Benchmarking Your AI Search Performance by Sector in 2026

Why a single number tells you nothing

An e-commerce client calls me in February 2025. Their site shows an LCP of 3.2 seconds on mobile. They ask if that’s good.

My answer: I don’t know yet.

Not because I lack data. Because a number without sector context is useless. In luxury, 3.2 seconds might be the sector norm—all competitors are at 3.5 seconds because of high-resolution visuals. In B2B SaaS, 3.2 seconds puts you out of the race against competitors at 1.8 seconds.

Sector benchmarking changes everything. It transforms a raw number into relative position. It reveals whether you’re in the top 20% of your sector or in the last quartile. It identifiés gaps that truly matter for your visibility.

According to DebugBear in their study published on Search Engine Journal, the central question isn’t « am I fast » but « am I faster than my direct competitors for the same queries ».

I’ll show you how to build this benchmark. Not with complex tools. With PageSpeed Insights, a spreadsheet, and a methodology proven across 47 clients since January 2024.

You’ll map your true position. Identify the 3 pages with maximum impact. And know exactly how many milliseconds separate you from the top 3 in your sector.

The 3 metrics that impact your AI Search visibility

Google measures user expérience with three Core Web Vitals. Each targets a specific aspect of perception.

Largest Contentful Paint (LCP): time before the largest visible element displays. Good threshold: ≤ 2.5 seconds. Needs improvement: 2.5–4.0 seconds. Poor: > 4.0 seconds.

This is perceived speed. A visitor seeing blank space for 4 seconds bounces. An LCP of 1.8 seconds feels instantaneous, even if the rest is still loading.

Interaction to Next Paint (INP): delay between a user action (click, tap, keystroke) and the visual response. Good threshold: ≤ 200 milliseconds. Needs improvement: 200–500 ms. Poor: > 500 ms.

INP replaced FID in March 2024. It measures all interactions, not just the first. A site with 180 ms INP feels smooth. A site at 600 ms feels constantly laggy.

Cumulative Layout Shift (CLS): visual stability during load. Good threshold: ≤ 0.1. Needs improvement: 0.1–0.25. Poor: > 0.25.

CLS measures element jumps. An image pushing text down. An ad shifting a button at click time. Score 0.05 = stable. Score 0.3 = frustrating.

According to DebugBear’s study published on Search Engine Journal, to get the ranking boost from Core Web Vitals, you must pass all three « good » thresholds on at least 75% of your real visits.

Not 70%. Not « most ». 75% minimum.

Even one of these three in the red zone is enough to exclude you from the visibility bonus. That’s why comparing your sector performance must cover all three metrics simultaneously.

Step 1: Extract your baseline data

Start with your own site. Not competitors. Establish your baseline first.

Open PageSpeed Insights (pagespeed.web.dev). Enter your homepage URL. Run the analysis. Wait 30–45 seconds.

You get two datasets: mobile and desktop. Focus on mobile first. From my observations across 650+ clients, 68% of organic traffic in B2C e-commerce now comes from mobile, 52% in B2B.

Record three numbers in a spreadsheet:

• Mobile LCP (seconds, one decimal)
• Mobile INP (milliseconds, integer)
• Mobile CLS (decimal score, two figures)

Real example from a cosmetics client tested March 2025:

• LCP: 3.4 seconds
• INP: 340 milliseconds
• CLS: 0.18

Repeat for desktop. Same page, same three metrics. Desktop performance is often better—faster connections, more powerful processors.

Now identify your 3–5 strategic pages. Not every page. The ones generating organic traffic or targeting your priority AI Search queries.

For an e-commerce site: homepage + 2 main catégories + 1 flagship product page. For a services site: homepage + 2 service pages + 1 resource page.

Repeat PageSpeed for each page. Build a table with 4–6 rows (your pages) and 6 columns (LCP/INP/CLS mobile + LCP/INP/CLS desktop).

Time for this step: 15–20 minutes. You now have your starting position, quantified.

Step 2: Map your direct competitors

Now add sector context. Measure 3 to 5 direct competitors with the exact same method.

Direct competitors = sites ranking for your target queries. Not out-of-category giants. If you sell running shoes, don’t benchmark against Nike.com. Benchmark against the 3 sites appearing in the same SERPs as you.

How do you identify these? Type your 5 priority queries into Google. Note the 3 domains appearing most often in the top 5 (excluding marketplaces like Amazon).

For each competitor, repeat PageSpeed Insights:

• Homepage mobile + desktop
• 2–3 pages equivalent to your strategic pages
• Same table, new rows

Real example: outdoor equipment client tested January 2025. Three competitors analyzed. Homepage mobile LCPs:

• My client: 2.8 seconds
• Competitor A: 2.1 seconds
• Competitor B: 3.6 seconds
• Competitor C: 1.9 seconds

Immediate relative position: my client is 3rd out of 4. Gap to leader: 0.9 seconds. Gap to last place: -0.8 seconds.

This mapping reveals your ecosystem position. You’re no longer in the dark. You know whether you’re in the top 25% sectorially or the last quartile.

Critical methodology point: always test at the same time of day. Performance fluctuates with server load. I systematically test between 10am and 12pm French time, never Monday morning or Friday afternoon.

Time for this step: 30–40 minutes for 3 complete competitors.

Step 3: Build the comparative dashboard

You have raw data. Now transform it into a visual dashboard that reveals priorities.

Create a second sheet in your spreadsheet. Title: « Sector benchmark mobile ». Build a synthetic table.

Columns: Site | LCP | LCP Rank | INP | INP Rank | CLS | CLS Rank | Composite Score

Rows: your site + 3–5 competitors, sorted by descending composite score.

Rank calculates automatically: 1 = best performance in the list, 4 = worst. For LCP and INP, lower is better. For CLS, lower is better too.

Composite score is the average of ranks. Site that’s 2nd on LCP, 1st on INP, 3rd on CLS = score (2+1+3)/3 = 2.0.

Real example from an online learning client (February 2025, 4 sites compared, homepage mobile):

This table immediately reveals three things:

• My client is 2nd out of 4 (honorable position)
• INP is the weakness (220 ms, rank 3, close to the « needs improvement » threshold of 200 ms)
• CLS is the strength (0.06, best in the sector)

Repeat this table for desktop. Often you’ll see different rankings. A site might be excellent mobile but mediocre desktop, or vice versa.

Add conditional color coding: green for ranks 1–2, orange for rank 3, red for rank 4+. Your dashboard becomes readable in 5 seconds.

Time for this step: 15 minutes of formatting.

Identify the 3 pages with maximum impact

You have the benchmark. Now decide what to optimize first.

Not every page. Not « we’ll see ». The 3 specific pages generating the biggest return for the least effort.

Criterion 1: gap to « good » threshold. A page at 2.7 seconds LCP is 0.2 seconds from the 2.5 threshold. A page at 4.2 seconds is 1.7 seconds away. The first is priority—accessible gains.

Criterion 2: current organic traffic. A page receiving 800 visits/month missing the LCP threshold impacts visibility on 800 sessions. A 50-visit/month page impacts 50 sessions. Prioritize traffic.

Criterion 3: competitive gap. If you’re at 2.9 seconds LCP and your 3 competitors are between 2.8 and 3.2 seconds, you’re sector-normal. If you’re at 3.8 seconds and they’re all under 2.5 seconds, you have real disadvantage.

Scoring method I apply with my clients:

• Threshold gap score: (threshold – current value) × 10. Example: LCP 2.7s → (2.5 – 2.7) × 10 = -2 points. LCP 1.9s → (2.5 – 1.9) × 10 = +6 points.
• Traffic score: monthly visits / 100. Example: 800 visits → 8 points.
• Competitive score: (your rank – 1) × -3. Example: rank 3 → (3-1) × -3 = -6 points. Rank 1 → 0 points.

Add the three scores. The 3 pages with the lowest scores are your optimization priorities.

Real case: sports e-commerce client (March 2025). 6 pages analyzed. Scores:

Priority 1: trail category (score -18, catastrophic LCP + rank 4).

Priority 2: running category (score -6, high traffic but rank 4).

Priority 3: homepage (score +18 but massive traffic, small gain = big impact).

You now have a quantified action plan. You’re not working by feel.

Refresh the benchmark every 45 days

A benchmark isn’t a static document. Your competitors optimize too. Google thresholds may shift. Your own performance fluctuates with deployments.

I recommend refreshing every 45 days. Not weekly (too much noise). Not every 6 months (too slow to react).

45 days gives you time to deploy an optimization, measure its real impact in the field (not just in lab), and compare before/after.

Refresh process: take your spreadsheet. Add a new sheet dated (« April 2025 benchmark », « June 2025 benchmark »). Rerun PageSpeed Insights on the same pages, same time of day.

Compare rank evolution. Not just your absolute numbers. Your relative rank.

Example: you go from 2.8s to 2.4s LCP between January and March. Excellent. But if competitors moved from 2.1s/3.6s/1.9s to 1.8s/2.9s/1.7s, your rank didn’t shift. You’re still 3rd. You progressed in absolute, stalled in relative.

Relative rank is what impacts AI Search visibility. Google compares sites for a given query. Being « good » in absolute but « average » relative to competitors gives no advantage.

Case observed at an HR SaaS client (January–June 2025 tracking):

• January: LCP 3.1s, rank 4/5
• March: LCP 2.6s, rank 3/5 (competitor D drops to 4.2s)
• June: LCP 2.3s, rank 2/5 (we + competitor B optimize, competitor A stalls at 1.9s)

Continuous progress. Two ranks gained in 5 months. Organic traffic +37% over the same period (multifactorial, but technical SEO contributes).

Document every iteration. You build a history revealing sector trends. If your entire sector improves 15% every quarter, you need 20% improvement to gain ground.

Archive old sheets. Never delete. You’ll need to compare April 2025 vs April 2026 to measure annual progress.

What the benchmark doesn’t measure

Core Web Vitals are a proxy for user expérience. Not expérience itself.

A site can have perfect 1.6-second LCP and catastrophic expérience if displayed content is unreadable, navigation is confusing, CTAs are invisible.

The sector benchmark tells you if you’re technically competitive. It says nothing about content quality, semantic architecture soundness, or answer depth.

I’ve seen sites rank positions 1–3 with average Core Web Vitals (LCP 3.2s, INP 280ms) because their content was 10× more complete than competitors. I’ve seen the opposite: ultra-fast sites (LCP 1.4s) stuck on page 2 because content was shallow.

Core Web Vitals are a confirmed ranking factor since June 2021. But they’re one of 200+. Per official Google statements (Search Central Blog), content and relevance signals weight far more heavily than expérience signals.

What does that mean concretely? Optimizing Core Web Vitals won’t jump you from page 5 to page 1. It might move you from position 4 to position 2. Or from position 11 to position 8.

It’s a differentiator when everything else is equal. Two sites with comparable content quality, comparable authority, comparable architecture—the faster one wins.

The sector benchmark tells you whether you’re in the race or out of it on this specific criterion. It guarantees nothing alone. It eliminates a disadvantage or creates a small edge.

Another limit: PageSpeed Insights measures lab conditions plus a sample of field data (CrUX, Chrome User Expérience Report). CrUX data is aggregated over 28 days. It lags. If you optimize today, you won’t see CrUX impact for 4 weeks.

Also use real-time field monitoring (DebugBear, SpeedCurve, Cloudflare Web Analytics) to see immediate effects. PageSpeed benchmark gives sector vision. Real-time monitoring gives responsiveness.

Complete application: furniture e-commerce case

I finish with a full case. Furniture e-commerce client, 1,200-item catalog, 8,000 organic sessions/month in December 2024.

Initial request: « We’ve stalled for 8 months. We invested $6,000 in backlinks. Nothing moved. »

Initial audit (January 2025). I build sector benchmark with 4 direct competitors. I test 5 pages: homepage + 3 catégories + 1 flagship product page.

Mobile results:

Dead last on all three metrics. No page passed the « good » LCP threshold. 60% of pages in red zone on INP.

The problem wasn’t backlinks. It was technical expérience. They were invisible to Google AI Search because technically outdated.

Action plan prioritized on 3 pages (sofa category, tables category, homepage):

• WebP images + native lazy loading → LCP -1.4s average
• Remove 3 blocking third-party scripts → INP -140ms
• Reserve space for carousel images → CLS -0.16

Deployed February 2025. New benchmark March 2025:

Three ranks gained on LCP. Two on INP. Four on CLS (best in the sector).

Traffic impact (March 2025 vs December 2024): +820 organic sessions (+10.3%). Conversion impact: bounce rate -8.4 percentage points, average session duration +47 seconds.

Total optimization cost: $2,400 (15 hours front-end dev + 8 hours testing). Measurable ROI by month two.

The sector benchmark revealed the true problem. Backlinks weren’t useless, but secondary. The blocker was technical. Once removed, the rest of SEO worked.

That’s what a well-built benchmark gives you: quantified truth about your real position.

Stéphane Jambu

SEO & AI Engineer

I build growth systems / AI / Neuroscience | 650+ clients · 80 LinkedIn testimonials · 30 years of expertise · 15 years of systems running without me.

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