Analysis Copilot
Analysis Copilot is an AI-powered assistant designed to help you analyze campaign data within AB Tasty reports.
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Analysis Copilot is an AI-powered assistant designed to help you analyze campaign data within AB Tasty reports.
Last updated
Was this helpful?
Instead of manually sifting through data tables and charts, you can simply type your questions, and the AI will process the underlying metrics, statistical significance, and objective performance to deliver concise and relevant answers.
Ask Copilot leverages CRO best practices and statistical data to provide clear, data-backed answers and recommendations.
The assistant can answer with text, table, and/or chart based on your needs.
Use case examples:
Explain the winning variation
Challenge my hypothesis
Give me CRO best practices based on my campaign results
To get the most accurate and helpful responses from the AI, consider the following:
Wait for readiness : if you are willing to make a decision, wait for the readiness to be ok at least on primary goals.
Be Specific: The more precise your question, the better the AI can understand your intent.
Good: "Which variation performed best for the 'Conversion Rate' objective?"
Avoid: "What about the conversion rate?"
Reference Objectives and Metrics: Clearly state the objectives and metrics you are interested in.
"What is the statistical significance for the 'Click-Through Rate' of Variation B versus Control?"
"Show me the difference in average revenue per user between all variations."
Ask for Comparisons: The AI is excellent at comparing performance between variations.
"Compare the bounce rate of Variation A and Variation B."
"Which variation had the highest increase in sign-ups compared to the control?"
Inquire About Statistical Significance:
"Is the difference in [Metric] between [Variation X] and [Variation Y] statistically significant?"
"What is the p-value for the 'Add to Cart' objective?"
Ask for Summaries:
"Summarize the overall performance of this A/B test."
"What are the key takeaways from this report?"
Identify Top/Worst Performers:
"Which variation had the highest [Metric]?"
"Which objective performed the worst for Variation C?"
Troubleshooting & Clarification:
"Can you explain the 'Confidence Interval' for the 'Purchase Rate'?"
While powerful, the Analysis Copilot has some limitations:
It does not work in Frequentist mode
Relies on Available Data: The AI can only analyze the data presented in your report. It cannot infer information not present in the underlying metrics and statistics.
Statistical Interpretation: The AI provides statistical interpretations, but it's crucial for you, to apply domain expertise and strategic context to those interpretations.
Complex Scenarios: For highly complex or multi-variate statistical modeling, you may still need to consult with a data analyst.
No Predictive Capabilities (currently): The AI focuses on analyzing past performance; it does not predict future outcomes or design new experiments (unless specifically integrated in a future release).