How to Improve Meta Event Match Quality (EMQ) Score

Every conversion event your Shopify store sends to Meta carries a hidden quality score that most advertisers never think about. Meta's Event Match Quality (EMQ) rating measures how well the data attached to your events — purchases, add-to-carts, page views — can be matched to real user profiles on Facebook and Instagram. A high EMQ means Meta knows exactly who took action on your store. A low EMQ means many of your conversion signals disappear into a void, unmatched and unused.

The impact is tangible. Brands with higher EMQ scores consistently see better ad optimization, more accurate attribution, and lower customer acquisition costs. Yet most Shopify merchants have never checked their EMQ score, let alone taken steps to improve it. This guide will change that — covering what EMQ is, how it's scored, what a good score looks like, and the specific, practical steps you can take to raise it.

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1. What Is Meta Event Match Quality?

Event Match Quality is Meta's scoring system for evaluating the data you send alongside your conversion events. When a customer makes a purchase on your Shopify store and that event is sent to Meta (via the Pixel, the Conversions API, or both), Meta tries to match that event to a specific user profile in its system.

To make that match, Meta looks for identifying parameters attached to the event:

• Email address (hashed)
• Phone number (hashed)
• First name and last name (hashed)
• City, state, zip code (hashed)
• Country
• Date of birth (hashed)
• Gender
• External ID (a unique customer identifier from your system)
• Client IP address
• User agent (browser information)
• Click ID (fbclid — the Facebook click identifier)
• Browser ID (fbp — the Facebook browser cookie)

The more of these parameters you send — and the more accurately they're formatted and hashed — the better Meta can match the event to a user. EMQ is the score that reflects how well you're doing this.

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2. How EMQ Scoring Works

Meta assigns an EMQ score on a scale of 1 to 10 for each event type you're sending. You can find your scores in Meta Events Manager by selecting your pixel and clicking on an individual event (like "Purchase" or "AddToCart").

What the Scores Mean

Score Range	Quality Level	What It Means
1–3	Poor	Most events can't be matched to user profiles. Significant data is missing.
4–5	Fair	Some matching is happening, but there are clear gaps in the data being sent.
6–7	Good	The majority of events are being matched. You're sending several customer parameters.
8–9	Great	Nearly all events are matched. Rich customer data is being sent with proper formatting.
10	Excellent	Maximum match rate. All available parameters are being sent accurately.

Score Varies by Event Type

Your EMQ score isn't a single number for your entire pixel — it's calculated per event type. It's common to see different scores for different events:

• Purchase events often have the highest EMQ because customers provide their email, name, and address during checkout.
• AddToCart events typically score lower because the customer may not be logged in yet.
• PageView events tend to have the lowest EMQ because there's minimal identifying data available for anonymous browsers.

This variance is normal. Focus your improvement efforts on the events that matter most for your ad optimization — typically Purchase, AddToCart, and InitiateCheckout.

How Meta Calculates the Score

Meta's exact algorithm isn't publicly disclosed, but the score is based on:

1. Number of customer parameters sent — more parameters mean a higher potential match rate
2. Quality of those parameters — properly formatted and hashed data matches better than malformed data
3. Actual match rate — the percentage of events that Meta successfully matched to user profiles
4. Consistency — sending parameters reliably across all events (not just some) improves the score

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3. Why EMQ Directly Impacts Your Ad Performance

EMQ isn't just a vanity metric in your Events Manager dashboard. It has a direct, measurable impact on how your ads perform.

More Matched Events = Better Optimization

Meta's advertising algorithm learns from conversion events. When you run a campaign optimized for purchases, Meta's system looks at the people who bought from you and finds patterns — what they have in common, what content they engage with, what time of day they shop. The algorithm then uses those patterns to find more people like them.

But this only works if Meta can identify who actually purchased. If your EMQ is low and only 40% of your purchase events can be matched to user profiles, the algorithm is learning from less than half of your real customers. It's making optimization decisions based on incomplete data.

Higher EMQ = Lower CPA

The relationship between EMQ and CPA (Cost Per Acquisition) is well-documented across the e-commerce advertising community. Here's why:

• Better signal quality means Meta's algorithm can more accurately target high-intent users
• More attributed conversions give the algorithm a larger learning set, reducing the "noise" in optimization
• Improved audience matching means your retargeting and lookalike audiences are built from more complete data
• Reduced waste because the algorithm isn't spending budget on users it can't learn from

Many Shopify brands report a 15–30% reduction in CPA after improving their EMQ score from the 4–5 range to 7+. The improvement isn't always immediate — it typically takes 1–2 weeks for the algorithm to recalibrate — but it's consistent.

Better Attribution Accuracy

A higher EMQ also means your Ads Manager reporting becomes more accurate. When Meta can match more conversions to specific users, it can more reliably attribute those conversions to the campaigns, ad sets, and ads that drove them. This gives you better data for making budget allocation decisions.

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4. How to Check Your EMQ Score

Before you can improve your EMQ, you need to know where you stand.

Step-by-Step in Events Manager

1. Go to Meta Events Manager (business.facebook.com/events_manager)
2. Select your pixel from the data sources list
3. Click on the specific event you want to check (e.g., Purchase)
4. Look for the Event Match Quality section — it displays your score on a 1–10 scale
5. Click into the details to see which customer parameters are being sent and at what rate

What to Look For

Pay attention to:

• Which parameters are being sent — you'll see a list with checkmarks indicating which identifiers Meta is receiving
• Parameter coverage — the percentage of events that include each parameter. 100% coverage for email is much better than 30%
• Parameter quality — Meta will flag if parameters appear to be improperly hashed or formatted

Check All Your Key Events

Don't just check Purchase. Review EMQ for:

• Purchase — your most important conversion event
• AddToCart — critical for retargeting and mid-funnel optimization
• InitiateCheckout — often undercounted but valuable for optimization
• ViewContent — the hardest to score well on, but improvements here help top-of-funnel campaigns

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5. Practical Steps to Improve Your EMQ Score

Improving your EMQ is a combination of sending more customer data, formatting it correctly, and using the right tracking infrastructure. Here are the specific steps, ordered by impact.

Step 1: Implement the Meta Conversions API (CAPI)

If you're relying solely on the Meta Pixel for tracking, this is the single highest-impact change you can make. The Pixel is limited in what customer data it can capture — especially for anonymous visitors or users with ad blockers and iOS privacy restrictions.

CAPI sends events from your server, where you have access to the full customer record at the time of purchase: email, phone number, name, billing address, and more. This data can be hashed and sent alongside the event, dramatically increasing your match rate.

Impact on EMQ: Moving from Pixel-only to Pixel + CAPI typically improves EMQ by 2–4 points.

Step 2: Send All Available Customer Parameters

Many Shopify stores send only an email address with their purchase events. While email is the single most impactful parameter, sending additional identifiers significantly improves match rates.

For every purchase event, aim to include:

• Email address (the single most important parameter)
• Phone number (often available from checkout)
• First name and last name (from checkout or account data)
• City, state, zip code (from shipping or billing address)
• Country
• External ID (your internal customer ID from Shopify)

Each additional parameter gives Meta another way to match the event if one identifier fails. A user might have a different email on Facebook than the one they used at checkout, but their phone number might match — if you're sending it.

Step 3: Hash Parameters Correctly

Meta requires that all personally identifiable information (PII) be hashed using SHA-256 before transmission. But proper hashing requires proper formatting first:

• Lowercase all text before hashing (email, name, city, state)
• Remove leading/trailing whitespace
• Standardize phone numbers to E.164 format (e.g., +15551234567)
• Use ISO 3166-1 alpha-2 for country codes (e.g., "us" not "United States")
• Remove non-numeric characters from zip codes where appropriate

A common mistake is hashing data that hasn't been normalized. If you hash "John@Gmail.com" and Meta has "john@gmail.com" for the same user, the hashes won't match — and the event goes unmatched.

Step 4: Pass the Facebook Click ID (fbclid) and Browser ID (fbp)

These two parameters are among the easiest to improve and have an outsized impact on EMQ:

• fbclid: When a user clicks on a Facebook ad, a click identifier is appended to the URL. Capturing this and passing it back with conversion events creates a direct link between the ad click and the purchase.
• fbp (Facebook Browser ID): The Meta Pixel sets a first-party cookie (_fbp) that identifies the browser. Sending this value with your CAPI events helps Meta match server-side events to the same user the Pixel saw.

If your Conversions API implementation doesn't include these parameters, you're leaving easy EMQ points on the table.

Step 5: Use Identity Resolution

This is where EMQ improvement gets strategic. Identity resolution is the process of connecting multiple sessions and touchpoints from the same customer into a unified profile — even across different devices and browsers.

Here's why this matters for EMQ:

Without identity resolution, a customer who visits your store three times — once on mobile Chrome, once on desktop Safari, once from an email link — appears as three separate anonymous visitors. When they finally purchase, you can only match that single purchase event with whatever data is available in that session.

With identity resolution, all three visits are stitched together into one profile. When the purchase happens, you can send Meta a richer set of identifiers — even data captured in earlier sessions — dramatically improving the match rate. This is exactly what Upstack ID does — it connects anonymous browsing sessions to known customer profiles across devices and browsers with 1-year identity persistence, so every event sent to Meta carries the richest possible set of customer parameters, not just the data from the session where the conversion happened.

Common scenarios identity resolution solves:

• Customer browses anonymously, then logs in later and purchases — earlier sessions are retroactively enriched
• Customer clicks a Facebook ad on mobile but purchases on desktop — the click ID from mobile is connected to the purchase event
• Customer enters their email in a popup or Klaviyo form early in the journey — that email is available for all subsequent events, not just the purchase

Step 6: Deduplicate Your Events

Sending duplicate events doesn't improve your EMQ — and it can actually create problems. Make sure your Pixel and CAPI implementations use the same event_id for the same action so Meta can properly deduplicate.

If Meta receives a Pixel "Purchase" event and a CAPI "Purchase" event for the same transaction but can't deduplicate them, it may count the purchase twice. This doesn't inflate your EMQ, but it distorts your reporting and optimization.

6. EMQ Benchmarks for Shopify Brands

To give you a realistic sense of where you should aim, here are typical EMQ ranges we see across Shopify stores at various levels of tracking maturity:

Tracking Setup	Typical Purchase EMQ	Notes
Meta Pixel only (default Shopify integration)	3–5	Limited to browser-side data; many events unmatched
Pixel + basic CAPI (Shopify native integration)	5–6	Server-side events help, but often missing key parameters
Pixel + CAPI with full customer parameters	6–8	Sending email, phone, name, address with proper hashing
Pixel + CAPI + identity resolution	8–10	Enriched events with cross-session data; highest match rates

Where to Focus Based on Your Current Score

• Score 1–4: Implement CAPI immediately. This is your biggest lever. You're likely missing the majority of matchable events.
• Score 5–6: You have CAPI but aren't sending enough customer parameters. Audit what data is included with each event and add missing fields.
• Score 7–8: You're in good shape. Focus on edge cases: are you passing fbclid and fbp? Is your hashing consistent? Consider identity resolution to close the gap.
• Score 9–10: You're at the top. Maintain your setup, monitor for regressions, and ensure any new events or tracking changes don't degrade quality.

For context, Shopify brands using Upstack Signal — which combines server-side event capture with identity-enriched CAPI delivery — consistently reach EMQ scores of 7.5+ within 30 days of implementation. Champo, a haircare brand, saw 128% more customers identified after switching to an identity-first tracking approach, which directly translated to higher EMQ and richer conversion signals for Meta's algorithm.

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7. Common Mistakes That Hurt EMQ

Even brands that invest in tracking infrastructure can make mistakes that drag down their EMQ. Here are the most common ones:

Sending Unhashed PII

If you send raw email addresses or phone numbers instead of SHA-256 hashed values, Meta will reject or ignore the data. Always hash before sending.

Inconsistent Data Formatting

Hashing "john@gmail.com" and "John@Gmail.com" produces different hashes. Normalize all data to lowercase, trim whitespace, and standardize formats before hashing.

Missing Parameters on Non-Purchase Events

Many Shopify stores send rich data with Purchase events (because checkout provides name, email, and address) but send almost nothing with AddToCart or ViewContent events. This creates a lopsided tracking setup where upper-funnel events — which Meta uses for mid-funnel optimization — have very low EMQ.

Solution: Use identity resolution to enrich non-purchase events with customer data captured elsewhere in the journey.

Not Passing fbclid Through the Funnel

The Facebook click ID is appended to your landing page URL when a user clicks an ad. If your site doesn't persist this value through the checkout flow, you lose one of the most reliable matching parameters by the time the purchase event fires.

Ensure your tracking implementation captures fbclid on the landing page and includes it in all subsequent events for that session.

Outdated or Broken CAPI Configuration

Tracking setups aren't "set it and forget it." Shopify theme updates, app changes, or checkout customizations can break your CAPI integration without warning. Review your Events Manager diagnostics monthly to catch issues early.

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8. The EMQ and CPA Connection: Real-World Impact

The relationship between EMQ and CPA isn't theoretical — it's observable in campaign data. Here's how the improvement typically plays out:

Short-Term (Week 1–2)

After improving your EMQ, you'll notice more events appearing as "matched" in Events Manager. Your reported conversion volume may increase (because Meta is now attributing events it previously couldn't). During this period, Meta's algorithm is recalibrating.

Medium-Term (Week 2–4)

As the algorithm absorbs the higher-quality data, you'll often see CPA begin to decrease. The algorithm is finding better audiences because it has a clearer picture of who your actual customers are. ROAS typically improves in parallel.

Long-Term (Month 2+)

The compounding effect kicks in. Better data leads to better optimization, which drives more conversions, which provides more data for the algorithm. Brands that maintain high EMQ scores over time see sustained improvements in campaign efficiency.

What to Expect

A realistic expectation for improving EMQ from the 4–5 range to 8+ is:

• 15–30% reduction in CPA over 4–6 weeks
• 10–20% increase in attributed conversions (conversions that were previously unmatched now appear in reporting)
• More stable campaign performance because the algorithm has more data to work with and is less prone to erratic optimization

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9. Conclusion

Meta Event Match Quality is one of the most impactful yet underappreciated metrics in e-commerce advertising. It sits at the intersection of your tracking infrastructure and Meta's ad optimization — and getting it right has a direct, measurable impact on your CPA, ROAS, and campaign stability.

Key takeaways:

• EMQ measures how well Meta can match your conversion events to real user profiles. It's scored per event type on a 1–10 scale, with higher scores meaning better match rates.
• Low EMQ directly hurts ad performance. If Meta can't identify who's converting, its algorithm can't optimize effectively — leading to higher CPA and less accurate reporting.
• Implement the Conversions API (CAPI) as your first and highest-impact step. Pixel-only tracking is no longer sufficient for competitive ad performance.
• Send all available customer parameters with every event — email, phone, name, address, external ID — and ensure they're properly formatted and hashed with SHA-256.
• Don't forget fbclid and fbp. These parameters are easy to pass and significantly improve match rates by linking ad clicks to conversion events.
• Identity resolution is the multiplier. Low EMQ isn't a tracking problem — it's an identity problem. Upstack Data gives Shopify brands the identity resolution (Upstack ID) and identity-enriched CAPI delivery (Upstack Signal) to close the gap between where your EMQ is and where it needs to be. Upstack ID resolves anonymous visitors into known customer profiles across devices and sessions, and Upstack Signal delivers those enriched events to Meta — driving EMQ scores to 7.5+ within 30 days. Champo saw 128% more customers identified and +54% flow revenue after implementing this identity-first approach. See how it works for your brand.
• Monitor your scores monthly. EMQ can regress if tracking configurations change, so treat it as an ongoing metric, not a one-time project.

Improving your EMQ isn't glamorous work. It's infrastructure, data hygiene, and plumbing. But for Shopify brands spending on Meta ads, it's some of the highest-ROI work you can do — because every improvement in match quality translates directly into better-performing campaigns.