How does ABKE (AB客) run a “de-AI-ification” content test to compare human expert tone vs pure AI copy—using reading time and scroll depth as proof?

Purpose (Awareness → Interest): why test “human expert tone” vs “pure AI copy”?

In the AI-search era, B2B buyers often ask AI systems questions like “Which supplier is reliable?” or “Who can solve this technical issue?”. ABKE (AB客) treats content as evidence-backed knowledge assets that help AI systems understand and trust a company.

This “de-AI-ification” test checks whether adding verifiable knowledge slices (facts, standards, data sources) increases measurable user engagement compared with generic AI-generated copy.

Test design (Evaluation): what exactly is A/B tested?

Metrics & tooling (Evaluation): what is measured and how?

• Avg. engagement time (seconds) — captured via GA4 or Matomo (unit: s).
• Scroll depth (%) — captured via GA4 or Matomo (unit: %).

Result format (Decision): what outputs do buyers and stakeholders get?

ABKE reports outcomes in a format that can be audited and compared across pages and campaigns:

• Median engagement time for Variant A (seconds).
• Median engagement time for Variant B (seconds).
• Delta between medians (seconds): Median(A) − Median(B).
• Scroll depth (%) distribution comparison as a supporting engagement indicator.

Using the median reduces the influence of extreme sessions (e.g., accidental long idle tabs).

Operational notes & boundaries (Purchase → Loyalty): what this test can and cannot prove

In ABKE’s GEO delivery, this test is typically used as a content quality gate before scaling distribution into the global publishing network.