Meta Ads Audit Checklist for E-Commerce Brands (2026)

Verify that the Meta Pixel fires correctly on every page of your site, including product pages, cart, and checkout.

A Pixel that silently fails on key pages means Meta cannot optimize toward your actual conversions, and your reported ROAS will be inaccurate.

Confirm that Conversions API (CAPI) is active and sending server-side events for all priority actions.

Browser-only tracking misses 20-40% of conversions post-iOS 14.5 due to cookie blocking and ad blockers, making CAPI essential for data completeness.

Check your Event Match Quality (EMQ) score in Events Manager and ensure it is above 6.0 for all key events.

A low EMQ means Meta cannot match events back to users, which directly reduces the effectiveness of your optimization and custom audiences.

Validate that browser Pixel events and CAPI events are properly deduplicated using event_id or a matching key.

Without deduplication, Meta counts the same conversion twice, inflating your reported ROAS and feeding incorrect signals to the algorithm.

Confirm that your Aggregated Event Measurement (AEM) events are prioritized in the correct order for your business.

Post-ATT, Meta only reports on up to 8 prioritized events per domain; misconfigured priorities mean your most valuable events may not be attributed correctly.

Test your domain verification status and ensure all advertising domains are verified in Business Manager.

Unverified domains lose the ability to configure conversion events and are limited in optimization options, a common silent cause of campaign underperformance.

Audit the total number of active campaigns and confirm you are consolidating rather than fragmenting spend.

Meta's algorithm performs best with fewer campaigns receiving higher budgets; spreading spend across too many campaigns starves each one of data.

Verify that each campaign has a clear, distinct objective aligned to a single stage of your funnel.

Mixing objectives within a campaign confuses the algorithm about who to show your ads to and what outcome to optimize for.

Check that no ad set has exited the learning phase with "Learning Limited" status for more than 7 days.

Learning Limited ad sets do not have enough data to optimize efficiently, which means higher CPAs and wasted spend that could be consolidated elsewhere.

Confirm your naming conventions are consistent and include campaign type, objective, audience, and date.

Inconsistent naming makes analysis nearly impossible at scale and slows down every future audit, reporting cycle, and team handoff.

Review whether you have separate campaigns for prospecting and retargeting, or if Advantage+ handles both.

Understanding your funnel split is critical for budget control; without clear separation, you cannot measure true acquisition cost versus remarketing efficiency.

Identify and pause any duplicate audiences across ad sets that are competing against each other in the auction.

Overlapping audiences drive up your CPMs through self-competition and make it impossible to attribute performance to any specific targeting approach.

Confirm whether you have an Advantage+ Shopping Campaign (ASC) running, and if so, evaluate its share of total spend.

ASC is Meta's most automated campaign type; you need to understand how much of your budget it controls and whether that allocation is justified by performance.

Review the existing customer budget cap inside your ASC to ensure you are not overspending on retargeting.

Without a cap, ASC will default to showing ads to people who already bought from you, inflating ROAS on paper while generating minimal incremental revenue.

Verify that your product catalog is connected, up to date, and contains accurate pricing, availability, and images.

ASC relies heavily on your catalog for dynamic product ads; stale or incorrect catalog data leads to disapproved ads and poor user experience.

Analyze the creative mix within ASC and confirm you have at least 10-15 varied creative assets loaded.

Advantage+ Shopping performs best with a high volume of diverse creatives because the algorithm needs options to test across different audience segments.

Compare ASC performance against your manual campaigns using a consistent attribution window.

Many advertisers find ASC looks better on paper due to attribution differences; a fair comparison requires the same attribution settings across both.

Review all active custom audiences and confirm their source data is fresh, ideally refreshed within the last 30-60 days.

Stale custom audiences contain users whose behavior has changed, reducing relevance scores and increasing wasted impressions on disengaged people.

Check for audience overlap between ad sets using Meta's Audience Overlap tool in Ads Manager.

High overlap means your ad sets are bidding against each other for the same users, inflating CPMs and making performance analysis unreliable.

Evaluate whether your Lookalike audiences are still built from high-value seed lists such as purchasers or high-LTV customers.

Lookalikes built from low-quality seeds like page visitors or engagers tend to attract browsers rather than buyers, dragging down conversion rates.

Confirm whether you are testing broad targeting (no interest or Lookalike restrictions) alongside your targeted ad sets.

Post-iOS 14.5, Meta's algorithm often outperforms manual targeting when given enough budget and creative variety; not testing broad leaves potential scale on the table.

Verify that retargeting audiences have appropriate exclusion windows to avoid showing ads to recent purchasers.

Without exclusions, you pay to advertise to people who just bought, which wastes budget and annoys customers during their post-purchase window.

Assess whether your audience sizes are large enough to exit the learning phase within 7 days at your current budget.

Audiences that are too narrow at your spend level will never generate the 50 weekly conversions Meta needs to optimize, keeping you permanently in Learning Limited.

Identify your top 3 performing creatives by cost-per-purchase and confirm they are still receiving meaningful spend.

The algorithm sometimes deprioritizes proven winners in favor of newer, untested creatives; manually monitoring ensures your best assets keep running.

Flag any creative that has shown a 20%+ increase in CPA over the past 14 days as a creative fatigue candidate.

Creative fatigue is the number one silent budget killer in Meta Ads; catching it early prevents weeks of declining performance before you react.

Verify that you have a mix of creative formats: static images, short-form video (under 15 seconds), carousel, and UGC.

Different formats win in different placements and with different audiences; relying on a single format limits your algorithm's ability to find conversions.

Check that all creatives are optimized for mobile-first viewing with legible text, vertical or square aspect ratios, and fast load times.

Over 90% of Meta ad impressions happen on mobile devices; desktop-designed creatives with small text or horizontal layouts underperform dramatically.

Review your creative testing cadence and confirm you are introducing at least 3-5 new creatives per ad set per month.

A consistent pipeline of fresh creative prevents fatigue cycles and gives the algorithm continuous new material to test against your existing winners.

Evaluate whether your Advantage+ Creative enhancements (text variations, brightness adjustments) are improving or hurting results.

Auto-enhancements can boost performance for some brands but distort others; reviewing placement-level data reveals if these optimizations are actually helping.

Confirm that every active ad has a clear, compelling hook in the first 3 seconds of video or the top portion of a static image.

Users scroll past ads in under 2 seconds on average; without an immediate hook, your creative spend is wasted on impressions that never register.

Verify which attribution window is set at the ad set level and ensure it is consistent across all active campaigns.

Comparing campaigns with different attribution windows is like comparing apples to oranges; inconsistency makes it impossible to know what is actually working.

Cross-reference Meta's reported conversions with your Shopify, GA4, or backend data over the past 30 days.

Discrepancies between Meta-reported and backend data reveal tracking gaps, over-attribution, or CAPI issues that silently distort your decision-making.

Check whether you are using 7-day click plus 1-day view as your primary attribution setting for optimization.

This is Meta's recommended default post-iOS 14.5 and gives the algorithm the most conversion data to work with while remaining reasonably accurate.

Review your custom reporting columns to ensure you are tracking cost-per-purchase, ROAS, CPC, CPM, CTR, and frequency at minimum.

Default Ads Manager columns hide critical metrics; a properly configured column set lets you diagnose problems in seconds instead of minutes.

Assess whether you have a secondary attribution source (GA4 UTM tracking, Triple Whale, or post-purchase surveys) to validate Meta data.

No single attribution platform tells the full truth post-iOS 14.5; triangulating data from multiple sources gives you the closest picture of real performance.

Audit the primary text of your top-spend ads and confirm each one leads with a clear benefit or pain point, not a feature list.

Benefit-led copy consistently outperforms feature-led copy in e-commerce; users need to understand why they should care before they will click.

Verify that every ad has a strong, specific call-to-action that matches the landing page destination.

A mismatched CTA-to-landing-page experience increases bounce rates and trains the algorithm to associate your ads with low-quality traffic signals.

Test whether your landing pages load in under 3 seconds on mobile, using Google PageSpeed Insights.

Every additional second of load time reduces mobile conversion rates by approximately 20%; a slow landing page undermines even the best ad creative.

Confirm that your landing pages have consistent messaging with the ad copy, including matching offers, product images, and price points.

Message mismatch is one of the top reasons for high click-through but low conversion rate; users who feel misled bounce immediately.

Check whether you are using dedicated landing pages for key campaigns versus sending all traffic to generic collection or home pages.

Campaign-specific landing pages convert 2-3x better than generic pages because they continue the exact narrative the ad started.

Review whether campaigns are using Campaign Budget Optimization (CBO) or ad set budgets, and confirm the choice is intentional.

CBO works well for letting the algorithm distribute spend to winning ad sets, but manual ad set budgets give you more control during testing phases.

Check that no single campaign is receiving less than $30-50 per day (or 2-3x your target CPA) in budget.

Underfunded campaigns never exit the learning phase; if you cannot afford to give a campaign at least 50 conversions per week in budget, consolidate it.

Verify your bid strategy for each campaign and confirm it aligns with your goals: lowest cost, cost cap, or bid cap.

Lowest cost is the default and works well at smaller budgets, but cost cap or bid cap becomes essential when scaling to maintain profitability targets.

Analyze your daily and weekly spend pacing to identify campaigns that consistently underspend their allocated budget.

Underspending signals that your audience is too narrow, your bid is too low, or your creative has fatigued, each requiring a different fix.

Evaluate your overall budget split between prospecting and retargeting and compare it against the 70/30 to 80/20 benchmark.

Over-investing in retargeting is the most common budget mistake in e-commerce Meta Ads; it feels safe but caps your growth ceiling.