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Customer Churn Prediction
Rashan avatar
Written by Rashan
Updated over a year ago

Churn prediction is essentially predicting which clients are most likely to cancel a subscription. Mortar portal has the potential to predict accurately which customer will churn and with these insights, you can gain a better understanding of future expected revenue and analyse which areas of operations lead to the churn.

The Mortar portal gives you the flexibility to choose a preferred time frame to get targeted results.

You can select the number of customer purchases based on your company's requirements to obtain a personalised churn rate. The higher the purchase count, the better the predicted churn rate.

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The text area will highlight the number of customers from your database who are expected to churn in the next 30 days.

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The table on the right will reflect the details of customers who are most likely to churn with their status and expected churn date. The detailed information about customers will aid in planning marketing strategies that could result in retaining these customers or preventing them from being lapsed.

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It allows you to export the data from the table to your personal systems with a simple Export button.

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The middle text box will reflect the revenue that could be generated by retaining the customers who are about to churn, based on their average spent and expected purchase interval.

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The last text box will provide you with some tips on retaining these customers who are at risk of churn.

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Historical Customer Breakdown:

The chart on the bottom left will describe the customer's status briefly and help you take necessary marketing actions to retain them. The breakdown of the customers are as follows:

Hard churned: hard to retain using marketing strategies or promotions

Active: customers who make active purchases

Soft churn: can retain them using marketing strategies or promotions

Lapsed: no more your customer and need to treat them as a new customer now

Non-spenders: people who haven’t spent anything

When you hover over the pie chart for the customer breakdown, it displays the number of customers and their status.

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Historical Churn Records:

The graph on the bottom right shows the number of customers who churn in a week. It compares data for five weeks to provide a better understanding of churn rate and help to plan retention marketing strategies.

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