Stop Guessing. Start Testing.

Connect content changes to measurable outcomes. GSC impressions, GA4 engagement, statistical significance, automatic verdicts.

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The Problem: Content Changes Without Evidence

"Does Living Content actually improve engagement?" "Did that rewrite help rankings?" Without experiments, these are just opinions. You make changes, hope they work, and never close the loop.

More traffic?

Better engagement?

Higher rankings?

no data, just speculation

The Fix: Hypothesis → Data → Verdict

Set a hypothesis. Link it to a blog post. LiquiChart collects weekly snapshots from GSC and GA4, calculates statistical significance, and delivers a verdict: confirmed, refuted, inconclusive, or partially confirmed.

Hypothesis

→

8 Weeks

→

Confirmed ✓

Statistical significance: 94%

See It in Action

A completed experiment with real statistical analysis, confirmed with high confidence.

app.liquichart.com/experiments/living-content-engagement

Does Living Content improve time on page?

Confirmed

Hypothesis: Posts with Living Content blocks will show 15%+ improvement in average session duration compared to static posts.

Statistical Analysis

high confidence

Metric	Before	After	Change	Effect	p-value	Sig.
Clicks(gsc)	661	816	+23.4%	1.12 (large)	0.018	✓
Impressions(gsc)	11,125	12,300	+10.6%	0.68 (medium)	0.042	✓
CTR(gsc)	5.90%	6.60%	+11.9%	0.72 (medium)	0.038	✓
Avg Position(gsc)	7.8	6.5	+15.5%	0.85 (large)	0.024	✓
Pageviews(ga4)	1,970	2,450	+24.4%	1.05 (large)	0.022	✓
Sessions(ga4)	1,518	1,900	+25.2%	1.10 (large)	0.019	✓
Engagement Rate(ga4)	61.0%	69.0%	+13.1%	0.78 (medium)	0.035	✓
Avg Duration(ga4)	155s	185s	+19.4%	0.90 (large)	0.028	✓

Verdict: Confirmed

6 of 8 tracked metrics show medium or large positive effects. Primary metric (clicks) p-value: 0.018. Confidence: high.

Caveats

No control group. Observed changes may be due to external factors (seasonality, algorithm updates)

Clicks

+5%

890

Impressions

+2%

12,800

CTR

+3%

7.00%

Avg Position

+5%

6.1

Pageviews

+5%

2,650

Sessions

+5%

2,050

Engagement Rate

+3%

72.0%

Avg Duration

+4%

198s

Search Performance

Traffic & Engagement

How It Works

Set a hypothesis

Write what you expect to happen. Link it to a blog post. Choose GSC and GA4 metrics to track.

System collects data

Weekly snapshots from GSC and GA4. No manual exports. No spreadsheets.

Statistical significance

The system calculates whether results are meaningful before delivering a verdict.

Verdict becomes recommendation

Confirmed findings auto-generate Living Content recommendations. Apply what worked to similar posts.

Capabilities

GSC Integration

Track impressions, clicks, CTR, and average position for specific pages or queries over the experiment period.

GA4 Integration

Measure sessions, bounce rate, time on page, and conversions. Compare before and after content changes.

Weekly Snapshots

Automatic data collection during the experiment run. No manual export needed.

Statistical Significance

The system calculates whether results are statistically significant before delivering a verdict.

Four Verdict Types

Confirmed, refuted, inconclusive, or partially confirmed. Each verdict includes the evidence that supports it.

Verdict → Recommendation

Confirmed findings automatically generate Living Content recommendations for the linked post and similar posts.

Part of the Evidence Chain

Experiments test claims, generate verdicts, and feed recommendations back into content.

Turn Content Strategy Into Evidence

Test hypotheses with real search and engagement data. Automatic verdicts. Automatic recommendations.

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