Prioritize Link Building with Search Console’s ‘Average Position’: A Practical Playbook

Many creators see a long list of pages with a middling average position in Google Search Console and assume they all deserve link outreach. That’s the fast track to wasted outreach and low ROI. This playbook translates Search Console’s average position into an actionable link building prioritization framework based on traffic potential, conversion intent, and SERP feature risk so small teams and solo creators can focus outreach where it moves the needle.

Why 'Average Position' is misunderstood (and why it still matters)

Search Console’s Average position is a useful signal, but it is an aggregate: it blends rankings across queries, dates, and devices. A page with an average position of 12 might rank #3 for some high-intent queries and #40 for lots of long-tail keywords. If you build outreach around the raw average, you’ll promote the wrong pages and miss high-impact opportunities.

That said, average position is a low-effort, high-value starting point for an SEO triage. Use it to surface candidates, then apply layers of filters to prioritize outreach by expected content ROI.

Overview: The 6-step prioritization framework

1. Export Search Console data by page and query
2. Convert average position into realistic traffic potential
3. Score conversion intent for each query
4. Assess SERP feature risk
5. Combine into a priority score
6. Pick outreach tactics by priority bucket

Who this is for

Content creators, influencers, and publishers with small teams or limited outreach capacity who need a repeatable way to decide where to focus link-building time.

Step 1 — Export and reshape Search Console data

Start in Search Console: Performance > Pages > Click the target page > Queries. Export the page-query-level data for the last 90 days (or 12 months if you have seasonal content). Include impressions, clicks, CTR, and position.

Build a sheet with one row per query + page and columns for:

• Query
• Page URL
• Impressions
• Clicks
• Average position for that query

Tip: If your team uses automation, you can fetch this programmatically with the Search Console API — but manual exports work fine for most small teams.

Step 2 — Estimate traffic potential from position

Average position must be turned into expected clicks to know whether an improvement is worth chasing. Use a simple CTR model and impressions to estimate baseline clicks if rank moves up.

Example CTR assumptions (conservative):

• Positions 1–3: 20% / 10% / 7%
• Positions 4–10: 4%–2%
• Positions 11–20: 1%–0.5%

For each query, multiply impressions by the CTR for the projected rank. Then compare current estimated clicks to the clicks if the page moved into the top 3 or top 5. This gives you a per-query traffic lift estimate. Aggregate lifts per page to get page-level traffic potential.

Practical example

Page A ranks average position 8 for a query with 5,000 impressions. At position 8, CTR might be ~2% (100 clicks/month). If moving to position 3 increases CTR to 7% (350 clicks/month), the lift is ~250 clicks/month. Multiply by conversion rate to get value (more on that below).

Step 3 — Score conversion intent (the multiplier)

Traffic alone isn’t ROI. A query that converts matters more than a dozen awareness queries. Classify each query’s intent into one of three tiers:

• High-conversion (transactional/commercial): product comparisons, buy intent, affiliate keywords
• Mid-conversion (research/consideration): “best X”, “vs”, “how to choose”
• Low-conversion (informational/awareness): “what is”, trend stories, broad topics

Assign a simple multiplier: High = 1.0, Mid = 0.4, Low = 0.1. Multiply estimated traffic lift by the multiplier to get a conversion-weighted traffic score. If you have historical conversion data, use it instead of the multipliers.

Step 4 — Add SERP feature risk

SERP features (featured snippets, knowledge panels, images, video carousels, shopping listings) can steal clicks even if you rank #1. For each high-impression query, check the SERP and tag feature types that appear.

Penalty suggestions (apply as a % reduction to expected clicks):

• Featured snippet present: -40%
• Video carousel or images dominating the top: -30%
• Shopping/ads above results: -50%
• No features: 0%

These are heuristic — validate them against your CTR data and tune. The idea is to avoid spending resources chasing positions that still won’t deliver clicks.

Step 5 — Compute a priority score

Combine the pieces into a single score per page. A simple weighted formula works and is easy to explain to stakeholders:

Priority score = (Traffic Lift x Intent Multiplier x (1 - SERP Feature Penalty)) x Authority Adjustment

• Traffic Lift: aggregated clicks gained if page moves to target rank
• Intent Multiplier: 1.0 / 0.4 / 0.1 as above
• SERP Feature Penalty: 0.0–0.7
• Authority Adjustment: small-team modifier (0.8–1.2) to favor pages you can realistically impact

Sort pages by this score. The top decile are your “A” targets—pages where outreach is most likely to move the needle.

Quick prioritization buckets

• A — High ROI: high traffic lift, high intent, low SERP risk
• B — Worth a try: moderate lift or intent, some SERP features
• C — Deprioritize: low lift, low intent, or heavy SERP feature competition

Step 6 — Outreach playbook: match tactics to priority

Not all link-building actions have the same cost or impact. Match outreach to bucket:

Bucket A (High ROI)

• Target: link inserts into high-authority resources, guest posts with contextual links, resource page placements
• Tactic: personalized outreach that highlights direct traffic lift and provides concise link placement options
• Investment: high — consider offering data, exclusive quotes, or reciprocal promotion
• Reference: think narrative-driven outreach where stories help earn links — see our piece on Link Building in the Age of Narrative.

Bucket B (Moderate ROI)

• Target: roundups, curated lists, topical guest posts
• Tactic: semi-personalized templates and follow-up sequences; test different messaging
• Investment: medium — reuse collateral (infographics, short data points)
• Tip: use the guidance in our guide on when automation can help — When to Let AI Execute Your Link-Building Workflows.

Bucket C (Low ROI)

• Target: internal linking improvements, on-page optimization, or archived for future scale
• Tactic: low-cost outreach (social pushes, community mentions) or no outreach — invest in content improvement instead
• Investment: low

Small-team operational tips

• Timebox outreach: allocate 30–60 minutes/week to A-list targets only.
• Batch personalization: create modular templates and swap one variable (name, resource link, specific benefit).
• Use mini-experiments: test two outreach angles on similar A pages and watch live clicks to validate your scoring model.
• Leverage events and partnerships for higher-authority links — our guide on live events has ideas for earning links beyond cold outreach.

Measuring success (what to track)

Track these KPIs per prioritized page:

• Monthly clicks from Search Console
• Rank movement for target queries
• Referral links acquired (domain authority and relevance)
• Conversion lift (signups, revenue, leads) if available

Evaluate after a 90-day window. If rank and clicks didn’t move despite earned links, revisit SERP feature penalties and intent classification.

Common pitfalls and fixes

Pitfall: Chasing low-intent traffic

Fix: Use intent multipliers. If a page’s score is driven by informational queries, prioritize on-page enhancements or internal links instead of costly outreach.

Pitfall: Ignoring SERP features

Fix: If featured snippets or videos dominate, either create the competitive asset (video, listicle designed for snippets) or deprioritize the page for links.

Pitfall: Over-optimizing for average position

Fix: Look at query-level positions and impressions. Use impression-weighted averages or directly model clicks — don’t rely on the single aggregate metric.

Final checklist for your first triage

1. Export page > query data from Search Console for the last 90 days.
2. Estimate traffic lifts using a CTR model and target ranks (top 3 or top 5).
3. Tag queries by conversion intent and apply multipliers.
4. Audit the SERP for feature risk and apply penalties.
5. Compute priority scores and sort pages into A/B/C buckets.
6. Execute targeted outreach only for A and select B pages; improve content/internal linking for C pages.

Average position is the right place to start, but not the final decision-maker. Use it to surface candidates and then apply traffic potential, conversion intent, and SERP feature risk to prioritize outreach. Doing so focuses scarce outreach hours on pages that actually move the needle — increasing search visibility, clicks, and ultimately content ROI.

Want more practical tips for creators on combining link-building with creative promotion strategies? See our posts on using narrative and humor to drive traffic — like Link Building in the Age of Narrative and Harnessing Humor to Drive Social Traffic.