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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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1answer
164 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 ...
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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
327 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 ...
3
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1answer
353 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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0answers
8 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, ...
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1answer
762 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, ...
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0answers
17 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 ...
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0answers
10 views

online news readers engagement index (inverse of churn model?)

I would like to get a second opinion of the problem of assigning engagement scores to online news readers. Currently, I build a churn model as required by the company, that mainly predicts the ...
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1answer
82 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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0answers
12 views

magnitude of covariates in user churn/survival analysis

Hi experts out there! I’m trying to use survival analysis for my user churn prediction. In General, I can get % of survival rate (X axis) as time goes by (Y axis) from survival analysis for one of ...
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0answers
32 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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1answer
38 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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1answer
638 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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1answer
326 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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0answers
11 views

BTYD: Can we predict Active/Churned based on P(alive) / P(active) without a holdout period?

I created a model with BTYD/lifetimes using the p(active)/p(alive) and optimized the threshold for dividing into active and churned customers. The prediction overall compared to actual data (holdout ...
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1answer
271 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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0answers
26 views
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0answers
14 views

Predicting a binary outcome (churn) with zero inflated data

I'm trying to understand what the best method to predict churn of a customer. Moreover, the purpose of this exercise is to weight what features within our product correlate most to retention. Most ...
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 ....
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0answers
50 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 ...
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0answers
52 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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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 ...
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2answers
486 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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1answer
299 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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1answer
233 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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3answers
300 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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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....
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1answer
157 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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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 ...
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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 ...
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1answer
115 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 ...
2
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1answer
240 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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0answers
394 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 ...
7
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2answers
5k 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)?
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1answer
361 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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0answers
111 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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1answer
528 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 ...
0
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0answers
40 views

Correlation analysis while detecting outliers

I have simple dataset here. Supposed I want to find out which customers who bought a certain item are more likely to come back after 10 months. I have 2 sets of data The repeat purchase % of users ...
0
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1answer
34 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 ...
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 ...
2
votes
0answers
322 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 ...
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0answers
120 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 ...
0
votes
1answer
155 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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2answers
160 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 ...
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1answer
148 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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1answer
912 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
vote
2answers
133 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) ...
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0answers
68 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 ...
0
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1answer
686 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? ...
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1answer
90 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 ...