Questions tagged [customer-lifetime-value]

Customer Lifetime Value (LTV) is the projected, discounted revenue that a customer will generate during their lifetime. LTV is a key business metric for many types of businesses.

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Help to confirm my Customer Lifetime Value approach in python [closed]

I have been working on a Customer Lifetime Value project where each customer's purchasing behavior is random but when they do purchase they sign up for a 12 month subscription meaning a single ...
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Where to get Time Series Subscriber or Customer Enrollment Data?

I am trying to get sample data on customer/subscriber enrollment which contains enrollment/renewal/exit transactions by date, along with other customer data such as income levels, age, and additional ...
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Churn Risk Modeling without ML

Is it readily possible to do predictive churn analysis (i.e., associating a churn risk with every individual/customer) using statistical tools (e.g. in Excel) not involving the use of machine learning ...
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buy till you die - Discounted cash flow - NBD/GAMMA [closed]

I was learning about BYTD in an online tutorial here I understand that it is used a) to predict the number of purchases that will be made by the customer. b) Lifetime value of the cuatomer over a ...
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Calculating a non-contractual CLV with dataset aggregated on yearly basis in R

I am looking for a way to predict the individual customer lifetime value (CLV) in a dataset that contains data over three years, aggregated on a yearly basis. I have the number of purchases and the ...
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Building a Customer Behavioral decision tree... seeking recommendations

I'm looking for some recommendations on how to model the following problem: I'm in the context of the retail industry and I want to model how the customers based their decisions at the time of picking ...
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What do I need to read/study to understand Peter Fader's papers that deal with CLV, Pareto/NBD models etc.?

I would appreciate if someone could tell me which subjects these papers listed below "belong to", and how do I get started in understanding them - what do I need to read/study and in what ...
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Which regression metrics fit best cases with very large values and exactly 0 values?

I'm working on a CLTV problem, where the objective is to predict the future spending of the customers, given their past behaviour. According to arXiv:1912.07753, paragraph 4 EVALUATION METRICS, I'm ...
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life time value prediction with logistic regression in r?

I have a mobile game dataset as below and I m expected to make analysis from users first 3 Days activity and predict/classify users’ Lifetime Values (LTV) from the user-level dataset with ...
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How can I predict customer lifetime value in 12 months?

I was trying to predict 'customer lifetime value' but only for the first 12 months of him/her in the platform I work for. However, most models, such as Pareto/NBD, are good in order to assess the real ...
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What is a good modelling approach for Customer Lifetime Value when consumption intensity matters?

I would like to produce a customer livetime value (CLV) analysis where the CLV is tied to the intensity of the use of the product, i.e. it is not a subscription business (where the relevant event ...
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Why do Pareto/NBD models require custom likelihood functions in PyMC3 and Stan?

I'm interested in Bayesian modeling of customer lifetime value (CLV), preferably via PyMC3. I've found that research in this area started mid-to-late 1900's and has remained active since. It would ...
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Chaining/combining logistic and linear models

I have a analysis that is looking to predict the total customer value based on a customer's first purchase amount. I am noticing that a set of features predict whether the customer will purchase ever ...
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Best way to forecast retention over a certain timespan

Let's say I have data, ...
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Fader/Hardie BG/NBD model. Interpretation of $a$ and $b$ of the beta distribution drop out process

On R's CLVTools package documentation, there's a sentence referring to the pareto/NBD model I'm working with the BG/NBD model not the pareto/NBD model. I'd like to understand if I can interpret the ...
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How can I improve the CLV accuracy from lifetimes model?

Not sure whether this should be asked in StackOverflow or here, but I believe this question is most about statistics, so I'll try it here. So I was modelling the Customer Lifetime Value using ...
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Brainstorming ways to calculate customer lifetime value for a long term subscription model

Business Model: Customers sign up for 12 month contracts with the option to incorporate add on services (these are also contractual). If they cancel, they still pay for 12 months and their account ...
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Calculate CLV / TLV for contractual Business

I am desperately trying to apply a CLV/TLV (Customer Lifetime Value) algorithm to my dataset in R. Unfortunately, the more I read about it, the less confident I get if all makes sense. =) Do you have ...
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LTV formula calls for Avg Order Value * Purchase Frequency * Lifespan--what to do when Lifespan is less than 1 year and Purchase frequency is 1?

Let's say hypothetically that you have the following: Looking at 5 years worth of data, we have in one group: ...
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Pareto/NBD and New/Existing Customers

I am looking at implementing a Pareto/NBD model to forecast customer lifetime value in a non-contractual business setting. One thing I haven't got my head around yet is whether such a model is equally ...
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Estimating variance of MLE estimate of Beta-Geometric/NBD without MCMC

I'm using Fader's BG/NBD model for customer LTV calculations. The log likelihood is the following: $$ \sum_{i=1}^{N} \ln L(r, \alpha, a, b|X_i=x_i, t_{x_i}, T_i) = \frac{B(a, b + x)}{B(a, b)}\frac{\...
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How to fit newer cohorts using Pareto/NBD or Beta/Geo for CLTV

I am trying to fit the popular Pareto/NBD or Beta/Geometric models for non-contractual, continuous customer data. On top of that I then fit the Gamma/Gamma model for monetary value (using the very ...
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14 votes
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RFM & customer lifetime value modeling in R

Can anybody tell me how to do recency, frequency & monetary value (RFM) modeling & customer value modeling in R? Also, can somebody refer me some literature on it?
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