Finding Low-Hanging Fruit Keywords in Search Console

Most SEO teams waste time chasing keywords that need new pages, new links, or months of authority-building. The faster wins are often already visible in Search Console: queries with meaningful demand, rankings just outside the strongest click zone, and a click-through rate that underperforms comparable positions.

This article gives you a repeatable way to find low hanging fruit keywords using one practical filter: average positions 8–20, impressions above a defined floor, and CTR below your site’s average CTR for that position. It is not a promise that every query will jump to page one. It is a prioritization system for identifying pages where a focused improvement has a credible chance of producing more clicks.

What counts as a low-hanging-fruit keyword?

A low-hanging-fruit keyword is not simply a query ranking on page two. It is a query where Search Console indicates three things at once:

• The page is already relevant: it ranks between positions 8 and 20 on average.
• There is enough opportunity: the query has passed an impressions floor.
• Current SERP performance is weak: its CTR is below the expected rate for its ranking position.

That third condition matters. A query at position 12 with a 1.8% CTR may be normal for your site and search result type. A query at position 12 with a 0.3% CTR deserves inspection, especially if it has 1,500 impressions in 90 days. The first query may need a ranking improvement; the second may have a relevance, title, intent, or SERP-feature problem.

Use a 90-day period as the default reporting window. It is long enough to reduce day-to-day volatility while still being recent enough to guide work. For sites with fewer than 10,000 organic impressions per month, use 180 days. For high-volume publishers or ecommerce sites with seasonal volatility, run both a trailing 90-day view and the same period from the previous year before making changes.

Set the three thresholds before you open Search Console

Set thresholds up front so the analysis does not become a hunt for interesting-looking keywords. The following starting rules work for many established sites:

• Position: 8.0–20.0 average position.
• Impressions floor: at least 100 impressions in 90 days for small and midsize sites; 300–500 for larger sites.
• CTR condition: below the site’s impression-weighted average CTR for the same rounded position.
• Minimum click potential: prioritize queries where a reasonable CTR gain would add at least 5–10 clicks per month.

The 8–20 range is deliberate. Positions 1–3 can produce significant gains, but they are rarely “low effort” because the ranking competition is already intense. Positions 21 and below are often discovery opportunities, not quick wins: the page may lack topical depth, authority, or intent alignment. Positions 8–20 tend to contain pages Google already considers credible enough to test near the first page.

Do not use a universal CTR benchmark such as “position 10 should get 2% CTR.” CTR changes with brand recognition, query wording, ads, shopping results, featured snippets, local packs, video carousels, and whether the search is navigational. Your own Search Console data is the benchmark that matters.

Exact Search Console filter and export steps

Search Console’s standard Search results report does not provide a reliable interface filter for an average-position range and a CTR-versus-position benchmark. You can set the report scope there, then export the query data and apply the actual three-part filter in a spreadsheet.

1. Open the relevant verified property in Google Search Console.
2. In the left navigation, select Performance, then Search results.
3. Click the date filter at the top of the report.
4. Select Custom and choose the most recent 90 complete days. Avoid including the last 2–3 days because Search Console data can be incomplete.
5. Click Search type and select Web. Do not mix Web, Image, Video, and News data in the same analysis.
6. Leave the Query filter blank for the initial pass. If you are auditing a category, use + New, select Page, choose URLs containing, and enter the relevant folder path, such as /services/.
7. Confirm that Total clicks, Total impressions, Average CTR, and Average position are all selected above the chart.
8. Click the Queries tab below the chart.
9. Click Export in the upper-right area of the report and select Google Sheets, Excel, or CSV.

Use a domain property where possible. A URL-prefix property may exclude protocol, subdomain, or directory variants that affect how you interpret keyword and page performance.

Apply the position, impression, and CTR filter in Google Sheets

Assume the exported columns are A: Query, B: Clicks, C: Impressions, D: CTR, and E: Position. Add three columns: F: Position band, G: Expected CTR, and H: Candidate.

1. In F2, enter =ROUND(E2,0). Fill the formula down. This creates an easy comparison group for each average position.
2. In G2, enter =SUMIFS($B:$B,$F:$F,F2)/SUMIFS($C:$C,$F:$F,F2). Fill down. This calculates the impression-weighted CTR for that position band across the exported data.
3. In H2, enter =AND(E2>=8,E2<=20,C2>=100,D2<G2). Fill down.
4. Turn on a filter for the header row and filter column H to TRUE.
5. Sort the remaining rows by impressions from largest to smallest, then review the CTR gap between columns D and G.

For a larger site, replace the 100-impression rule with 300 or 500 impressions. For a narrow category or B2B product with low search volume, keep 100 impressions but require at least 3 clicks and review queries manually. This avoids prioritizing one impression-heavy query that has no commercial or informational value.

How to estimate the upside without pretending it is guaranteed

Use the CTR gap to estimate a conservative opportunity. The formula is:

Estimated additional clicks = impressions × (expected CTR − current CTR)

For example, a query has 2,400 impressions over 90 days, a current CTR of 0.5%, and an expected position-band CTR of 1.4%. The estimated gap is 2,400 × (0.014 − 0.005) = 21.6 additional clicks over 90 days, or roughly 7 clicks per month. That may not justify a major rewrite. If the same gap appears on a query with 30,000 impressions, the estimated opportunity is 270 clicks over 90 days and deserves attention.

Keep estimates conservative. Search Console position is an average, not a fixed rank. A URL can rank at position 6 in one city and 18 in another, or rank differently across devices. CTR can also remain flat after a ranking gain if a shopping module, answer box, or competitor brand absorbs attention.

Diagnose the pattern before choosing the fix

Check query-to-page alignment before editing anything

After finding a candidate query, click it in Search Console, then select the Pages tab. This shows which URL receives impressions and clicks for that query. If one URL clearly dominates, optimize that page. If two or more URLs split impressions, investigate cannibalization before updating titles or adding content.

For each promising query, review four items:

• Intent: Is the search result page mostly guides, product pages, category pages, comparison pages, or local results?
• Page promise: Does the title state what the user will actually get, using the language of the query?
• Above-the-fold relevance: Does the first 100–150 words answer the immediate question or explain the offer clearly?
• Content gap: Do leading results cover a decision factor, use case, price range, specification, process step, or comparison your page omits?

A lightweight optimization usually takes 1–3 hours: revise the title, improve the introduction, add one useful section, update internal links, and confirm that the page still has a clear conversion path. A more substantial page rebuild can take 6–15 hours. If outside writing, design, developer, or subject-matter-expert support is needed, costs can range from roughly $300 to $2,500 per page depending on complexity. Do not spend that amount on a query whose modeled upside is only a handful of low-intent clicks.

What not to do with low hanging fruit keywords

Do not blindly add every query to a title tag. A title stuffed with five near-duplicate phrases can reduce clarity and clicks, even if it looks more “optimized.” Write for the dominant intent first, then use natural terminology where it helps the searcher understand the page.

Do not create a new page for every query between positions 8 and 20. The popular advice to make one page per keyword is wrong when the queries share the same intent. For example, “project management software for small teams,” “small team project management tools,” and “project tool for a small business” may belong on one strong commercial page, not three competing pages.

Do not treat low CTR as proof that the meta description is broken. Google may rewrite descriptions, and some SERPs leave little room for organic clicks. If a query has ads, a local pack, shopping results, and a featured snippet, a below-average CTR may be structural rather than fixable.

Do not judge changes after seven days. Wait at least 28 days after publication for a first read, and use 56–90 days for lower-volume pages. Compare the updated period with an equivalent prior period, while checking whether impressions, average position, and query mix changed.

Make this a monthly operating process

Run this filter once per month, but keep a simple opportunity log. Record the query, landing page, 90-day impressions, current CTR, expected CTR, average position, proposed fix, publication date, and results after 28 and 56 days. Limit each cycle to the 10–20 candidates with the highest realistic click opportunity.

Separate candidates into three queues: snippet fixes for pages already around positions 8–12; content and internal-link improvements for positions 13–20; and no-action observations for SERPs where features or intent make the CTR gap unfixable. That separation prevents a title-tag task from being mistaken for a ranking strategy.

The value of this process is not that it finds magical easy keywords. It creates a disciplined shortlist from data you already own, ties each keyword to a specific URL and diagnosis, and prevents SEO effort from being spent on pages with little measurable upside.

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