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Improving Facebook Ads Relevance Diagnostics: Fixing 'Below Average' Quality (2026)

2026-01-28
4 min read
Kiril Ivanov
Kiril Ivanov
Performance Marketing Specialist

Google has "Quality Score." Meta has Relevance Diagnostics. It is a report card that grades your ad compared to competitors targeting the same audience. It appears after ~500 impressions.

The grades:

  • Above Average (Top 20%)
  • Average (35% - 55%)
  • Below Average (Bottom 35%, Bottom 20%, Bottom 10%)

If you are Bottom 10%, Meta charges you a "Quality Tax" (Higher CPM). If you are Above Average, Meta gives you a "Quality Discount" (Lower CPM).

In this "Mega-Authority" guide, we cover:

  1. Quality Ranking: Visuals and Hook.
  2. Engagement Rate Ranking: Likes/Comments/Clicks.
  3. Conversion Rate Ranking: The Offer/Landing Page.
  4. The Matrix: Diagnosing the mix.

Part 1: Quality Ranking (The "Stop" Signal)

"How does the ad look?"

  • Below Average?
    • Cause: Creating "Ad-like" images (Stock photos, aggressive text overlays). Low resolution. Bait-and-switch.
    • Fix: Switch to native UGC. Remove "Salesy" text.

Part 2: Engagement Rate Ranking (The "Click" Signal)

"Are people interacting?"

  • Below Average?
    • Cause: Boring hook. No reason to click.
    • Fix: Punchier initial 3 seconds. Ask a question in the copy. Use a "See Price" CTA.

Part 3: Conversion Rate Ranking (The "Buy" Signal)

"Are people buying after clicking?"

  • Below Average?
    • Cause: Disconnect between Ad and Landing Page. Slow site speed. Bad Offer.
    • Fix: Check "Message Match." If ad says "50% Off," page must say "50% Off."

Part 4: The Diagnostic Matrix

Scenario A: Low Quality / Low Engagement / High Conversion

  • Diagnosis: The ad is ugly and clickbait, but the product is great.
  • Action: Polish the creative but keep the offer.

Scenario B: High Quality / High Engagement / Low Conversion

  • Diagnosis: Viral Video. Everyone loves watching it, nobody buys.
  • Action: The creative is too entertaining. Make the product the hero. Fix the Landing Page.

Scenario C: Average / Average / Average

  • Diagnosis: "Meh."
  • Action: Test a radical new angle.

Part 5: Summary & Checklist

Your Action Plan:

  1. Filter your ads by "Active."
  2. Add the 3 Relevance Columns to your view.
  3. Sort by Spend.
  4. Kill any ad that is "Bottom 20%" in Quality Ranking (It is inflating your costs).
  5. Iterate based on the specific failing metric.

Don't ignore the report card.


The 3×3 Diagnostic Matrix

The three Relevance Diagnostics — Quality Ranking, Engagement Rate Ranking, Conversion Rate Ranking — can each be Above Average, Average, or Below Average. That's 27 possible combinations. Here are the nine most common states and the precise action for each:

QualityEngagementConversionDiagnosisAction
Below AvgBelow AvgBelow AvgEverything is brokenRebuild: new audience, new creative, new offer
Below AvgAverageAverageAd looks spammy or low-trustRewrite primary text; add social proof; remove clickbait hook
AverageBelow AvgAverageCreative isn't compellingReplace visual; test video vs static; improve hook
AverageAverageBelow AvgFunnel breaks post-clickAudit landing page for message match and load speed
Above AvgBelow AvgBelow AvgStrong brand trust, weak creativeNew creative formats (UGC, testimonial video)
Above AvgAbove AvgBelow AvgEverything works until conversionFix landing page CTA and form friction
Below AvgAbove AvgAverageClick-bait — drives clicks, damages brandAlign creative with actual offer; reduce sensationalism
AverageAbove AvgAbove AvgHealthy — iterate, don't fixScale budget; test new audiences with same creative
Above AvgAbove AvgAbove AvgWinning ad — protect itExtract Post ID; duplicate to new audiences

The most insidious state is the bottom-left of the matrix: Below Avg / Above Avg / Average — clickbait. High engagement hides the quality problem. Meta's auction will eventually down-rank this ad as users engage but don't convert, driving up CPMs even while CTR stays high.

Kiril Ivanov

About the Author

Performance marketing specialist with 6 years of experience in Google Ads, Meta Ads, and paid media strategy. Helps B2B and Ecommerce brands scale profitably through data-driven advertising.

View author profile Connect on LinkedIn

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