Live Experiment Results ReportSAMPLEReady
Sample report with illustrative demo values. Not a real study, customer or market claim.
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Live Experiment Results Report

Executive summary

A’s concrete time promise outperformed B at every funnel step (SAMPLE data).

The biggest drop-off for both is signup → checkout.

Payment counts are too small to support a pricing conclusion.

01 / 07

Signals statement

We observed behavior, not opinions: clicks, signups, checkout starts and payment attempts from real visitors.

02 / 07

Funnel summary

Events per variant (SAMPLE counts).

A · “Plan in 5 min”B · “Eat better”
Visit
620620
Click
186124
Signup
6231
Checkout
1911
Payment
63
03 / 07

Behavioral read

Visitors respond to a concrete, time-bound promise. Interest collapses when price appears.

04 / 07

Segment differences

SegmentSignup rate ASignup rate B
Mobile9.1%4.6%
Desktop12.4%5.9%
05 / 07

Friction points

  • Price revealed only at checkout.
  • Account creation required before preview.
06 / 07

Next decision

Whether to show price earlier and remove forced signup.

07 / 07

Recommended next experiment

A vs A+visible price, 7 days, same budget.

Next stepRe-run SKPSIS on pricing before scaling spend.

Research behind the method / SKPTST

Current methodological context. These references are not evidence for this historical run.

SKPTST: planned methodology. The engine and paid traffic acquisition are not active.

Plan allocation and sample size before testing

Kohavi, R.; Longbotham, R.; Sommerfield, D.; Henne, R. M. (2009). Controlled experiments on the web: survey and practical guide. Data Mining and Knowledge Discovery, 18, 140–181. Online: 30 July 2008; issue: February 2009.

Research finding
Controlled experiments use randomization, statistical power and variance considerations.

Define stopping rules before inspecting outcomes

Kohavi, R.; Deng, A.; Vermeer, L. (2022). A/B Testing Intuition Busters: Common Misunderstandings in Online Controlled Experiments. Proceedings of ACM SIGKDD 2022, 3168–3177. Conference: 14–18 August 2022.

Research finding
Opportunistic stopping and post-hoc analysis can undermine A/B-test interpretation.

Separate a traffic pilot from proof of advertising impact

Lewis, R. A.; Rao, J. M. (2015). The Unfavorable Economics of Measuring the Returns to Advertising. The Quarterly Journal of Economics, 130(4), 1941–1973. Issue: November 2015. · Blake, T.; Nosko, C.; Tadelis, S. (2015). Consumer Heterogeneity and Paid Search Effectiveness: A Large-Scale Field Experiment. Econometrica, 83(1), 155–174. Issue: January 2015.

Research finding
Advertising returns can be difficult to estimate; the eBay experiment found effects differed across user groups.
The SKP suite
Adversarial research

Research designed to disagree with you.

Logical next step →Explore SKPSIS
Synthetic decision panel

Where ideas meet resistance.

Explore SKPTIK
Observe real behavior

Test behavior, not opinions.

This report