> For the complete documentation index, see [llms.txt](https://presight.gitbook.io/presight-v1.0/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://presight.gitbook.io/presight-v1.0/presight-iq-beta/auto-insights-beta/insight-type-1-based-on-contribution.md).

# Insight Type 1 - Based on Contribution

The first type of insight PresightIQ suggests to you is the direct sub-segment of the metric where **there was the biggest gap** between its expected contribution to the metric value and its actual contribution.

For example: 

> <mark style="color:green;">**Sales of Region Europe**</mark> - based on historical trends, seasonality and levels - was expected to contribute <mark style="color:blue;">**50%**</mark> to **Total Sales** for **March 2023**. But when the numbers came back, it actually contributed only <mark style="color:red;">**30%**</mark>, and thus we have a gap of **20%** (50% - 30%).&#x20;
>
> Comparing this 20% with results of similar calculations for other segments, we see that 20% is the biggest gap. Presight will then recommend <mark style="color:green;">**Region Europe**</mark> to you for this first type of insight.

{% hint style="warning" %}
To make sure that all of our recommendations are meaningful to your diagnosis of the anomaly, all segments need to pass a certain threshold of significance in value. So when we say "biggest", think biggest of all the significant enough segments.
{% endhint %}