Datamart Watcher Use Case 1: Churn Risk (Actionable Insights)

Owned by Jana Volencová
Apr 16, 2024
4 min read

In this example, we will configure a Datamart Watcher to alert us about customers that have a decreasing revenue trend.

The alert will be raised for any customer for whom this year’s performance decreased by at least 20% compared to the last year’s performance. We want the watcher to check this trend monthly.

If such a negative trend is detected, actions are created so that we can analyze the causes and take the recommended, guided or other actions.

Prerequisites

  • Transactional data are available.

  • There are the following fields available in the transactional data:

    • Unique identifier of the customer (Customer ID)

    • Invoice price

    • Pricing date

  • The Actionable Insights capability is available.

  • Customer Insights Dashboards are available.

Alert Definition

If the revenue trend between two defined periods is lower than the defined threshold, the alert is raised on the defined level of the entity.

Time Period

Base period: Last 12 months from the report day.

Comparison period: Prior 12 Months from the Last 12 Months from the report day.

Entity

Customer ID

Measures

Customer Revenue (Invoice Price) for two different periods.

Threshold

-20%

Detection Rule

Base Period Revenue / Comparison Period Revenue - 1 < Threshold

Configuration

Data Scope

In the first step, we will configure the source data.

  1. Define Series 1, let’s call it Base Period.

    ChurnRisk01.png

    1. Select a transactional Datamart as Data Source.

    2. Add Group By: These optional hierarchical dimensions can be used to assign actions to different users in the Action Definition step. We will select Customer Group as Level 1, Customer ID as Level 2 and Customer Name as Level 3. Actions will be created based on this lowest level. Customer name is better than ID for presenting the results to the users.

    3. As a Measure select SUM of Invoice Price. Name the measure Revenue.

    4. Set up a Generic Filter: Pricing Date between 12 months ago and the current day.

       

  2. Add Series 2, let’s call it Comparison Period.

    1. Adjust the Generic Filter so that the Pricing Date is between 12 and 24 months ago.

    2. Other fields can be left as they have been copied.

  3. Add a Join Series, let’s call it Revenue Trend.

     

    1. Set up the Definition. The base series (Base Period) is preselected and non-editable, for the joined series select Comparison Period and as Dimension select in both cases Customer ID. This will be the key connecting data from both series.

       

    2. Create a Measure that will calculate the revenue trend – the difference between this year’s and last year’s Invoice Price sum. Let’s call the measure Revenue Trend.

  4. Click Apply Settings and review the output data in the Data Scope table.

Detection Rules

In the second step, we will set the rules for detecting a negative trend – decreased performance by at least 20% compared to the last year.

  1. In the Series drop-down list select the Revenue Trend join series.

  2. Add the following Rule: Revenue Trend is less than -0.2 (i.e., 20%).

  3. Click Preview Rules to see how many records meet the set rule.

  4. Set up a Schedule: We want the rule to be evaluated once every month, so we will set Period to Month and Interval to 1.

Action Definition

In the third step, define actions that will be generated when the detection rule condition is met.

  1. Click Create Action and add Summary, Description and the Due Date.

  2. Select user(s) in Assign to or Assign to per Dimension.

  3. Add a dashboard.

Summary

In the fourth step, review the complete setup of the Watcher and submit it for approval.