What is an Interpretation?

3 mins read - Created on Dec 17, 2025

An Interpretation in Kimola is an AI-powered analysis layer that generates advanced, human-readable insights from your dataset. Interpretations go beyond basic metrics by transforming analyzed data into structured explanations such as summaries, patterns, motivations, and actionable findings.

Getting Ready

Interpretations are powered by Kimola’s GPT integration and are designed to help you quickly understand why something is happening in your data — not just what is happening.

What Interpretations Provide

Interpretations generate qualitative insights based on the analyzed dataset and present them in clear, natural language. These outputs are designed to help you understand why certain patterns exist in your data, not just what the results are.

The most commonly used interpretation types include:

Executive Summary – A concise overview highlighting the key positive and negative findings in the dataset
Personas – Buyer or user personas generated from customer feedback
Usage Motivations – The main reasons customers choose or use the product or service
Pain Points – The most common problems, frustrations, or unmet needs expressed by customers
Customer Journey – Actionable stages of the customer experience based on feedback patterns

In addition to these core interpretations, Kimola also offers more specialized interpretation outputs, such as feature requests, highlights, FAQs, product or app descriptions, marketing recommendations, and roadmap-related insights. These advanced options allow you to tailor reports for specific teams like product, marketing, or sales, depending on your needs.

All interpretation outputs are generated in natural language and are especially useful when sharing reports with non-technical stakeholders or using insights directly in presentations and decision-making processes.

When Interpretations Are Used

Interpretations are optional and can be added either during report creation or after a report is created. You may choose to use them when:

You want ready-to-use summaries in addition to reviewing sentiment and themes
You need insight narratives for presentations or executive reporting
You want to quickly identify key themes without manual analysis
You are working with large or complex datasets

If interpretations are not needed, reports can still be created using standard analysis outputs such as sentiment, topics, and trends.

How Interpretations Work in Kimola

Interpretations work on already analyzed data. The process follows these steps:

A dataset is prepared (from a feed, links, custom dataset, or integration).
Kimola analyzes the data using standard analytics (sentiment, themes, trends, etc.).
Selected interpretations use AI to generate written insights based on those results.

Interpretations do not change the underlying data. They only generate additional insight layers on top of existing analysis.

Note

To learn when interpretations can be added to a report and how to generate them step by step, see Add Interpretations to a Report.

Why Interpretations Matter

Interpretations help bridge the gap between data and decisions by:

Reducing manual analysis time
Turning complex results into clear narratives
Making insights accessible to wider teams
Supporting faster, data-driven actions

They are especially valuable when insights need to be communicated clearly, quickly, and consistently.

Example

If you analyze hundreds of customer reviews, sentiment charts may show what customers feel. An interpretation explains why — summarizing common complaints, expectations, and motivations in a format ready to share with product or leadership teams.