🟡Dynamic Dimension

(Also known as Slowly Changing 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.)

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.

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!

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

  • Name the Segment and apply conditions

Describing the conditions at the Segment name can help you to remember the segment better.

  • 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.

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.

💡Identifying customer segment can help companies improve targeted marketing, pricing strategies or product development, which can grow their business and increase customer loyalty.

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.

Edit the created Dynamic Dimension

You can also edit the Dynamic Dimension from Data Hub, tab Dimensions, Dynamic Dimension:

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