---
title: "Forum analysis and product ideas | cm-opti team experience"
url: https://cm-opti.com/business-cases/forum-analysis-product-development
description: "Clustering and analysis of posts from special-interest forums. A map of user expectations for a new customer group and a higher-margin product."
language: en
---

# Analyzing forum content: a new customer group and product development

**Product development and customer acquisition**

Michael Jan Rogocki delivered this project before founding cm-opti. We use the same method in client projects today.

## Industry and type of organization

A company developing its own product and looking for new audiences for it. Knowledge of what users really want was scattered across forums and topic groups, where people describe their problems in their own words.

## Business problem

Decisions about what to add to the product and who to market it to were made on the basis of single signals: a louder customer, an internal hunch, whatever the competition happened to be doing. Meanwhile users on forums describe directly what bothers them and what they would be willing to pay for.

This material, however, is unstructured. It is free text, in varying styles, with no categories at all. Reading and sorting that many posts by hand is not feasible, so the knowledge went unused.

## Approach and scope of work

The material was content that users write themselves on topic forums, processed with natural language processing (NLP) methods. Rather than reading post by post, the analysis first turned the statements into vector representations (embeddings) that capture their meaning and then grouped them by clustering: the algorithm arranges similar statements into clusters on its own, so recurring themes and needs emerge from the raw mass of posts.

Each cluster is one group of expectations: a concrete problem, the way people talk about it, and the language they use. On this map you see two things at once: audiences the product had not yet spoken to, and features missing from the current product.

The text data was processed in a secured environment.

## Business impact

tens of thousands

statements analyzed

content from forums and topic groups

two directions

a new customer group and new features

entering a new segment and extending the current product

The company received user expectations described in their own words and grouped into clear themes. Some clusters pointed to a segment the product had not previously reached, which opens up a new customer group. Some showed concrete gaps in the current product, in effect a ready-made list of features to add.

Extending the product with features for which there is real demand raises its value for the customer and has a positive effect on margin, because the company builds what people are actually looking for.

## Scale of the implementation

The analysis covered tens of thousands of statements from forums and topic groups related to the product, so the scale was large enough for the patterns to be reliable. The more statements in the source, the more reliable the clusters, because a single voice is an anecdote, while a recurring pattern is a signal.

If your users describe their needs online and you make product decisions by gut feel, [describe your case to us](https://cm-opti.com/en_index#kontakt). We will check what can be learned from what people already write about you.

## Related articles in the cm-opti knowledge base

- [What is data analysis and BI](https://cm-opti.com/knowledge-base/what-is-data-analysis-bi)
- [What are OCR and NLP](https://cm-opti.com/knowledge-base/what-is-ocr-nlp)
- [What is artificial intelligence](https://cm-opti.com/knowledge-base/what-is-artificial-intelligence)

Service area: [Machine learning and forecasting](https://cm-opti.com/en_solutions#dane) (data analysis and NLP in product development).

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