# 🟡Dynamic Dimension
How many times have you asked the following questions:
* How many customers *churned* last month?
* How much revenue did our “*priority customers*” contribute last quarter?
* Or even: let’s set a goal to reduce churn rate by 20% next year.
**The tricky thing with those questions is that such properties vary over time for a given object**. A customer might be “priority” last year, but not this year - depending on their yearly spend level. To do this, your data team has to code and maintain a complex data query in their system, and they usually are fixed for use with a single metric, not to mention the need for tweaking the definitions around. Now you can do that on Presight with a simple point-and-click interface.
(Note that **this is different from a regular dimension** in that Dynamic Dimensions deal with data that tend to change occasionally or at irregular intervals, like Customer Spendings, Products Sold. In contrast, non-changing dimensions - or regular dimensions, such as Customer Country, Product Color, are usually fixed over time and can be defined using our existing [Dimension Editor](/presight-v1.0/model/segments-and-custom-segments/create-a-new-dimension.md).)
## What makes a Dynamic Dimension
A Dynamic Dimension is consisted of 3 elements:
1\. The **target dimension** to be segmented:
* is it your customers (Active vs Churned), to run different campaigns
* or your sales personnels (Top Employees vs Normal Employees), to design different commission levels, for example.
2\. The **changing property** (i.e. a Metric) being used to segment the target dimension, for example:
* segment customers by their total spending in the month
* differentiate your salespersons by their total revenue contribution in prior year
3\. Lastly, the **time window** used in your segmentation definition
* A calendar period: a customer is “Churned” if they didn’t spend any money for a full calendar year, a product is “Hot” if it sold more than 1,000 units in a quarter.
* A running period: a customer is “Churned” if they haven't come back for 3 consecutive months.
{% hint style="info" %}
Currently Presight doesn't support a running period time window in defining a Dynamic Dimension yet. For now, most usecases can be approximated using the calendar period method above without changing the effectiveness of applying the SCD to your operations.
Dynamic Dimension also cannot be created from formulated metrics.
These will be available in a future release!
{% endhint %}
**Once defined, Dynamic Dimensions can be used by many other metrics**, just like any other dimension defined the traditional way. For example:
* Show percentage of churned users over time. What products were viewed by churned users but weren’t purchased?
* Show revenue contribution of “Best Selling” products over time. Show average margin of these best performing products versus the rest, should we invest more in our product R\&D?
* Are our sales teams performing well? Percentage of sales persons exceeding KPIs over time and see the projection.
* Make future growth plans for each of these questions.
Experimenting with different segmentation, and allocating your operations effectively to best serve each segment is crucial to success in many companies. With Presight, non-tech users can create a new Dynamic dimension in a few clicks. Compared to the traditional way of waiting for a few weeks for the tech team to code this into the data pipeline, Presight is setting a new standard in bringing data closer to business outcomes.
## How to use
* Choose a metric, find a dimension that you want to segment and click on the **Segment icon** 
Segmenting Icon
* Name the Segment and apply conditions
Classifying Customers by their spending values in a month
{% hint style="info" %}
Describing the conditions at the Segment name can help you to remember the segment better.
{% endhint %}
* Then, Click **`Apply`**
* The dimension will appear in the drop-down list for you to breakdown the metric
The newly created segmenting dimension can also be used to breakdown at other related metrics.
{% hint style="success" %}
The Segmenting Dimension helps to show that: Large Customer accounted for 808k sales in June (which is almost 48% of total sales), and there are 366 customers in that group (which is 7% of total customer number). \
Then, company can deeply dive in more details, such as: products sold to this group , their location, their age-bin...., and offer suitable marketing or pricing programs for them to increase sales and customer loyalty.
đź’ˇ**Identifying customer segment can help companies improve targeted marketing, pricing strategies or product development, which can grow their business and increase customer loyalty.**
{% endhint %}
{% hint style="info" %}
The same Dynamic Dimension can be used by other metrics at different time granularity. For example, Customer Status defined with Quarterly Spending can be used in Monthly, Quarterly, Yearly breakdowns of related metrics.
{% endhint %}
Yearly Sales broken-down by Customer Monthly Spendings
### Edit the created Dynamic Dimension
You can find the Edit Icon  next to the Dynamic Dimension name to edit the dimension: dimension name, segment name and conditions.
Edit a Dynamic Dimension
You can also edit the Dynamic Dimension from **Data Hub**, tab **Dimensions**, **Dynamic Dimension**:
Edit a Dynamic Dimension
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