What SERP performance analysis is
SERP performance analysis treats the search results page itself as data. Not just the position of your URL, but the shape of the SERP around it. What features are present (featured snippet, local pack, People Also Ask, AI Overview, knowledge panel). How much real estate the regular organic results actually have above the fold. Which competitors hold which positions and what their snippets look like. The analysis exists because position alone is no longer a clean proxy for traffic.
The work has two layers. Quantitative: pulling CTR-by-position data from GSC and segmenting it by query intent, device and SERP shape. Qualitative: manually running priority queries through the SERP to see the actual feature mix and competitive positioning. Both layers feed the same question: where is the lift, and which optimisation moves earn it.
CTR by position in 2026
The widely cited Advanced Web Ranking CTR curves and the older AOL leak from 2006 are still being quoted in 2026. Both are out of date. The honest 2026 curves vary by intent and SERP shape, and they have shifted downwards as Google has added more SERP features above the regular results.
Clean commercial SERP, desktop, no AI Overview
- Position 1: 25 to 35 percent CTR
- Position 2: 12 to 18 percent
- Position 3: 8 to 12 percent
- Position 4: 5 to 8 percent
- Position 5: 3 to 5 percent
- Positions 6-10: under 3 percent each
SERP with AI Overview above, desktop, informational intent
- Position 1: 15 to 25 percent CTR (20 to 30 percent reduction versus the clean curve above)
- Position 2: 8 to 12 percent
- Position 3: 5 to 8 percent
- Positions 4-10: drop in line with the headline reduction
Local pack present, mobile, local-intent query
- Local pack position 1: 18 to 22 percent
- Local pack position 2: 10 to 14 percent
- Local pack position 3: 6 to 10 percent
- Regular organic position 1 (below the pack): 5 to 10 percent. The pack absorbs most of the click volume.
These ranges are observed across Perth and WA client GSC accounts and are consistent with publicly reported industry studies. They are not laws of physics; they are central tendencies. Branded queries skew higher (position 1 can hit 50 to 70 percent CTR for a known brand searching for itself). Long-tail informational queries skew lower because the answer often comes from the snippet itself. Use the ranges as a sanity check, not as a target.
SERP features and their impact
Six SERP features account for most of the click-curve distortion we see across client SERPs.
Featured snippet
The boxed answer at the top of the SERP. Earns roughly 30 to 50 percent of the click volume that would have gone to position 1 on informational queries. On commercial queries the snippet is often skipped and the click goes to the regular results. Worth optimising for if your traffic is informational-heavy. See featured snippets.
People Also Ask
The expandable question box, usually mid-SERP. Each PAA entry that expands earns a few clicks. The cumulative effect across a SERP is significant. Optimising for PAA is the same work as optimising for featured snippets: clear question-and-answer formatting with valid FAQPage schema.
Sitelinks
The additional links shown under a brand's main result. Increase your share of the click volume on branded queries. You do not earn sitelinks directly; Google generates them from your site structure when you rank well on brand terms.
Local pack
The map plus three business listings on local-intent queries. Dominates the SERP on Australian local searches. Local pack position 1 at 18 to 22 percent CTR is one of the most valuable placements in search, full stop. See the Local SEO pillar and Google Business Profile.
Knowledge panel
The right-hand-side panel on entity queries (brand names, public figures, well-known places). Earns its own clicks (image, website, social links) and competes with the regular organic results. For most businesses the work is to ensure your Knowledge Panel exists and is accurate; you cannot directly compete with someone else's Panel.
AI Overview
Covered in its own section below. Worth flagging here as the SERP feature with the biggest 2026 click-curve impact.
AI Overviews and the click curve
The single biggest change to SERP CTR in 2026 is the rollout of AI Overviews. The headline impact: 20 to 30 percent reduction in click volume on pure informational queries where the Overview is present. Commercial intent is less affected. Local intent is barely affected.
The measurement implication for SERP performance analysis. Always segment by whether the underlying SERP has an AI Overview. A page that holds rank but loses clicks usually has an AI Overview above it now. The fix is not to win a higher rank; it is to compete for the citation inside the Overview or to ride the click loss out on commercial pages that are less affected.
See the Google AI Overviews chapter for the citation-optimisation playbook and the AI Search pillar for the wider context.
A manual SERP analysis workflow
The monthly workflow we run on every client's top 20 priority queries.
- Pull the priority query list. Top 20 by either current rank, target keyword priority, or commercial value. Usually overlaps with the rank-tracker keyword list.
- Run each query in Google Search, logged out, with the target location set. For Perth queries, use a VPN to a Perth IP if you are not physically here. For multi-suburb businesses, run each priority suburb separately.
- Record the SERP shape. Which features are present (AI Overview, featured snippet, PAA, local pack, sitelinks, ads), how much real estate the regular organic results have above the fold, and your current ranking position.
- Record the top 3 to 5 cited competitors. For AI Overviews, which sources are cited. For featured snippets, which page holds the snippet. For local pack, which businesses are in positions 1 to 3.
- Note any changes from last month. New SERP features, new competitor citations, new ads above the fold. The change log is more useful than the snapshot.
The workflow takes 60 to 90 minutes for a 20-query list. Run it on the same day every month for trend continuity. Pair with the GSC CTR-by-position data quarterly for the quantitative side.
Prioritising from the analysis
The output of the SERP analysis feeds the next round of optimisation prioritisation. Three patterns drive most decisions.
Page ranks but underperforms expected CTR. Title tag or meta description weakness. The fix is on-page CTR optimisation: rewrite the title tag for the query, tighten the meta description, add structured data that triggers rich snippets. See title tags.
Page ranks well but loses clicks to an AI Overview. Compete for the citation inside the Overview by adding entity schema, tightening the direct answer at the top of the page, and adding FAQPage schema. See the AI Overviews chapter.
Page does not rank well enough to attract clicks at any CTR. The work is upstream: content depth, topical authority, on-page SEO, backlinks. See the On-Page SEO pillar and Off-Page SEO pillar.
Common mistakes
- Pulling CTR-by-position from GSC and segmenting by intent and SERP feature.
- Running manual SERP checks on priority queries monthly to catch feature changes.
- Reading position 1 differently when an AI Overview sits above it.
- Tracking local pack position separately from regular organic for local businesses.
- Quoting 2014 CTR curves as if they still applied in 2026.
- Assuming position 1 is always 30 percent CTR regardless of SERP shape.
- Treating CTR drops as ranking failures when the cause is a new SERP feature.
- Ignoring the local pack on commercial local queries.
Perth and WA context
Two SERP patterns specific to Perth and WA.
Local pack dominates suburb-suffixed queries. "Plumber Fremantle", "electrician Joondalup", "dentist Mandurah". The local pack is almost always present, takes most of the click volume, and pushes the regular organic results down a screen. The SEO analysis on these queries should treat the local pack position as the primary scorecard and the regular organic position as a secondary metric. See Local SEO and Local SEO Perth.
WA mining and resources queries skew long-tail informational. "FIFO roster types", "what is a planned shutdown", "mining equipment classifications". These are high-volume informational queries that increasingly trigger AI Overviews and featured snippets. The SERP analysis on these queries should focus on the citation game inside the Overview rather than chasing position-1 CTR. See mining SEO and SEO Karratha.
For the wider context, the GSC chapter covers the data source, the rank tracking chapter covers the keyword-level scorecard that complements SERP analysis, the title tags chapter covers the most direct CTR lever, the featured snippets chapter covers the snippet optimisation playbook, and the AI Overviews chapter covers the dominant 2026 SERP feature. Clients ready for SERP-side optimisation can engage the SEO service or start with a free SEO audit.