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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17
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2answers
8k views

Survival Model for Predicting Churn - Time-varying predictors?

I am looking to build a predictive model for predicting churn and looking to use a discrete time survival model fitted to a person-period training dataset (one row for each customer and discrete ...
8
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2answers
6k views

Modeling customer churn - Machine learning versus hazard/survival models

Is their any rational (theoretical, substantial, statistical) to opt for either machine learning or hazard models when modeling customer churn (or more general, event occurences)?
6
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2answers
411 views

Machine learning for activity streams

My data takes the form of a stream of events for each customer in my sample. For a given customer, the stream takes the form of a list of events over time: At T1, customer C1 bought 1 unit of ...
4
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1answer
3k views

Predicting customer churn - train & test sets

I'm struggling with a problem where I'm trying to predict customer churn. I have monthly snapshot data going back several years, and tags for whether a customer left during a given month. My main ...
4
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1answer
172 views

What's the probability a rabbit will return to a (certain) forest?

Let's assume we have a forest. And there is a breed of rabbits that is visiting that forest all the time. It is possible to distinguish every individual rabbit. There are devices in that forest ...
3
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1answer
3k views

Low probability levels when doing logistic regression

I am building a Logistic regression model for a churn problem. When I scored the out of sample data set, I find very low probability levels as the output probability. Conventionally, I would look for ....
3
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1answer
383 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 ...
3
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0answers
1k views

Predicting customer churn [closed]

I'm trying to decide how to go about this problem. I have a large database of customers, both who have churned at some point, and who are current. I'm not sure how to create test/train sets from this....
2
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3answers
368 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 ...
2
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1answer
305 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 ...
2
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2answers
221 views

Reasonable approach for modelling churn (survival) and choice of intervention campaign (multinomial regression)?

I've only recently moved into customer analytics, and would love to get some advice around designing a reasonable approach to modelling my data. I want to be able to predict customer churn (that is, ...
2
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3answers
550 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 ...
2
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0answers
459 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 ...
2
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0answers
128 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 ...
2
votes
1answer
718 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 ...
2
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0answers
53 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 ...
2
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0answers
339 views

Bayesian Model For Churn

I need to evaluate how long a customer stays with the company given a retention offer she accepted $r\in\{r_1,\dots,r_k\}$ I'd like to use Bayesian inference for modelling churn. What prior ...
2
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0answers
3k views

How to select observation window and performance window for churn prediction?

I have to built a customer churn model for of a teleco. The churn rate is 15 %. There is no particular campaign conducted. By churn I mean customer leaving the teleco permanently. Data is available ...
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2answers
2k views

Temporal abstraction in Churn analysis: Why do we need it?

Could you explain the need of temporal abstraction in churn analysis intuitively with a simple example? I tried Google but there are not any clear answers , especially for churn analysis.
1
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2answers
172 views

Churn Prediction: why is 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 ...
1
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1answer
964 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 ...
1
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1answer
138 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 ...
1
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1answer
168 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 ...
1
vote
1answer
367 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 ...
1
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1answer
688 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 ...
1
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1answer
838 views

customer behavior analysis and segmentation 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, ...
1
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2answers
552 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 ...
1
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1answer
40 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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0answers
31 views

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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0answers
127 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 ...
1
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0answers
62 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 ...
1
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0answers
70 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 ...
1
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1answer
93 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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0answers
1k views

Choosing right set of variables for Logistic regression and decision tree [duplicate]

I am a beginner in R. I am doing logistic regression using around 80 independent variables using glm function in R. The dependent variable is ...
1
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2answers
143 views

using training data in final model output

I have customer data for around 400,000 customers where 270,000 of them are current customers and 130,000 of them are past customers who churned, what I am doing is classifying them as 0 (non-churn) ...
1
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0answers
141 views

Intuition behind Expected Value of conversion events

I'm trying to develop a high level model to value events in a marketing conversion funnel. To take a simple e-commerce example: You start with leads in the form of ad clicks. Some % of these ad ...
1
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0answers
584 views

Churn predictive modelling

I'd like to build a predictive model for predicting churn for a website. Here is the information I have for each customer : What they did : visit the website Buy something Do not read ...
0
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1answer
173 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 ...
0
votes
1answer
36 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 ...
0
votes
1answer
290 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. ...
0
votes
1answer
720 views

Bayesian Network or Logistic regression?

The Bayesian Networks and Logistic regression can be used to predict events or give to each customer the propensity to have a behavior. Which are the advantages or disadvantages of these 2 methods? ...
0
votes
1answer
84 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 ...
0
votes
1answer
202 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 ...
0
votes
1answer
183 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 ...
0
votes
1answer
124 views

Performing CART using unlabeled data

I am involving in a project of customer churn prediction. I have 10000 customers data. All the data are unlabeled data. Now my question is can I perform CART analysis with unlabeled data?
0
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0answers
13 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 ...
0
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0answers
21 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 ...
0
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1answer
48 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 ...
0
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0answers
17 views

Customer Churn: Difference predicting has or will churn

I have got the following question: I want to build a basic model which predicts whether a customer will churn or not using logistic regression to target 'high-risk' customers with, for instance, ...
0
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0answers
27 views

How to approach machine learning time specific data; which months of usage to use?

I am relatively new to the data science area and just have a question about how to approach a time specific machine learning problem. Just as an FYI I am currently using a random forest classifier for ...