Figures & Functions
Figures and functions are the building blocks of your analysis in Ipiphany. They allow you to create custom metrics and calculations to gain deeper insights from your data.
- Average Function
Explanation of the 'Average' function in Ipiphany and how it is used to calculate the mean of numerical data.
- Contribution Function
Explanation of the Contribution function in Ipiphany and how it is used to compare groups with different sample sizes.
- Detractor, Passive, Promoter Functions
Explanation of the Detractor, Passive, and Promoter functions in Ipiphany and how they are used to calculate NPS type attributes.
- Difference Function
Explanation of the Difference function in Ipiphany and how it is used to calculate the difference between a specific pattern's metric and the overall value.
- Frequency
Explanation of the 'Frequency' function in Ipiphany and how it is used to analyze data patterns.
- Impact Function
Explanation of the Impact function in Ipiphany and how it is used to measure the contribution of patterns to overall data selection measures.
- Lift Function
Explanation of the Lift function in Ipiphany and how it is used to measure the over-indexing of patterns in your data.
- Net Function
Explanation of the 'Net' function in Ipiphany and how it is used to measure customer experience scores.
- NPS Function
Explanation of the 'NPS' function in Ipiphany and how it is used to measure customer loyalty.
- Opinion Function
Explanation of the Opinion function in Ipiphany and how it is used to measure positive and negative sentiment towards a target topic.
- Relevance Function
Explanation of the Relevance function in Ipiphany and how it is used to measure the relevance of sub-patterns in relation to patterns or overall data.
- Subset% Function
Explanation of the 'Subset%' function in Ipiphany and how it is used to calculate the percentage of selected attribute values within an attribute.
- Sum and Sum % Functions
Explanation of the Sum and Sum% functions in Ipiphany and how they are used to calculate the total value of an attribute across all records.