Questions tagged [churn]

Churn rate is used in business as a measure of the process of losing customers: see http://en.wikipedia.org/wiki/Churn_rate.

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Approach(es) to discover “conditional churn propensities”?

I'm aware of a variety of approaches to discovering “stand-alone” churn probabilities. But I haven't been able to find by searching any info on “conditional” churn probabilities. Use case: I'm a ...
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38 views

Carrying Out Interventions Based on ML “Feature Importances”

Recently, I have been studying causal inference and have come to a bit of a crossroads with respect to making decisions based on the analysis of data (especially in a business/industry setting). ...
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Am I using risk ratio appropriately?

I am doing a retrospective analysis of customers who renewed or terminated their subscription. I have about 40,000 renewals and 1,000 churn. Among my churn group, 25% (N = 250) contacted customer ...
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The most important matrices for evaluating a predictive model for customer churn

My questions is as above. What are the most important matrices (f1, precision, recall...etc) that I need to prioritize my work to improve for evaluating how good a model predict customer churn and the ...
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48 views

How to label Churn/Not Churn and perform Survival Analysis on Transactional Data without Subscription

I have longitudinal transaction data of a retail store where each row is a transaction done by an individual. I would like to perform a survival analysis to analyse how long a customer will transact ...
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11 views

Customer Retention Rate for a subscription business selling products with multiple contract durations

I have a question related to the standard metric used to evaluate subscription model businesses, aka user retention. We define user retention as the percentage of customers that keep their ...
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28 views

How to interpret left and right censoring

I am fully aware that question regrading left and right censoring has been asked before. I will however post my own question, as I believe that its focus differs significantly. Here goes: I have a ...
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3answers
135 views

Interview Question at Gaming Company

I came across the following interview question : In an online gaming company, customer churn is defined in terms of the number of days of continuous inactivity of the player. So how will you ...
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46 views

Deploying a churn prediction model

When deploying models such as churn prediction models how do you deal with the fact the you are constantly predicting on observations you previously trained on? I have an employee churn prediction ...
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Using probabilities on churn and death

I've been assigned with 2 models that forecast probabilities of death and churn for some clients. For every client, a 1 is assigned if the person left the company, or if he-she died, thus the task is ...
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163 views

survival analysis unobserved customers

I have got an extensive dataset of customers in a certain industry. I will build a survival model of churn on the customers. Some customers data back to 1990 and are still, as of 2020, customers in ...
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107 views

Employee churn as time-to-failure/survival analysis?

I have an employee churn problem where I have data for every three months of employees in a company ranging from 2015-2019. Does it make sense to model this problem as a time-to-failure/survival ...
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60 views

Building a Classification model for predicting Customer Churn

I am currently building a Customer Churn Prediction model and the project is in the process of development of models. The client has given data till Sep 2019 and wants to check if the model is able to ...
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33 views

How should time series data be grouped?

I'm fairly new to time series classification. I have an employee churn problem where I have quarterly data of the employees available. Should I group my observations by time (example in table A) or ...
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Unsure how to continuously train a churn model after my model has gone live

I'm having trouble describing this properly so I'll provide as many details as possible. First, here are a few details on the model that I am building: I have built a classification model that ...
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22 views

Will historical data lead to target leakage?

I'm bulding a employee churn model. I've employee data from 2016 to 2019 (of people who stayed/left the company), my goal is to train using data from 2016 to 2018 and predict on 2019. Since there's ...
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63 views

How to take advantage of historic data while doing churn prediction?

The problem: Predict customers who will downgrade their bank account category 2 months in advance. The data: 100's monthly variables for each customer for the last year. At first, I thought I could ...
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1answer
234 views

Churn Model Performance Measurement Metrics & KPI For Business

I have a customer churn model, which classifies people who are going to leave (Yes) from those who are staying ...
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49 views

User Churn - is it possible to find the moment that they will churn?

Hi experts out there - I have a user behavior log (e.g. # of logins, send post..etc) and trying to come up with a churn prediction model. A part of the request that I was asked was to find the value, ...
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50 views

Survival analysis for fixed time period licencing

I need to predict attrition of customers who use product that has fixed time period (1 year) licence. I have monthly feature usage data, for example the product has 5 features f1, f2, f3, f4 and f5, I ...
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Discussion on building logic for Churn for monthly renewal [closed]

I have a subscription based business dataset which looks like this: ...
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1answer
97 views

What are paralell training and attention mechanism?

I read a quite interesting paper here: http://hanj.cs.illinois.edu/pdf/kdd18_cyang.pdf Accordingly, the basic idea is to combine clustering and churn prediction so that it can imply some insight from ...
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683 views

How to predict customer churn (attrition) one month after start date? [closed]

I am trying to understand the strength of impact of variables on customer churn (attrition). I want to predict the probability that a customer will churn after time period t (after 1 months, after 3 ...
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520 views

Too many False Positives with Unbalanced Data

I am trying to predict customer churn in a telco company, using R.The dataset is very unbalanced, the target is around 0.6% of the base. 8,746 Customers will Churn 1,396,664 Customers do not churn I ...
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1k views

Longitudinal panel data classification

My problem context specifically lies in churn modeling, where accounts have account-specific attributes (like industry, number of employees, etc), but also have longitudinal yearly data (product usage ...
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584 views

Churn prediction on a highly passive and imbalance dataset

I'm trying to create a model to predict churn in the insurance industry. The objective will be to ' predict the probability of each member that will churn next month' i created a one row per member ...
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327 views

Using SVM and Logistic Regression for survival analysis

I am trying to use SVM and Logistic Regression for survival analysis but I am not able to properly find the implementation in R or python? I was wondering if it was possible to predict whether a ...
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226 views

INTERPRET ODDS RATIOS : What coefficients tells about monthly churn (people leaving)?

I am wondering how I can interpret results from GLM. To begin with I have 9 % monthly churn (people leaving). I am taking as an example. The coefficient for ...
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402 views

Likelihood of churn modeling

I am attempting to build a model that predicts the likelihood of 1000 customers churning every week, for the next 5 week. My training consists of 4 continuous feature variables, and a class variable ...
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616 views

Creating training and validation sets for churn model

I need to determine a statistically sound methodology for creating training and validation datasets for a churn model. Testing sets and model selection aren't a problem. The data spans 4 years of ...
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184 views

User inactivity to predict churn

I would like to use users' consecutive inactivity time in order to predict probability for not returning. For example, I would like to be able to say that if a user was inactive for a month, the ...
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624 views

How do I predict the churning out probability for each customer using survival analysis?

I have created a cox proportional hazards regression model for predicting churning out in R(using coxph function from the ...
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1answer
957 views

How do I predict the probability of churning out in the next month for e-commerce customers?

Data: Customer details : Name, registration device, state province, referrer, registration datetime, activation datetime Product details Transaction details Prediction: I need to predict what is ...
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61 views

Measuring customer attrition after a branch closure

Let's say that there were 1,000 customers who had primarily transacted at a branch prior to the branch's announced closure. Among this cohort, 40 customers closed their accounts with the bank the ...
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1answer
322 views

Identify customers with high risk of churn while training/testing model

This is more of a general question about modeling churn behavior. I hope I am posting in the right place and hopefully the question makes sense. I'm using a Telco dataset to create a churn model. ...
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909 views

Customer behavior analysis and clustering using data from loyalty program?

I'm trying to do some analysis on customers behavior. Basically, I have information on customer's loyalty points activities data (e.g. how many points they have earned, how many points they have used, ...
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232 views

Timeframe for training data in churn models vs prediction data - confused

I am developing a churn model for a subscription business. The churn rate is 7% yearly for it. The training data was prepared in such a way that customer information is tracked at the start of the ...
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194 views

Churn Prediction: why are churners usually selected as the positive class and not vice versa?

Is it just because churners usually form the minority class in the binary classification setting? Would it make sense to turn the non-churners group of customers into the positive class instead if ...
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172 views

Churn risk and lifetime period relationship

I am exploring churn and lifetime modeling. From what I see on various online material, the lifetime period is defined as 1 / churn-risk. For example, if the churn risk for a 12-month period is ...
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559 views

How to formulate a classification problem with time series element

Let’s say i want to do customer attrition prediction. Now customer attrition can happen anytime during an year. There are 2 ways i can think of setting up the problem. Fix a reference data e.g. 1 Nov’...
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133 views

Data segmentation using optimal features as input

I'm going to make a churn prediction model based on customer data from users of an app. I will have a feature set containing for example features over time related to user behavior in the app, and ...
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98 views

ML w/ Nested Data (Event data to help with Churn)

My personal experience with ML is strictly tied to Coursera ML class. Most of their classes are really good, but I never figured out how to apply it to my data. My question is; I have a lot of user ...
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731 views

Defining churn for customers with seasonal purchase patterns

I want to define customer churn accurately for the data showing seasonal patterns of not-purchasing. Our customers purchase on the regular basis most time of the year, with approx. 97% of all orders ...
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71 views

Customer Churn Measurement

Looking at trying to determine the dependent variable in a customer churn problem for a car dealership. Right now my customers make two types of purchases (oil changes, maintenance) and big ticket ...
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461 views

What kind of model should I use for churn risk prediction?

I have a data set containing many client's id, and its behavior characteristics measured each month before churn or censored. Data looks like: id || lifetime period || folow-up time before churn of ...
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1answer
109 views

R: How can I use global average as baseline?

Using Cox regression I'm trying to find the difference in churnrate for different demographic properties for a dataset with millions of records. The data is similar to below: user zip time ...
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1k views

Collinearity in Classification Model for Churn Prediction

I'm working on evaluating various classification algorithms to help predict customer churn (or at least ID interesting features to use in later strategy). The goal is to identify accounts who are at ...
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226 views

Bayes theorem applied correctly on client churn?

Here is a table selected and grouped from table where i store information about client - if he churned(TRUE - he churned, FALSE he stayed) and how many refund he got. CNT counts number of rows per ...
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994 views

Splitting between train/test for customer churn survival models

I am a bit confused on how data can be split between train/test and "live" data for predicting churn using survival models such as the one in RandomForestSRC package. Goal of the model is to predict ...
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54 views

Prediction With Diagnosis: Variable Importance by Test Set Observation

I'm tasked with predicting customer churn, and given hundreds of variables with which to create a binary classification model. In addition to producing a predicted probability of churn for each ...