Conducting Competitive Benchmarking for SEO Insights

Nadia Gastrom | | 4 min read

Conducting Competitive Benchmarking for SEO Insights

Introduction: What competitive benchmarking solves (and what it doesn’t)

Competitive benchmarking for SEO is a structured comparison of your pages against the pages that outrank you for the same queries, to isolate why you’re losing.

Used for troubleshooting, it tells you whether the gap is relevance (content/intent), authority (links/brand), or experience and SERP fit (technical constraints and feature alignment).

Benchmarking is about patterns and priorities—not copying competitors line-by-line or chasing every keyword they rank for. When I run this with in-house teams, the deliverable is a short list of fixes tied to specific queries and landing pages.

This workflow covers four steps: pick true SERP competitors and queries, collect a consistent baseline dataset, diagnose content/on-page gaps, and assess authority signals without defaulting to “build links.”

Step 1: Choose the right competitors and the right queries

Start with SERP competitors: domains that repeatedly rank on page 1 for the queries you care about. Business competitors are irrelevant if they don’t show up.

How to pick competitors (fast):

  • Pull 10–20 core non-brand queries tied to the stalled area.
  • Search them using the same location/device.
  • Note domains that recur in the top 10.
  • Select 3–5 max.

Scope the query set to match the problem:

  • Include core commercial queries.
  • Add a small sample of supporting informational queries (or stick to one topic cluster).
  • Separate brand vs non-brand so brand strength doesn’t hide non-brand gaps.

Example: for “best project management software for agencies,” likely SERP competitors are a review/list site, a direct SaaS competitor’s “best for agencies” page, and a niche agency blog with a detailed roundup. Exclude a general tech news site that appears once due to a trending story; it’s not a stable comparator.

Step 2: Collect a baseline dataset (keywords, URLs, SERP features)

Get an apples-to-apples dataset before you interpret anything. A spreadsheet is fine if it’s consistent.

Minimum fields to capture:

  • Query
  • Your ranking URL (landing page)
  • Competitor ranking URLs (top 3–5)
  • Position (or buckets like 1–3, 4–10, 11–20)
  • Intent type (informational / commercial / transactional)
  • SERP features present (featured snippet, PAA, video, local pack)

Collection method (tool + spot-check):

  • Export from any rank tracker/SEO suite (Ahrefs, Semrush, Moz, Search Console + a rank tool).
  • Spot-check the top 10–20 highest-value queries in a clean browser to confirm current top URLs and features. In my experience, exports miss nuance like “PAA dominates” or “video results are constant.”

Consistency rules:

  • Keep location, device, and date window the same.
  • Always record the landing page URL for every site. Wrong-page ranking (or URL swapping from cannibalization) is a common reason you “have content” but can’t move.

Step 3: Diagnose content and on-page gaps (the usual culprit)

Most losses show up here: intent mismatch, missing coverage, weak on-page signals, or internal links that don’t support the target page.

Classify intent per query (informational / commercial / transactional), then check whether your page type matches what the SERP rewards. If page 1 is mostly comparisons and you’re pushing a feature page, you’re fighting the format.

High-signal checks:

  • Subtopics competitors cover (headings/questions you don’t answer)
  • Freshness where the SERP expects updates
  • Depth vs the page-1 norm (match what wins; don’t overbuild)
  • Visuals/FAQs only if common in the SERP
  • Clear answer/value near the top

On-page comparisons: title/H1 alignment, headings that reflect key subtopics, internal links pointing to the ranking page, and schema only when it produces visible SERP results.

Example: if a “best X software” SERP consistently shows comparison tables and pricing sections, but your page is a short feature list, treat it as a structural gap: add comparison criteria, pricing notes (“starts at” or ranges), and “best for” use-cases.

Step 4: Benchmark authority signals without over-crediting links

Next, test whether authority is the constraint—or whether you’re trying to link your way out of an intent/content problem.

What to compare:

  • Referring domains and link quality to the specific ranking page (not just the homepage)
  • A directional view of site strength trend (not a score chase)

Links likely matter when page 1 is dominated by high-authority domains despite similar content, or when one competitor has unusually strong page-level links to the exact URL ranking.

Avoid the “just build links” trap: only prioritize link work after you’ve reached intent/content parity. When I ran audits in this order, intent fixes often moved rankings without new links; link work mattered most once pages were already SERP-eligible.

Outputs: pick 1–2 pages closest to winning (often positions ~4–15 with a clean intent match) for link investment, and define 1–2 linkable asset angles that support those pages (original comparison data, templates, benchmarks, a calculator), not generic guest posts.

Conclusion: Turn benchmarks into a short priority list

Benchmarking only matters if it ends in decisions. For each priority query, label the failure mode (wrong page, intent mismatch, coverage/on-page, internal linking, or authority limit), then fix the highest-leverage items first.

Run a tight loop: benchmark → ship fixes on one cluster → re-measure in 30–45 days. Finish one scoped set, document what moved, then reuse the same workflow on the next cluster.

Sources

  1. Google Search Quality Rater Guidelines (PDF)
  2. Google Search Central: Understand your site’s search performance
Nadia Gastrom

Article author

Nadia Gastrom

Nadia Gastrom is an independent SEO consultant and writer with more than three years of experience helping businesses improve their organic search visibility through SEO strategy, content optimization, and technical SEO. She has worked extensively with SEO platforms such as Semrush and Ahrefs and has a particular interest in how search is evolving beyond traditional rankings. Nadia is currently exploring Answer Engine Optimization (AEO), AI-powered search, and the ways businesses can make their content more useful and discoverable across emerging search experiences. When she is not researching search trends or writing about SEO, Nadia enjoys travelling, discovering new places, and spending time with dogs. She continues to follow the SEO and AEO industry closely to understand what is changing and what marketers should be preparing for next.