A/B Test Decision Advisor – Excel XLSX

BENEFITS OF THIS DOWNLOADABLE EXCEL DOCUMENT

1. Helps turn A/B test results into structured, defensible business recommendations.
2. Incorporates statistical evidence, business relevance, guardrails, segmentation, and decision risk into the judgment.
3. Provides a suggested decision posture, supporting rationale, and executive-ready wording to communicate the recommendation.

DECISION MAKING EXCEL DESCRIPTION

A/B Test Decision Advisor is an Excel template (XLSX) available for immediate download upon purchase.

<Analyzing an A/B test is only part of the job. The harder question is what to do with the result.>
A statistically significant result does not automatically justify rollout. A promising result may still carry too much uncertainty or risk. A strong result may come with an important guardrail concern. A subgroup may appear to respond differently, but the finding may not be sufficiently validated. And even a statistically credible improvement may simply be too small to matter to the business.

<A/B Test Decision Advisor helps bridge the gap between experimental analysis and business judgment.>
Instead of looking at statistical significance alone, the workbook brings together multiple factors that matter when making an experiment-based business decision: statistical evidence, business relevance, KPI alignment, guardrails, subgroup findings, decision risk and reversibility, implementation effort, and the value of collecting additional evidence.

Users enter their experiment results and relevant business context. The Decision Advisor organizes that information into a structured assessment and provides a suggested decision posture, an explanation of why that posture is appropriate, and executive-ready wording to help communicate the recommendation.

Suggested postures may include scaling through a controlled rollout, continuing to learn through a pilot, collecting more evidence, investigating a guardrail concern before rollout, validating a subgroup before targeting, or not rolling out when the observed benefit does not meet the business threshold.

The workbook supports both binary/proportion outcomes and continuous outcomes. It also includes four worked case studies that demonstrate how the framework approaches common experimentation situations:
• An encouraging but statistically inconclusive result
• A statistically favorable result with material guardrail harm
• A promising post-hoc subgroup finding requiring validation
• A statistically credible improvement that falls below the minimum business-meaningful threshold

The workbook is designed for analysts, data scientists, experimentation practitioners, product and marketing professionals, and business decision-makers who want a more structured way to translate experimental evidence into action.

The goal is not to automate judgment. It is to help make judgment more structured, transparent, and defensible.

A/B Test Decision Advisor is an analytical and decision-support tool. Users remain responsible for reviewing the underlying data, assumptions, statistical appropriateness, business context, risks, policies, and applicable requirements before making or implementing a decision.

Source: Best Practices in Decision Making, Data Analytics Excel: A/B Test Decision Advisor Excel (XLSX) Spreadsheet, Rainbonova