lead magnet downloads
• Consent status — Opt-in dates, subscription preferences, and consent history

Customer Profile Data

Klaviyo builds rich customer profiles that combine:

• Contact information — Email, phone number, name, address
• Purchase history — Total orders, total revenue, average order value, product preferences
• Predictive analytics — Expected date of next order, predicted customer lifetime value, churn risk score
• Custom properties — Any custom data you pass through integrations or forms (quiz answers, preferences, loyalty tier)

Why This Data Is Valuable for Advertising

Each of these data points represents a signal that ad platforms can use to find and target the right people. The challenge is getting this data from Klaviyo into your ad platforms in a way that's actionable.

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Syncing Klaviyo Segments to Ad Platforms

The most direct way to leverage Klaviyo's first-party data for advertising is to sync customer segments from Klaviyo to your ad platforms as Custom Audiences.

How Klaviyo-to-Meta Sync Works

Klaviyo offers a native integration with Meta that lets you sync segments directly:

1. Build a segment in Klaviyo based on any combination of behavioral, engagement, or profile data.
2. Connect Klaviyo to your Meta Ad Account through Klaviyo's integrations settings.
3. Sync the segment as a Custom Audience. Klaviyo sends hashed customer identifiers (email, phone) to Meta.
4. Meta matches these identifiers to user profiles on Facebook and Instagram.
5. The audience stays synced. As people enter or exit the Klaviyo segment, the Meta audience updates automatically.

High-Value Segments to Sync

Not all segments are equally useful for advertising. Here are the ones that consistently drive the best results:

For Retargeting:

• Cart abandoners (last 7–14 days) — High intent, haven't purchased yet
• Browse abandoners (viewed 3+ products, no purchase) — Interested but need a nudge
• Checkout abandoners — Highest intent non-buyers
• Lapsed customers (purchased 60–120 days ago, no repeat) — Win-back candidates

For Lookalike Audiences:

• Top 10% customers by LTV — Your best buyers, used as a seed for finding similar people
• Repeat purchasers (3+ orders) — Customers who love your brand
• High-AOV customers — People who buy your premium products
• Recent purchasers (last 30 days) — Fresh signal for Meta's algorithm

For Suppression:

• Recent purchasers (last 7–14 days) — Exclude from prospecting to avoid wasting budget
• Unsubscribed contacts — People who don't want to hear from you
• Existing subscribers — Exclude from lead generation campaigns

Syncing to Google Ads

Klaviyo also integrates with Google Ads Customer Match:

1. Create a segment in Klaviyo with the audience you want to target or suppress.
2. Sync via Klaviyo's Google Ads integration.
3. Google matches the hashed data to user profiles across Search, YouTube, Gmail, and Display.
4. Use the audience for remarketing, similar audiences, or bid adjustments.

Syncing to TikTok and Other Platforms

For platforms without native Klaviyo integrations, you can:

• Export segments manually from Klaviyo as CSV files and upload them to the ad platform
• Use middleware tools (like Zapier or a server-side tracking platform) to automate the sync
• Build custom integrations using Klaviyo's API and the ad platform's audience API

Regardless of which sync method you use, the quality of your Klaviyo segments depends on the completeness of the underlying customer profiles. Upstack Enrichment unifies fragmented customer data across sources — connecting browsing behavior, purchase history, and identity signals into a single profile — so the segments you sync to ad platforms are built on the most complete data available.

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Using Email Engagement Data for Audience Building

Here's where it gets interesting. Most merchants sync basic customer lists to ad platforms. But Klaviyo's email engagement data adds a layer of intent signal that pure purchase data misses.

Why Email Engagement Signals Matter

Consider two customers who both purchased once, three months ago:

• Customer A opens every email, clicks through to products weekly, and has browsed your site recently.
• Customer B hasn't opened an email in two months and hasn't visited your site.

Both are "past purchasers" in a basic segment. But Customer A is clearly more engaged and more likely to convert on an ad. Email engagement data lets you distinguish between them.

Engagement-Based Audience Strategies

High-Engagement Lookalikes: Build a Klaviyo segment of contacts who have opened or clicked an email in the last 30 days AND have purchased at least once. Sync this to Meta as a lookalike seed. These are your most engaged, proven buyers — Meta's algorithm will find people who match their profile.

Engaged Non-Buyers: Create a segment of contacts who engage with emails (open rate > 50% over last 90 days) but haven't purchased. Sync this as a retargeting audience with conversion-focused ad creative. These people are interested — they just need the right offer or moment.

Win-Back Through Ads: Identify customers who used to engage with emails but have gone quiet (no opens in 60+ days). Some of these people aren't seeing your emails (spam folder, inbox overload). A targeted ad campaign can re-engage them through a different channel.

Disengaged Suppression: Suppress contacts who haven't engaged with any email in 90+ days from your paid campaigns. They're unlikely to convert, and showing them ads wastes budget. This is a simple way to improve ROAS by removing dead weight from your audiences.

Combining Engagement With Predictive Data

Klaviyo's predictive analytics add another dimension:

• High predicted LTV + high email engagement = Your best seed audience for lookalikes
• High churn risk + recent email engagement = Win-back targets for both email and ads
• Low predicted next order date = Customers likely to buy soon, perfect for retargeting

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The Connection Between Identity Resolution and Klaviyo Enrichment

There's a fundamental dependency that limits how well Klaviyo can collect data: it can only track behavior for visitors it can identify. If a visitor is anonymous — and the majority of e-commerce traffic is — Klaviyo doesn't know who they are and can't attribute their behavior to a profile.

The Identification Problem

Here's what typically happens:

1. A visitor clicks a Meta ad and lands on your store.
2. They browse several products, add something to cart, but don't check out.
3. They leave without entering their email.
4. Two days later, they come back directly (typing your URL or via a bookmark).
5. They continue browsing.

Without identity resolution, Klaviyo sees these as two separate anonymous sessions. No cart abandonment email is triggered. No browse data is attributed to a profile. That visitor's behavioral data is effectively lost.

How Identity Resolution Fixes This

Identity resolution connects fragmented visitor sessions to a single, persistent profile using first-party signals — device fingerprinting, IP inference, behavioral patterns, and historical data. When implemented correctly:

• A visitor who entered their email on Monday via a pop-up is recognized when they return on Thursday, even if their cookies have expired.
• Klaviyo receives the identification event and can now attribute Thursday's browse and cart behavior to that person's profile.
• Abandonment flows trigger correctly.
• The customer's profile is enriched with complete behavioral data.

This is exactly what Upstack Flow is built for — re-identifying anonymous visitors so Klaviyo automations fire for people who would otherwise be invisible. Stores using Upstack Flow typically see a 1.8x increase in Klaviyo flow entries because visitors who previously dropped off unrecognized are now matched back to their profiles.

The Downstream Impact on Ad Audiences

Better identification doesn't just help email flows — it directly improves the quality of the audiences you sync to ad platforms:

• Larger retargeting pools. More identified visitors means more people in your retargeting segments.
• Richer behavioral data. Customer profiles with complete browse and cart history produce better lookalike seeds.
• More accurate engagement signals. When Klaviyo can track behavior across sessions, engagement scoring becomes more accurate.
• Higher match rates. More identified profiles means more email addresses and phone numbers to match against ad platform user bases.

This creates a positive feedback loop: better identity resolution → richer Klaviyo profiles → better ad audiences → more traffic → more people to identify.

Practical Workflows for Shopify Merchants

Let's put this all together with concrete workflows you can implement.

Workflow 1: The Lookalike Flywheel

Goal: Continuously improve your prospecting audiences using Klaviyo data.

1. Create a dynamic Klaviyo segment: "Purchased in last 90 days AND email engagement > 30% open rate AND total revenue > $100"
2. Sync to Meta as a Custom Audience.
3. Build a 1% lookalike from this audience.
4. Run prospecting campaigns targeting the lookalike.
5. New customers enter the Klaviyo segment as they purchase and engage.
6. The lookalike seed automatically updates — getting better over time.

This creates a self-improving loop where your best customers continuously refine who Meta targets next.

Workflow 2: Full-Funnel Retargeting With Email Backup

Goal: Ensure no high-intent visitor falls through the cracks.

1. Klaviyo tracks browse and cart behavior for identified visitors.
2. Abandonment flows trigger for visitors Klaviyo can identify (email within 1–4 hours).
3. Simultaneously, sync these segments to Meta:
   • "Added to Cart, No Purchase, Last 7 Days" → Retargeting ads with product-specific creative
   • "Viewed Product 3+ Times, No Add to Cart, Last 14 Days" → Retargeting ads with social proof
4. For visitors Klaviyo can't identify (anonymous), the Meta Pixel and server-side tracking still capture their behavior for pixel-based retargeting.
5. Result: Identified visitors get emails AND ads. Anonymous visitors still get ads. No one is completely lost.

Workflow 3: Seasonal Campaign Audience Prep

Goal: Build high-quality audiences before a big sale or product launch.

1. 60 days before the event, create Klaviyo segments:
   • "Engaged email subscribers who haven't purchased" (warm leads)
   • "Past purchasers of [related product category]" (cross-sell targets)
   • "VIP customers (top 20% by LTV)" (early access candidates)
2. Sync all three segments to Meta and Google as Custom Audiences.
3. Build lookalikes from the VIP and past purchaser segments.
4. Run awareness/teaser campaigns to these audiences in the weeks leading up to the event.
5. On launch day, retarget the engaged audiences with conversion-focused creative.
6. Post-event, sync the new purchaser list back to suppress from prospecting and seed new lookalikes.

Workflow 4: Cross-Channel Attribution Validation

Goal: Validate your ad platform's reported conversions against Klaviyo data.

1. Create a Klaviyo segment of customers who purchased in the last 30 days.
2. Add a condition: "Has property 'utm_source' equals 'facebook'" (or whatever UTM parameter your Meta ads use).
3. Compare the count against what Meta Ads Manager reports as conversions.
4. Significant discrepancy? Your tracking might have gaps. This is a signal to audit your server-side tracking, pixel setup, or identity resolution.

This isn't a replacement for proper attribution tooling, but it's a quick gut-check that any merchant can do.

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How Server-Side Tracking Improves the Data Klaviyo Receives

Everything we've discussed so far depends on one thing: the quality and completeness of data flowing into Klaviyo. If Klaviyo doesn't receive an event, it can't attribute behavior, trigger flows, or enrich profiles.

The Client-Side Data Gap

When Klaviyo relies solely on its client-side JavaScript snippet:

• Ad blockers prevent the snippet from loading. 15–30% of desktop visitors may not be tracked at all.
• Safari ITP restricts cookie lifetime. First-party cookies are capped at 7 days (or 24 hours if set via JavaScript), meaning returning visitors are treated as anonymous.
• iOS restrictions limit cross-app tracking, reducing the ability to connect ad clicks to on-site behavior.
• Page load issues can prevent the snippet from firing — slow connections, quick bounces, or JavaScript errors.

How Server-Side Tracking Closes the Gap

Server-side tracking sends event data from your server directly to Klaviyo's API, bypassing all client-side limitations:

• Every order is tracked. Purchase events sent server-side are guaranteed to reach Klaviyo, regardless of the customer's browser or device settings.
• Behavioral events are backed up. Browse, cart, and checkout events can be sent from the server as a supplement to client-side tracking.
• Customer data is enriched. Server-side events can include data that isn't available in the browser — customer lifetime value, order count, product margins, segment membership.
• Identity is maintained. Server-side tracking can include customer identifiers (email, phone) that help Klaviyo attribute events to the right profile, even when cookies have expired.

The Compound Effect

When you combine server-side tracking with Klaviyo:

1. More events reach Klaviyo → More complete customer profiles
2. More complete profiles → Better segmentation for both email and ads
3. Better segmentation → Higher-quality audiences synced to ad platforms
4. Higher-quality audiences → Better ad performance and lower CAC
5. Lower CAC → More efficient growth

This is why the most effective Shopify merchants don't think of email marketing and paid advertising as separate channels. They treat them as a unified system where the data layer — first-party data collection, identity resolution, and server-side tracking — is the foundation that makes both channels perform better.

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Measuring the Impact

How do you know if your Klaviyo-powered ad strategy is working? Track these metrics:

Audience Quality Metrics

• Custom Audience match rate. What percentage of Klaviyo contacts match to profiles on Meta or Google? Higher match rates mean more of your first-party data is usable. Target 60%+ for email-based audiences.
• Lookalike performance vs. interest-based targeting. Compare CAC and ROAS for campaigns using Klaviyo-seeded lookalikes vs. standard interest targeting. Lookalikes should outperform.
• Retargeting ROAS. Campaigns targeting Klaviyo-synced segments (cart abandoners, browse abandoners) should show significantly higher ROAS than prospecting.

Data Quality Metrics

• Klaviyo identification rate. What percentage of your site visitors does Klaviyo identify? Below 20% suggests an identity resolution problem.
• Profile completeness. What percentage of Klaviyo profiles have an email, phone number, and at least one purchase? More complete profiles produce better ad audiences.
• Event coverage. Are all standard events (browse, cart, checkout, purchase) flowing into Klaviyo consistently? Gaps in event data reduce audience accuracy.

Revenue Attribution

• Klaviyo-attributed revenue vs. ad platform revenue. These numbers won't match exactly, but they should tell a consistent story. Large discrepancies indicate data quality issues.
• Email + SMS revenue as a percentage of total. Healthy Shopify stores see 25–40% of revenue from owned channels. If it's lower, your Klaviyo data and flows may need optimization.

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Conclusion

Klaviyo isn't just an email platform — it's a first-party data engine that, when used strategically, can transform your paid advertising performance. The brands that win in today's privacy-first landscape are the ones that connect their email marketing and paid advertising through a shared data layer.

Key takeaways:

• Klaviyo collects deep behavioral, engagement, and profile data that most merchants underutilize for advertising.
• Syncing Klaviyo segments to ad platforms gives you Custom Audiences and lookalike seeds that outperform generic interest-based targeting.
• Email engagement data is a powerful intent signal that helps you distinguish between active prospects and dormant contacts — improving audience quality and reducing wasted ad spend.
• Identity resolution is the force multiplier. The more visitors you can identify, the more complete your Klaviyo profiles become, and the better your ad audiences perform. Upstack Data specializes in exactly this — Upstack Flow re-identifies lost visitors for Klaviyo automations while Upstack ID provides cross-device identity resolution with 1-year persistence. The results speak for themselves: Perfect White Tee saw +$92K/month in flow revenue and an 85% increase in email-driven revenue, while Champo recovered an additional $24K/month in abandonment revenue with a 54% lift in flow revenue.
• Server-side tracking ensures data completeness by bypassing ad blockers and browser restrictions that degrade client-side tracking.
• Practical workflows — from lookalike flywheels to full-funnel retargeting with email backup — turn these concepts into repeatable processes.

The merchants who treat Klaviyo data as a strategic asset for advertising, not just a tool for sending emails, are the ones building a sustainable competitive advantage in customer acquisition.