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.

26 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
2
votes
0answers
424 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
votes
0answers
119 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
676 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
votes
0answers
51 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
votes
0answers
332 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
votes
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 ...
1
vote
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 ...
1
vote
2answers
436 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 ...
1
vote
0answers
124 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
vote
0answers
58 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
vote
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
vote
2answers
135 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
vote
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
vote
0answers
559 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
votes
0answers
14 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
votes
0answers
22 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 ...
0
votes
0answers
12 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 ...
0
votes
0answers
16 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 ...
0
votes
0answers
33 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, ...
0
votes
0answers
21 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 ...
0
votes
0answers
16 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 ...
0
votes
1answer
344 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’...
0
votes
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
votes
0answers
116 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?
-1
votes
1answer
268 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 ...
-1
votes
1answer
82 views

Survival analysis

I have a data set in which I have the date of joining of employees, age, and the date of leaving , also i have the dataset with current employees,so should I combine these two datasets or should I ...