EXP-008: The 30-Day SEO Indexing Window — Which Evergreen Articles Finally Got Traffic?

Experiment ID: EXP-008 Status: COMPLETE Date: 2026-05-07 Data Window: 2026-04-03 to 2026-05-07 (34 days, full site lifetime) Owner: Effloow Experiment Lab Predecessor: EXP-007 (Publication Timing × Topic Heat, 2026-04-23)

1. Hypothesis

EXP-007 prediction (recorded 2026-04-23):

"The 0% hit rate for Apr 5–7 articles may partially be a timing effect. These articles should be re-examined at the 30-day mark (May 5–7) to verify whether SEO indexing kicks in for evergreen content."

EXP-008 hypothesis: At least some April 5–7 evergreen articles will accumulate measurable organic traffic by their 30-day mark (May 5–7), validating that SEO indexing provides a delayed traffic ramp even for content that had zero visibility at day 20.

Null hypothesis: The April 5–7 articles will still have zero measurable GA4 traffic at day 30, confirming that topic heat — not time — is the primary traffic driver at Effloow's current site age.

2. Data Sources

3. The April 5–7 Cohort: Baseline Recap

EXP-007 identified 9 articles from the April 5–7 publishing window. All were classified as "evergreen" (no hot-release topic timing) and had zero measurable GA4 traffic at the 20-day mark (April 23).

4. The May 7 GA4 Snapshot: Full Top Pages

Current data/metrics.json top_pages (2026-05-07):

Total article views in top_pages: 430 views across 6 articles (out of 138 published)

5. April 5–7 Cohort at Day 30: Results

Verdict: Hypothesis partially confirmed. The 30-day window did unlock organic traffic — but for only 1 of 9 articles.

6. Why Framer Review Broke Through

The framer-review article is distinguished from the rest of the cohort by its keyword search volume profile. Its frontmatter contains:

keywords:
  - framer review
  - framer review 2026
  - framer website builder
  - framer vs webflow
  - framer pricing
  - framer ai website builder
  - is framer good for seo
  - best ai website builder 2026

Compared to the zero-traffic articles:

The differentiator is not word count, content quality, or publication date. All 9 articles are from the same publish window and similar quality. The sole distinguishing factor is that Framer has massive organic search demand from developers and designers actively evaluating website builders — a much larger addressable audience than any individual AI dev tool.

7. The New Entrant: mcp-ecosystem-growth (April 12)

A notable finding: mcp-ecosystem-growth-100-million-installs-2026 now has 70 views — making it the second-highest article and the new breakout article in the May snapshot. It was not visible in any previous experiment's top_pages.

This is remarkable. A mid-April hot-topic article with only 3,074 words outperforms all April 5-7 articles (which average 4,389 words each) by a wide margin. This reinforces EXP-007's finding that topic heat at publication dominates word count in the traffic prediction model.

8. The Traffic Source Shift Finding

Comparing the EXP-007 snapshot (Apr 23) vs the EXP-008 snapshot (May 7) reveals a key structural change: codex-vs-claude-code-comparison-2026 dropped out of top_pages.

Working interpretation: data/metrics.json top_pages reflects a monthly rolling window, not cumulative all-time data. Articles that were driven by social amplification (cross-posts, founder shares) in April have cycled out as that referral traffic decayed. Meanwhile, newer organic search traffic is arriving from articles with high-intent keywords, creating a composition shift in the monthly top_pages.

This finding has important implications for measuring article ROI.

9. Updated Traffic Performance Table: All Time

Combining all experiments, the lifetime traffic picture for the top articles is:

Traffic concentration: 6 articles out of 138 published (4.3%) appear in monthly top_pages. The remaining 132 articles (95.7%) have zero measurable monthly traffic.

10. Findings Summary

Finding 1: 30-Day Window DOES Unlock Organic Traffic — for Keyword-Rich Evergreen Content

Hypothesis partially confirmed. The April 5-7 cohort achieved a 0% → 11% hit rate over 30 days. But the breakthrough required a specific condition: the article must target keywords with high organic search volume (i.e., people actively searching for that specific tool). framer review is a top-of-funnel query for a widely-used product. Most AI developer tool reviews do not meet this bar.

Implication: Not all evergreen content accumulates organic traffic equally. The 30-day window only activates for articles whose keywords have real search volume.

Finding 2: Hot-Topic Articles Have a Second Traffic Phase

mcp-ecosystem-growth (April 12) entered the top_pages at day 25 with 70 views. This suggests hot-topic articles have two traffic phases:

1. Phase 1 (Days 0–7): Social amplification spike from cross-posts and shares
2. Phase 2 (Days 21–30+): Organic search traffic from people discovering the article via search

Hot-topic articles written around trending developer ecosystem events (MCP reaching 100M installs) may have both a higher social ceiling AND a sustained organic floor.

Finding 3: Social Amplification Traffic Has ~30-Day Half-Life

codex-vs-claude-code and terminal-ai-coding-agents were the #4 and #5 article traffic drivers at the April 23 snapshot. Both have since dropped out of the monthly top_pages entirely. This suggests that cross-post and founder-share traffic decays to near-zero within approximately 30 days unless organic search picks up.

Implication: Cross-posting is a short-term spike mechanism, not a sustained traffic source. Articles that don't attract organic search traffic within 30 days of publication will effectively go dark.

Finding 4: Word Count Does Not Predict 30-Day Organic Breakthrough

The 9 articles in the April 5-7 cohort average 4,389 words each. framer-review (4,776 words) broke through, but so did the much shorter mcp-ecosystem-growth (3,074 words, Apr 12). The 5,781-word surfer-seo-review remains at zero. Word count is a weaker predictor than previously hypothesized.

11. Revised Traffic Prediction Model

Building on EXP-006 and EXP-007, the updated traffic model is:

Monthly Traffic = f(Topic Heat at Publication, Keyword Search Volume, Social Amplification)

Where:
  - Topic Heat:       Hot Release → Phase 1 spike + Phase 2 organic floor
                      High-Volume Keyword → Phase 2 organic floor only (no Phase 1)
                      Low-Volume Evergreen → ~zero (verified at 30-day mark)
  - Keyword Volume:   Must be verifiably high-intent to trigger 30-day organic emergence
  - Social Amplif.:   Provides Phase 1 spike only; decays within 30 days
  - Word Count:       Not a significant standalone predictor (r ≈ unclear, sample too small)

12. Recommendations

Immediate (Priority 1)

Content Strategy (Priority 2)

Metrics (Priority 3)

13. Next Experiment: EXP-009

Proposed experiment: Keyword search volume scoring vs actual traffic performance.

Method: Score all 138 articles with estimated keyword search volume (using public tools or GSC impression data), then correlate with monthly GA4 views. Identify the search volume threshold above which articles reliably appear in monthly top_pages.

Expected result: Articles targeting keywords with ≥1,000 monthly searches will have 3× or higher appearance rate in monthly top_pages compared to articles targeting keywords with <200 monthly searches.

Timing: Run when Google Search Console data is available, or schedule for 2026-06-07 (60-day site mark).

Appendix: April 5–7 Articles — Keyword Profile vs Outcome

Note: Monthly search estimates are qualitative (High/Medium/Low) based on tool brand size and query type. A dedicated keyword tool analysis is planned for EXP-009.

Data collected: 2026-05-07 | Articles analyzed: 138 total, 9 in focus cohort | GA4 data window: monthly rolling snapshot Predecessor: EXP-007 (2026-04-23) | Next: EXP-009 (keyword volume vs traffic correlation)