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Questions tagged [churn]

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Predict average duration of a contract

I would like to predict the average duration of a contract. I have worked with different machine learning models before, especially from Scikit-learn, but this task seems to be somehow different for ...
Julian's user avatar
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0 votes
1 answer
35 views

Is this Dataset somehow skewed?

I am working on a dataset that has 100K points, it's about Customer churn. So I don't know whether this dataset is skewed, incomplete or what. I tried doing some feature engineering on it but couldn't ...
Harshal R's user avatar
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0 answers
16 views

Predicting Year-End Outcome from Monthly (and Annual) Data

I have data on customers' usage of various product features over time. Each month, a customer can choose to use a feature or not. I want to create a live system that produces the probability of a user ...
pyassign67's user avatar
0 votes
1 answer
29 views

Integrating time context in a machine learning model

Basically, what I'm curious about, are there any methods in machine learning to make the model take into account events that happen in real time that affect the data points during that time period. ...
Maxim Chopivskyy's user avatar
1 vote
1 answer
196 views

How to predict customer churn by a certain date?

I have a dataset of inactive users for the last 365 days, with columns: When subscribed (e.g. 10.10.2022) When unsubscribed (e.g. 12.10.2022) and client info I also have a set of data about active ...
Quaw's user avatar
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0 votes
1 answer
114 views

Should I use "Recency" as an predictor for churn if I want to catch churners early?

I want to build a customer churn prediction model that predicts probability of churn the next day and I'm looking for some features that might be important for the target variable which has outcomes ...
Parseval's user avatar
  • 103
1 vote
1 answer
69 views

More representative data set OR higher model evaluation metrics?

A colleague and I are working on a churn model and reached an impasse: Our data set is for a global product. We've been asked to look at the US market only. When we subset the data to the US only, the ...
Blue Otter Hat's user avatar
2 votes
1 answer
110 views

What to do when one feature has very large importance/weight?

I am new to Data Science and currently am trying to predict customers churn for a company that offers of subscription-based bookings management software. Its customers are gyms. I have a small ...
Daria's user avatar
  • 21
2 votes
2 answers
126 views

Logistic Regression for prediction

I would like to ask about the theoretical approach of using Logistic Regression for customer data and more specifically Churn Prediction (in BigQuery and Python). I have my customer data for an online ...
Ledian K.'s user avatar
  • 121
1 vote
1 answer
34 views

Data for churning model

I am thinking to improve the imbalanced dataset for my churning model, as most people recommend like over/under sampling. I am wondering if using past customer churn data would be helpful. Say that I ...
TC_L's user avatar
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1 vote
1 answer
13 views

What sort of analysis should be done in order to define our target outcome for modelling customer lapse?

I am trying to build a model to predict customer lapse and am required to define the target lapse definition myself. What sort of customer behavioural analysis should I do in order to define my ...
mlman's user avatar
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0 votes
2 answers
143 views

Churn prediction model doesn't predict good on real data

I am working currently on churn prediction problem. As an input I use data from date warehouse for a period 082016 - 032021(one row per month for each customer). Based on this data I have created a ...
zdz's user avatar
  • 113
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1 answer
35 views

What is the best way to model survival when the hazard rate decreases over time?

The standard survival analysis model - for example the model which forms the basis for the proportional hazards model - assumes the hazard rate is constant. In many applications this would be the ...
JJ Levine's user avatar
2 votes
2 answers
102 views

How do you effectively predict the top 20% most likely customers to churn from a dataset?

I am looking to work out that if I have a dataset with 100,000 existing customers who didn't churn and 20,000 previous customers that churned in the past and the business objective is to target the 20%...
Dean F's user avatar
  • 21
2 votes
1 answer
72 views

Expected Lifetime: Churn Formula vs. Experience Data

I am analyzing data for a subscription based company. I.e they sell a service in exchange for monthly payment. I would like to conduct an analysis and come up with an estimate of the average lifetime (...
Prince M's user avatar
  • 137
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1 answer
124 views

How to predict churn events that may happen within a period of time?

I am trying to build a model that predicts churn events in the future. The business wants to be able to identify which customers are likely to terminate the services within a month. "Within a ...
ddd's user avatar
  • 203
0 votes
1 answer
140 views

Should I perform customer segmentation before performing churn prediction?

Imagine a company with multiple lines of revenues coming from diferent products, but all customer can access these different products through the same account and the same online platform. My goal is ...
Breno Duarte's user avatar
1 vote
1 answer
173 views

How to use multiple cross-section observations per subject for churn prediction?

Recently I have started to teach myself about machine learning and I have ran into a dataset, which got me a bit confused. Dataset: The subjects of the dataset are university students (student ID == &...
Márton Szekeres's user avatar
1 vote
1 answer
321 views

Student Churn prediction

I am working on an ML model for student churn prediction. It is a classification problem if some student will churn or not. I have a lot of data like the student data and the activities of the student....
nnikolay's user avatar
  • 191
0 votes
0 answers
57 views

Parameters to build a churn prediction engine

Let us assume that I’m working for some company A, and my manager has asked me to build a churn prediction engine given that the product to which the churn prediction is to be done is unknown. The ...
Blackdeath's user avatar
3 votes
1 answer
221 views

Can I apply survival analysis to predict if a user will revisit the website?

I have one business problem in hand which is to predict if a user will revisit the website or not within 6 months. I need to majorly understand what are the factors which make the user return and also ...
asspsss's user avatar
  • 75
1 vote
1 answer
274 views

Predicting churn - deal with missing dates in time series and improve modelling result

This is the follow up question for General approach on time series for customer retention/churn in retail. I have a time series of data in the following form: ...
Michael's user avatar
  • 23
1 vote
1 answer
653 views

General approach on time series for customer retention/churn in retail

I have a time series of data in the following form: ...
Michael's user avatar
  • 23
1 vote
1 answer
136 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 ...
lsfischer's user avatar
  • 242
1 vote
1 answer
176 views

Churn Prediction Training Set

I don't understand how to form my dataset from activity(logins etc.) and characteristic(location, age etc.) raw user data. Ultimately, each row of the training set will have N activity features for a ...
thatguyoverthere's user avatar
1 vote
1 answer
530 views

How to predict whether the client will renew the subscription or not based on given data structure

I have a requirement where I want to predict whether the client will renew the subscription or not. And the data is something like below. Basically client's subscription end date can be anything. And ...
Akash's user avatar
  • 235
0 votes
1 answer
229 views

Churn Prediction Model based on Customer Activities

I am new to data science, so forgive me if i have not done my research well. I want to build a system that calculates the churn scores for each customer and hence try to prevent it. I just want to ...
Anh Tuấn Phạm's user avatar
0 votes
1 answer
781 views

Cohort analysis over 3 months

I am trying to look at the customer retention & churn by using cohorts for an e-commerce usecase. From a business perspective, a client is defined as churned if it hasn't performed any ...
Remus Raphael's user avatar
3 votes
1 answer
270 views

How to most effectively utilize historical data to train churn model

Suppose we have some historical data of users activity on a website and we want to build a churn prediction model (let's say we want to predict churn in a 2 month window). The usual approach, as I ...
Vitaly Manoshin's user avatar
4 votes
3 answers
1k views

How to predict whether or not a customer will renew

I have a dataset of customer contracts that specify a start date and if applicable an end date. Each month a customer is up for renewal. Below is an example of how the data is organized in excel: <...
Geometric's user avatar
1 vote
1 answer
51 views

How to represent a user who hasn't churned in training data

I am building a file with sample data that has a bunch of variables: date, customer_id, ...
James Stott's user avatar
0 votes
1 answer
111 views

Behavioural data required to predict churn

I am trying to build a predictive churn model that will identify customers who are likely to churn. I am defining a churned user as someone who hasn't transacted within 60 days. 90% of all ...
James Stott's user avatar
2 votes
1 answer
97 views

Decision tree to get difference in rates in two groups?

I have two sample groups of customers, each customer has 100s of features. For a single sample, i would use Decision Trees to find sub-groups that have a high churn rate. Thats easy. However, my ...
Arslán's user avatar
  • 131
0 votes
2 answers
155 views

Database on time to churn in telecomunication

I would like to research about time to churn1 in the telecommunication market. Does anyone have a link to such a database? The only ones I found did not include the time of churn, but only if a ...
User12547645's user avatar
0 votes
2 answers
406 views

How to handle NaNs for ratio feature for binary classifier?

I'm creating a churn model and would like to create a ratio (# customers / total transaction) for each merchant. About 70% of the data are NaNs (zero/zero). I was wondering what I should impute for ...
user3368526's user avatar
1 vote
2 answers
620 views

How would you deal with inf. or NA for rate or ratio as a feature variable

I'm trying to create a feature for a churn model (binary classifier). The feature is mean of sales growth rates for several months. But if I just take the mean of sales for several months, I often ...
user3368526's user avatar
0 votes
1 answer
78 views

Churn Prediction problem [closed]

I am a data science neophyte struggling to solve a churn prediction problem, i would be grateful to have someone help with the regression model
Olalekan Adeeko's user avatar
1 vote
0 answers
75 views

Causes for churn

I have a model which calculates churn probabilities for e-commerce customers based on their historical activity data (no. of sessions, page views, purchases etc) using supervised learning with an AUC ...
Sagar Jounkani's user avatar
5 votes
3 answers
2k views

Predicting contract churn/cancellation: Great model results does not work in the real world

I'm busy with a supervised machine learning problem where I am predicting contract cancellation. Although a lengthy question, I do hope someone will take the time as I'm convinced it will help others ...
Ernst Dinkelmann's user avatar
2 votes
1 answer
223 views

Your Prediction Model works. What to do after?

One of the most crucial skills of a data scientist is not only to be able to build an accurate predictive algorithm but to suggest a set of actions based on that to enhance the goal ratios. I have ...
sergiOrtiz's user avatar
1 vote
1 answer
2k views

Understanding churn prediction model [closed]

guys! I have a dataset with a bunch of costumer-behavior features and the output being "Churned"/"Not churned". I applied a simple Random Forest Classifier and got a nice performance. With this, I ...
Rodrigo Araújo's user avatar
3 votes
1 answer
243 views

Opposite of churn?

I'm trying to build a model in R that predicts when a customer will purchase a product again. However, I don't know what kind of model can handle time and predict this kind of outcome. I'm wondering ...
Michael Elma's user avatar
3 votes
2 answers
381 views

How to define user churn

I'd like to define our app user churn, Generally, people will define their app user churn by some simply way, like: if the user do not logon continually 7 days or 1 month, we will define them churn ...
llxlf's user avatar
  • 31
2 votes
2 answers
196 views

Dividing data between test, learn and predict

I was posting on stats.stackexchange but perhaps I should be posting here. Context. Subscription business that charges users a monthly fee for access to the service. Management would like to predict "...
Doug Fir's user avatar
  • 165
6 votes
3 answers
762 views

Data driven approach to define a churn user

I'm trying to define a churn prediction model for an online service (betting/gambling). A lot of papers talk about churn analysis/prediction for telco companies where defining a churn user is ...
Geims Bond's user avatar