SEO & PPC Strategy — Keyword Research Workflow — 2026-04-05
Overview
During a weekly call between Mark Hope and Gilbert Barrongo, the team identified a core SEO problem for Citrus America: high-intent commercial keywords are ranking on page one of Google but in positions 8–11, producing high impressions and near-zero click-through rate. The session established a repeatable keyword research workflow (GSC + Ahrefs → ChatGPT) and produced a concrete set of SEO and PPC recommendations to address the ranking gap.
Primary objective: Move commercial intent keywords from positions 8–11 into the top 5, which is the threshold where CTR becomes meaningful.
The Core Problem
Citrus America ranks on page one for high-value commercial queries such as "commercial citrus juicer" — but at positions 9–11. At those positions:
- Impressions are high (the site appears in results)
- CTR is very low (users rarely scroll past position 5)
- Revenue impact is minimal despite the organic visibility
"You end up with high impressions because you're on the front page, but low click-through rate because you're low on the front page." — Mark Hope
The fix is not to find new keywords. It is to push existing high-intent rankings up the page through content, technical SEO, and internal linking.
Keyword Research Workflow
A three-step workflow was established for accounts with existing history. This is now the standard approach for Citrus America keyword research.
Step 1 — Google Search Console: Export Queries
- Go to GSC → Performance → Search Results
- Set date range (3 months recommended)
- Scroll to the Queries table (what users actually searched to land on the site)
- Export as Excel (CSV can cause ChatGPT parsing issues)
Step 2 — Ahrefs: Export Organic Keywords
- Open the Citrus America project in Ahrefs
- Navigate to Organic Keywords
- Filter to positions 1–50 (uncheck 51+ buckets to focus on actionable rankings)
- Export as UTF-8 CSV or Excel
Note: Queries (GSC) = what people searched. Keywords (Ahrefs) = what we rank for. They overlap but are not identical. Both perspectives are needed.
Step 3 — ChatGPT: Combined Analysis & Recommendations
Upload both files to ChatGPT and prompt in sequence:
- "Evaluate these queries for citrusamerica.com" → upload GSC file
- "These are the organic keywords we rank for now" → upload Ahrefs file
- "Consider the query report and the keywords report, and give me a combined summary and recommendations"
ChatGPT will surface:
- Brand vs. commercial keyword performance split
- Position gaps for high-intent terms
- CTR weaknesses
- Content and technical recommendations
Follow up with: "Give me additional core commercial keywords we should be targeting that are not in this list."
Findings for Citrus America (This Session)
| Category | Finding |
|---|---|
| Brand queries | Ranking #1, ~50% CTR — healthy |
| Commercial intent keywords | Positions 8–11, very low CTR — primary problem |
| Informational/recipe traffic | Ranking #1 for "margarita recipe" — intentional (bar/tavern audience), not a concern |
| Overall keyword count | 252 organic keywords in Ahrefs, growing |
Key insight from ChatGPT combined analysis:
"You rank for the right commercial topics, but too low. Get commercial citrus juicer from position 11 to position 5 or better."
Recommendations
SEO Tasks (→ Melissa / Yash / Gavin)
| Task | Owner | Notes |
|---|---|---|
| Build or expand core commercial landing pages | Yash | Category pages are weak; this is the highest-leverage fix |
| Rework title tags & meta descriptions | Yash | Target high-intent commercial terms; improve CTR directly |
| Internal linking overhaul | Yash | Pass authority to commercial pages from supporting content |
| Create high-intent supporting blog content | Gavin | Target commercial keywords identified in ChatGPT output |
Example content types suggested by ChatGPT:
- Commercial juicer comparison guides
- Category-specific landing pages (e.g., hotel orange juice machines, bar citrus juicers)
- Supporting blog posts around mid-intent commercial queries
PPC Tasks (→ Gilbert)
- Create Single Keyword Ad Groups (SKAGs) for each high-intent commercial keyword identified in the ChatGPT output
- Use exact, phrase, and broad match modifier within each SKAG
- Monitor the Search Query Report (SQR) after launch to identify adjacent terms
- Do not group multiple commercial terms into one ad group — split them individually
Example SKAG targets from this session:
- commercial citrus juicer
- commercial orange juicer machine
- hotel orange juice machine
- supermarket orange juicer machine
- self-service juice machine
Competitor Analysis via SpyFu
SpyFu was introduced as a complementary research tool. Two use cases were demonstrated:
SEO Combat (Organic)
- Go to SEO Research → Combat
- Add CitrusAmerica.com + 2 competitors
- Read the Venn diagram:
- Overlap zone = shared keywords (less interesting)
- Competitor-exclusive zone = keywords they have that we don't → highest value for gap analysis
- Rotate through competitor pairs to build a broad picture
PPC Overview (Paid)
- Go to PPC → PPC Overview, enter a competitor domain
- View their Google Ads History to see actual ad copy
- Click Keywords to see what terms they were targeting
- Useful for ad copy inspiration and keyword gap identification
SpyFu is most useful for larger advertisers. If a competitor has low ad spend, the database may not have enough data.
Action Items
- [ ] Gilbert — Create Citrus America SKAGs for all high-intent commercial keywords from ChatGPT output; monitor SQR weekly
- [ ] Gilbert — Call Melissa to walk through SEO/PPC recommendations from this session
- [ ] Gilbert — Share this Fathom recording with Melissa
- [ ] Melissa — Assign Yash: title tags, meta descriptions, internal linking overhaul
- [ ] Melissa — Assign Gavin: blog content targeting commercial intent keywords
- [ ] Yash/Gavin — Build or expand core commercial landing pages for Citrus America
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