The DOI matches its Crossref record; 142 of the 157 references it cites were found in a registry or an index; 3 of the 54 sources its claims cite were checked for support.
A Survey on Churn Analysis in Various Business Domains
Open accessAbstract
In this paper, we present churn prediction techniques that have been released so far. Churn prediction is used in the fields of Internet services, games, insurance, and management. However, since it has been used intensively to increase the predictability of various industry/academic fields, there is a big difference in its definition and utilization. In this paper, we collected the definitions of churn used in the fields of business administration, marketing, IT, telecommunications, newspapers, insurance and psychology, and described their differences. Based on this, we classified and explained churn loss, feature engineering, and prediction models. Our study can be used to select the definition of churn and its associated models suitable for the service field that researchers are most interested in by integrating fragmented churn studies in industry/academic fields.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
This survey reviews churn analysis across business domains, collecting definitions and comparing churn loss, feature engineering, and prediction models. It classifies churn as contractual or non-contractual and reports that preferred modeling techniques vary by industry, with deep learning more common where dense log data exist.
Key findings
- The survey identifies 12 business fields with churn prediction and reports model-type counts: telecommunications has 26 traditional machine learning, 3 statistics, 3 graph theory, and 1 deep learning study; games has 16 traditional machine learning, 7 statistics, and 2 deep learning; finance has 10 traditional machine learning, 2 statistics, and 1 deep learning (Table 2).
- Churn definitions split into contractual churn (non-renewal at contract date) and non-contractual churn, where a time window defines inactivity; Yang et al. (2019) found more than 95% of mobile-game customers did not return after 3 consecutive absent days and set 3 days as the window, while Lee et al. (2018) set 14 weeks as the period when 75% or more customers were continuously unconnected.
- Loss is framed via customer acquisition cost (CAC) and customer lifetime value (CLV); the paper cites Reichheld et al. (1996) that a 5% increase in retention rate achieved 35% and 95% increases in net present value for a software company and an advertising agency, respectively.
- Feature engineering includes one-hot encoding, bucketing, data imputation, normalization, feature embedding, and imbalanced-data handling; for imbalance, Amin et al. (2016) found MTDF highest accuracy versus SMOTE, ADASYN, MWMOTE, ICOTE, and TRkNN, while Gui (2017) reported SMOTE best in telecom. Performance evaluation commonly uses AUC/ROC or lift/top-decile lift.
Methods
- Design: literature survey integrating fragmented churn studies across industry and academic fields; no new empirical experiment is reported.
- Data/sample: collected definitions of churn from business administration, marketing, IT, telecommunications, newspapers, insurance, and psychology, and cases from 12 business fields.
- Analysis: thematic classification and comparison of churn definitions, churn loss (CAC/CLV), feature engineering, prediction models (traditional machine learning, statistics, graph theory, deep learning), and performance evaluation.
Limitations
- The paper states that because each study uses different sizes and types of features, the set of studies has a limitation in comparing a common performance; readers cannot determine which model is suitable and has the best performance for their study.
- The paper states future work will combine feature engineering with open churn datasets and construct various churn prediction models, including a deep learning model, to compare and evaluate suitability.
- Evident from the text: the survey is narrative and does not run a benchmark or meta-analysis; claims such as deep learning outperforming other algorithms are based on cited studies rather than independent validation.
Model-written summary. Check it against the paper before relying on it.
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Claims the paper makes
3 of 54 cited sources checked · 0 supported · 0 flagged · accuracy not yet measured
The cited sources that could be checked couldn’t confirm or dispute this claim.
In the paper
“Therefore, some studies measured the CAC, and calculated it as the loss incurred when a customer churned [8] [31] [72].”
§ A Survey on Churn Analysis in Various Business Domains > A. CUSTOMER ACQUISITION COST (CAC)
What the sources say
- Not checked — no full text of the sourcecites [8] source
- Not checked — no full text of the sourcecites [31] source
- Could not verifycites [72] sourceExperimental — accuracy not yet measured
The Conclusions state that acquiring subscribers is expensive and that retaining them matters, while Section 4 models the probability of churn. Neither passage measures customer acquisition cost (CAC) or calculates it as the loss incurred when a customer churns; searches for acquisition costs and financial loss from churn found no such calculation. (LLM, conf=0.76)
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesThe cited sources that could be checked couldn’t confirm or dispute this claim.
In the paper
“Zhu, Lingxue, and Nikolay Laptev.(2017) improved the performance of the prediction model by compressing sparse data through a longshort-term memory autoencoder and then concatenating the data with fully connected neural networks (FCNNs) [143].”
§ A Survey on Churn Analysis in Various Business Domains > 5) Feature Embedding
What the sources say
- Could not verifycites [143] sourceExperimental — accuracy not yet measured
The Implementation section describes two deep-learning algorithms, and the convolutional-network section describes fully connected layers, but neither passage addresses Zhu and Laptev's claimed method. Searches for their names, an LSTM autoencoder, sparse-data compression, and concatenation found no passage supporting the attributed claim. Page numbers were not available in our copy. (LLM, conf=0.76)
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A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“The majority of the early studies on churn were conducted from a management perspective, especially CRM (Customer Relation Management) [30] [31].”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
What the sources say
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In the paper
“The financial and insurance industries also predict customer churn.”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesThe paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Telecommunications services have high customer stickiness despite high customer acquisition costs.”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesThe paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“However, predicting churn and compensating for it with the last log of service usage do not change the overall service usage patterns of customers.”
§ A Survey on Churn Analysis in Various Business Domains > V. FEATURE ENGINEERING
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesThe paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“We were able to confirm that preferred modelling techniques were different depending on the business field.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesThe paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Businesses with dense log data and easy access to customer information, such as the games and telecom-munications industries, are applying relatively many deep learning techniques using big data, which is a fast trend.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“In the past, customer churn had occurred explicitly through contractual cancellations, however, in the modern services including Internet and retail services, frequent customer churns occur due to the low customers' investment costs [19] [20] [21] [96].”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
What the sources say
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, the churn prediction models implemented using log data can be used for Internet services in various industries.”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Unlike the explicit methods such as bucketing, a deep learning algorithm can learn that customers' latent behavior who are about to churn in a end-to-end way.”
§ A Survey on Churn Analysis in Various Business Domains > 5) Feature Embedding
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The use of undersampling technique when dealing with churn dataset has disclosed the possibility of discarding useful information that expresses the characteristics of retained customers.”
§ A Survey on Churn Analysis in Various Business Domains > C. DEALING WITH IMBALANCED DATA
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIn the paper
“According to the study conducted by Mozer, Michael C., et al. (2000), the retained customers are known to provide a better return on investment than the newly recruited customers through the CAC [16].”
§ A Survey on Churn Analysis in Various Business Domains > A. CUSTOMER ACQUISITION COST (CAC)
What the sources say
- Not matchedcites [16]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“On the contrary, the use of oversampling technique has disclosed the possibility of raising the overfitting issue due to replicating insufficient variance size of the oversampled churned group data.”
§ A Survey on Churn Analysis in Various Business Domains > C. DEALING WITH IMBALANCED DATA
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesNone of the sources cited for this claim have been checked yet.
In the paper
“Therefore, if customer churn is prevented and appropriate incentives are provided, it is of great help in maintaining sales [16] [32] [33] [34].”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
What the sources say
- Not matchedcites [16]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites [32] source
- Not matchedcites [33]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:boosted· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Not matched
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“Therefore, some studies show that short-term prediction and monetary rewards soon leads to another churn [10] [45].”
§ A Survey on Churn Analysis in Various Business Domains > V. FEATURE ENGINEERING
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Meanwhile, there could be an issue where the prediction model may not have enough data for training if a simple undersampling method is used to obtain a balanced dataset.”
§ A Survey on Churn Analysis in Various Business Domains > C. DEALING WITH IMBALANCED DATA
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“In addition, by multiplying the number of customers planning to churn by the incentive cost to be provided to those customers, the cost of business loss that can incur when the customers are not retained can be calculated through the churn prediction model [45] [53].”
§ A Survey on Churn Analysis in Various Business Domains > A. CUSTOMER ACQUISITION COST (CAC)
What the sources say
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In such way, if a customer who is likely to churn the service in the near future can be inferred through the churn prediction, the basis for measuring a suitable incentive for the customer while minimizing the CAC can be established.”
§ A Survey on Churn Analysis in Various Business Domains > A. CUSTOMER ACQUISITION COST (CAC)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“Verbraken, Thomas, Wouter Verbeke, and Bart Baesens.(2012) and Neslin, Scott A., et al. (2006) proposed formulas for calculating the net profit using churn rate, CAC, CLV, fixed operating cost, and incentive cost [54] [55].”
§ A Survey on Churn Analysis in Various Business Domains > B. CUSTOMER LIFETIME VALUE (CLV)
What the sources say
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In general, the performance evaluation algorithms of machine learning model developed for churn prediction use the area under the curve (AUC) of receiver operating characteristic (ROC) curve or the lift.”
§ A Survey on Churn Analysis in Various Business Domains > C. PERFORMANCE EVALUATION
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIn the paper
“The Deep and Shallow model they built showed excellent churn prediction performance compared to other models.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
What the sources say
- Not checked — no full text of the sourcecites [10] source
Strength:boosted· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, given minute timestamps and abundant observations, applying this data to deep learning algorithms for the generation of latent features is expected to produce better performance than conventional churn prediction models.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
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In the paper
“Thus, the AUC close to 1 indicates that the churn prediction model accurately distinguishes difference between the characteristics of churn customers and non-churn customers [13] [45] [55] [95].”
§ A Survey on Churn Analysis in Various Business Domains > C. PERFORMANCE EVALUATION
What the sources say
Strength:hedged· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In such case, feature engineering techniques for processing logs have a significant effect on model performance enhancement.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“To define customer churn in the non-contractual settings, researchers used in timeseries modification techniques such as grouping customer id to make tidy data or calculate behavioral variances [114].”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
What the sources say
- Not checked — no full text of the sourcecites [114] source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Deep learning algorithms have been found to outperform other algorithms.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, as each study uses different sizes and types of features in the data, the set of studies provided in this paper has a limitation in comparing a common performance.”
§ A Survey on Churn Analysis in Various Business Domains > VIII. LIMITATIONS AND ISSUES FOR FURTHER RESEARCH
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In the paper
“This is due to variations in which churn prediction model has the best performance depending on the data format.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
- Probably not a substantial claim. 130
- It may state two separate claims as one. 33
The cited sources that could be checked couldn’t confirm or dispute this claim.
In the paper
“Burez, Jonathan, and Dirk Van den Poel.(2009) utilized a method called the CUBE method to improve the churn prediction performance.[95].”
§ A Survey on Churn Analysis in Various Business Domains > C. DEALING WITH IMBALANCED DATA
What the sources say
- Could not verifycites [95] sourceExperimental — accuracy not yet measured
The paper’s introduction (p. 1) and evaluation (pp. 5–7) concern time-series forecasting and anomaly detection at Uber. Searches for Burez, Van den Poel, CUBE, and churn prediction found no passage addressing the attributed claim. (LLM, conf=0.76)
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- Could not verify
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In addition, contractual churn is frequently found in a flat-rate service such as music and movie streaming services.”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Therefore, these days majority of the log-based churn prediction problems use the probabilistic method to determine whether customers are churning or not and to give customers incentive to reuse their service.”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“There are 12 business fields that performed churn prediction.”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The time window method is frequently used when analyzing activity logs these days in a non-contractual situation.”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“The criteria for setting the time window are different for each service feature.”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Modern churn prediction problems are mainly analyzed using log data.”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The telecommunications industry accounts for the majority of previous studies on churn.”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Churn has been defined in various ways in multiple industries.”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“However, the criteria for 'inactivity'and 'prolonged'are different according to each research field.”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Therefore, in most churn prediction problems, the churn period is defined as a section that can restore customers' trust.”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“However, not all logs are helpful in estimating churn.”
§ A Survey on Churn Analysis in Various Business Domains > A. DEVELOPING NEW FEATURE
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None of the sources cited for this claim have been checked yet.
In the paper
“There were some studies which approached customer churn from a psychological perspective.”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The efficiency of a retained customer value is usually calculated with the CLV.”
§ A Survey on Churn Analysis in Various Business Domains > B. CUSTOMER LIFETIME VALUE (CLV)
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Research on churn prediction was also conducted in online dating, online commerce, Q&A services, and social network-based services [46]”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
What the sources say
- Not checked — no full text of the sourcecites [46] source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Logs remain in the majority of services.”
§ A Survey on Churn Analysis in Various Business Domains > A. DEVELOPING NEW FEATURE
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None of the sources cited for this claim have been checked yet.
In the paper
“Studies on churn prediction were conducted in the human resources and energy fields although they were minority.”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The newspaper subscription and mu-sic streaming service offer fixed-rate services, and customer churn is consistent with the contract renewal period.”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“On the other hand, because the Internet service goes into an inactive state as customers wish, contract renewal takes place nearlyreal-time.”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Later on, studies on churn have been actively conducted in the gaming field as in the telecommunication field.”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
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In the paper
“Therefore, studies have emerged in recent years to develop other features that are as important as the last log the customer left before churning, or to discover potential churners by reprocessing the time series features.”
§ A Survey on Churn Analysis in Various Business Domains > V. FEATURE ENGINEERING
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In the paper
“These features are used to extract customers who carry business values.”
§ A Survey on Churn Analysis in Various Business Domains > A. DEVELOPING NEW FEATURE
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“These services have a fast cycle of customer inflow and churn because of mass competition.”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“There are multiple studies on the method of calculating the CLV and that apply the CLV to churn models.”
§ A Survey on Churn Analysis in Various Business Domains > B. CUSTOMER LIFETIME VALUE (CLV)
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In the paper
“Here, the value of m may be different for each customer segment.”
§ A Survey on Churn Analysis in Various Business Domains > B. CUSTOMER LIFETIME VALUE (CLV)
Strength:hedged· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Churn is generally related to customers' last time activity.”
§ A Survey on Churn Analysis in Various Business Domains > V. FEATURE ENGINEERING
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Finance 10 | 2 | | 1”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Telecommunications 26 | 3 | 3 | 1”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“According to the research of this paper, many articles use AUC as a performance measurement method aside from standard precision.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Internet Service 1 | 1 | | 1”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Psychology 1 | | | |”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Retails 2 | | | |”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Finance 10 | 2 | | 1”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Game 16 | 7 | | 2”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Marketing 1 | | | |”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Newspapers 4 | | | |”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Internet Commerce 1 | | | |”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“As for the financial and insurance sectors, since the log data is relatively small and the information obtained from customers does not change to a great degree, there are many statistical approaches using traditional machine learning models or survival analysis.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Internet Service 1 | 1 | | 1”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Commerce 1 | | | |”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Music Streaming Service 1 | | | |”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Insurance 3 | | | 1”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Internet Service 1 | 1 | | 1”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Energy 1 | | | |”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Finance 10 | 2 | | 1”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Telecommunications 26 | 3 | 3 | 1”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Telecommunications 26 | 3 | 3 | 1”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Telecommunications 26 | 3 | 3 | 1”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Game 16 | 7 | | 2”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Game 16 | 7 | | 2”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Insurance 3 | | | 1”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Human Resources 1 | | | |”
§ A Survey on Churn Analysis in Various Business Domains > Churn Prevention
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“These non-contractual customer churns occur due to low switching cost for changing the service [31].”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
What the sources say
- Not checked — no full text of the sourcecites [31] source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Lee, Eunjo, et al. (2018) defined the period during which 75% of customers were continuously unconnected as a churn section by taking into consideration the characteristics of PC game services [17].”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
What the sources say
- Not checked — no full text of the sourcecites [17] source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“According to Fig. 2, the period during which customers were unconnected more than 75% was 14 According to the figure, the period during which 75% or more customers are continuously unconnected is 14 weeks.Therefore, if a customer is unconnected for 14 weeks, he/she is regarded as churn and this period is a time window section.”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
What the sources say
- Not checked — no full text of the sourcecites [17] source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“And through such observation, the expected net business value can be increased by predicting customer churn rates and providing possible churn customers with incentives to retain them from leaving [16] [23].”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
What the sources say
- Not matchedcites [16]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites [23] source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
In the paper
“If the time period during which a customer completely churns is selected as a time window, the period for churn definition exponentially increases and it does not provide any gain in terms of business as changing the will of the customers who want to churn is deemed impossible [17].”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
What the sources say
- Not checked — no full text of the sourcecites [17] source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As described above, there are two customer churn types, which are contractual churn and non-contractual churn.Additionally, there are three churn observation criteria as follows: monthly, daily, and binary.”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Yang, Wanshan, et al. (2019) analyzed log data to define the churn period of mobile games, and the analysis result showed that more than 95% of customers did not return when they were absent for 3 consecutive days.They set 3 days as the time window churn period [43].”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
What the sources say
- Not matchedcites [43]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The reason for having multiple ways of defining customer churn is to periodically monitor the customers' status changes.”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Therefore, the Internet service interprets the log-in as prolonged, that is, the retention of the service, and interprets unconnected access for a certain period of time as churn [17].”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
What the sources say
- Not checked — no full text of the sourcecites [17] source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, we can divide the criteria of churn into contractual churn and non-contractual churn.”
§ A Survey on Churn Analysis in Various Business Domains > II. DEFINITION OF CHURN
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, it is necessary to extract important information using an appropriate feature engineering technique for churn prediction.”
§ A Survey on Churn Analysis in Various Business Domains > B. FEATURE MODIFICATION
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
- Rests on an assumption: Service indicators are generally sparse and have many outliers, and the data distribution is skewed to one side.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“There are four domains as a method of building a churn prediction model.They are traditional machine learning, statistics, graph theory, and deep learning.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“likewise binary encoding produces distance between categories.”
§ A Survey on Churn Analysis in Various Business Domains > 1) One-hot encoding
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“Zhang, Rong, et al. (2017) also used latent feature modification for churn prediction.They classified features into a memorization feature and a generalization feature depending on data attributes [11].”
§ A Survey on Churn Analysis in Various Business Domains > 5) Feature Embedding
What the sources say
- Not checked — no full text of the sourcecites [11] source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“To calculate CLV within the contractual settings, a shifted-Beta-Geometric (sBG) model is used.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Without normalization, the machine learning model generally have to select a very small learning rate when searching for the optimum, resulting in a long training time.”
§ A Survey on Churn Analysis in Various Business Domains > 4) Normalization
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
- Rests on an assumption: The distribution of service data is generally skewed to one side.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Bucketing (also called Discrete binning or Data binning) can be used for both categorical and continuous features.”
§ A Survey on Churn Analysis in Various Business Domains > 2) Bucketing
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“Nimmagadda, Sravya, Akshay Subramaniam, and Man Long Wong.(2017) argued that filling the missing data improved performance instead of dropping them [58].”
§ A Survey on Churn Analysis in Various Business Domains > 3) Data Imputation
What the sources say
- Not checked — no full text of the sourcecites [58] source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As opposed to the memorization feature, the generalization feature exhibits the characteristics of the churn/no-churn group with only shortterm attributes.”
§ A Survey on Churn Analysis in Various Business Domains > 5) Feature Embedding
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If a customer churns from a service, the company will have to recruit another customer by spending the CAC to maintain the service.”
§ A Survey on Churn Analysis in Various Business Domains > A. CUSTOMER ACQUISITION COST (CAC)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
- Rests on an assumption: The CAC cost is the minimum value to operate service makes from a customer with Return on Investing (ROI).
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The latent features generated during this process compresses high-dimensional sparse data into low-dimensional dense data.”
§ A Survey on Churn Analysis in Various Business Domains > 5) Feature Embedding
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Data imputation techniques may help to solve data imbalances and make the best of the information used in the model.”
§ A Survey on Churn Analysis in Various Business Domains > 3) Data Imputation
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Lee, Eunjo, et al. (2018) claimed that in the customer churn prediction competition hosted by the authors, the winning team showed significantly better performance than other teams by utilizing the autoencoder to compress the sparse data [10].”
§ A Survey on Churn Analysis in Various Business Domains > 5) Feature Embedding
What the sources say
- Not checked — no full text of the sourcecites [10] source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Nimmagadda, Sravya, Akshay Subramaniam, and Man Long Wong.(2017) used techniques such as log-normalization or quantile normalization to build a prediction model other than 0-1 normalization [58].”
§ A Survey on Churn Analysis in Various Business Domains > 4) Normalization
What the sources say
- Not checked — no full text of the sourcecites [58] source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“In particular, probability models have been traditionally used for customer-base analysis [149].”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
What the sources say
- Not checked — no full text of the sourcecites [149] source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“However, if a single service is run for a long time, the service competition intensifies and the Customer Acquisition Cost (CAC) tends to increase [16]”
§ A Survey on Churn Analysis in Various Business Domains > III. CHURN ANALYSIS IN VARIOUS BUSINESS FIELD
What the sources say
- Not matchedcites [16]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These types of data slowly reveal the characteristics of the churn/no-churn group usually over a period of time.”
§ A Survey on Churn Analysis in Various Business Domains > 5) Feature Embedding
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Numerical encoding breaks the nominal nature inherent in categorical data and results in encoding with linearity between categories”
§ A Survey on Churn Analysis in Various Business Domains > 1) One-hot encoding
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The boundary is blurring between the above four disciplines in recent times.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“One-hot encoding on categorical data in this way produces an orthogonal feature space for each category.”
§ A Survey on Churn Analysis in Various Business Domains > 1) One-hot encoding
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Normalized features can achieve rapid model training while using relatively large learning rates compared to the initial data.”
§ A Survey on Churn Analysis in Various Business Domains > 4) Normalization
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If a prediction model is trained using this data and it always outputs only the results that indicate customers being retained, the model would maintain a 96 percent accuracy.In this case, although the accuracy of the model may be said to be high, the model would not be effective in identifying characteristics of churned customers.”
§ A Survey on Churn Analysis in Various Business Domains > C. DEALING WITH IMBALANCED DATA
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: In a stable service, the number of churned customers generally account for a small proportion compared to the number of retained customers.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The churn feature that combines the memorization feature and the generalization feature predicts churn by combining deep learning models and traditional machine learning techniques.”
§ A Survey on Churn Analysis in Various Business Domains > 5) Feature Embedding
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The generalization feature data predicts results with shallow machine learning models such as logistic linear regression.”
§ A Survey on Churn Analysis in Various Business Domains > 5) Feature Embedding
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“Sifa, Rafet, et al. (2015) improved performance by using a semi-supervised learning technique since there was no sufficient data to solve prediction problems [52].”
§ A Survey on Churn Analysis in Various Business Domains > 3) Data Imputation
What the sources say
- Not checked — no full text of the sourcecites [52] source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These changes have the side effect of the model learning unintentional continuity.”
§ A Survey on Churn Analysis in Various Business Domains > 1) One-hot encoding
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, churn prediction tends to be more accurate when processing raw logs.”
§ A Survey on Churn Analysis in Various Business Domains > B. FEATURE MODIFICATION
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
- Rests on an assumption: Service indicators are generally sparse and have many outliers, and the data distribution is skewed to one side.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In general, when the customer behavior is stored as log data in gaming, Internet service, and telecommunication service fields, the customer data is often found in the form of highdimensional sparse data.”
§ A Survey on Churn Analysis in Various Business Domains > 5) Feature Embedding
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For features that are too sparse to be used in the model due to the large variance because the feature value category is too wide, bucketing is a technique that makes these features into categorical features.”
§ A Survey on Churn Analysis in Various Business Domains > 2) Bucketing
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“According to the study, the Mega-Trend Diffusion Function (MTDF) method provided the highest accuracy when compared with other techniques such as Synthetic Minority Oversampling Technique (SMOTE), Adaptive Synthetic Sampling Approach (ADASYN), Majority Weighted Minority Oversampling Technique (MWMOTE), Immune Centroids Oversampling Technique (ICOTE) and couples Top-N Reverse K-Nearest Neighbor (TR”
§ A Survey on Churn Analysis in Various Business Domains > C. DEALING WITH IMBALANCED DATA
What the sources say
- Not checked — no full text of the sourcecites [144] source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In this way, we can calculate the value of a churn prevention model by multiplying the loss cost of one customer by the number of people who are prevented from churn with a churn prediction algorithm.”
§ A Survey on Churn Analysis in Various Business Domains > IV. CUSTOMER CHURN LOSS
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- Rests on an assumption: Customer churn behavior is quantitative.
- Rests on an assumption: It is difficult to directly relate customer churn to a decrease in sales.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, with the emergence of deep learning techniques of machine learning, it has become possible to manage timedependent high-dimensional sparse data.”
§ A Survey on Churn Analysis in Various Business Domains > 5) Feature Embedding
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Moreover, a deep learning algorithm enables generating latent features by compressing long-term features that is a new technique of feature embedding.”
§ A Survey on Churn Analysis in Various Business Domains > 5) Feature Embedding
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“This is because a balanced dataset composed of churned and retained customers has higher noise tolerance than a imbalanced dataset, hence it is more likely to be able to obtain decision boundaries for minor groups, which in this case denotes the churned customer dataset [91].”
§ A Survey on Churn Analysis in Various Business Domains > C. DEALING WITH IMBALANCED DATA
What the sources say
- Not checked — no full text of the sourcecites [91] source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Gui, Chun.(2017) applied undersampling, oversampling, and SMOTE methods to an imbalanced dataset of telecommunication field and compared the performance of the derived churn prediction models [145].”
§ A Survey on Churn Analysis in Various Business Domains > C. DEALING WITH IMBALANCED DATA
What the sources say
- Not checked — no full text of the sourcecites [145] source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Hence, in the past, the customer behavior data was simplified through a bucketing process.”
§ A Survey on Churn Analysis in Various Business Domains > 5) Feature Embedding
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“In the study, the author suggested that the SMOTE sampling technique provided the best prediction performance.”
§ A Survey on Churn Analysis in Various Business Domains > C. DEALING WITH IMBALANCED DATA
What the sources say
- Not checked — no full text of the sourcecites [145] source
Strength:hedged· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In statistics, probability models have been mainly used for conducting churn predictions.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In a customer-base analysis, churn rate is applied to the survival time estimation when calculating the CLV.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Churn studies on different fields are undoubtedly helpful in grasping the comprehensive view of churn and exploring various features to apply them to the churn models.”
§ A Survey on Churn Analysis in Various Business Domains > VIII. LIMITATIONS AND ISSUES FOR FURTHER RESEARCH
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
In the paper
“According to Goodfellow, Ian, Yoshua Bengio, and Aaron Courville.(2016), deep learning is part of machine learning [64].”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
What the sources say
- Not checked — no full text of the sourcecites [64] source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Deep learning techniques often used for predicting customer churn mainly involves training via sparse customer data that have been densified, or a fully-connected neural network produced from extracting the latent vector from the autoencoder and concatenating those features with static features.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the non-contractual settings, customer churn tends to have a characteristic of continuous probabilistic.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Most churn prediction models are related to customer relation management.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
- Rests on an assumption: Most churn prediction models are related to customer relation management.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, the time window is used to select potential churning customers rather than measuring a customer's complete churn.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
In the paper
“Accordingly, the sBG model allows continuous interpretation of the conditions in which the customer retention is determined to be discrete-time contractual in a contractual service [150].”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
What the sources say
- Not checked — no full text of the sourcecites [150] source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, there may be performance differences depending on whether the churn prediction model is robust against false positives or false negatives.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A ROC curve is a very robust measurement criterion that measures classifiers independent of class distribution and misclassification error cost.”
§ A Survey on Churn Analysis in Various Business Domains > C. PERFORMANCE EVALUATION
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Accordingly, although researchers may be able to discern whether if their constructed model is used widely through our study, they would not be able to determine which model is suitable and has the best performance for their study.”
§ A Survey on Churn Analysis in Various Business Domains > VIII. LIMITATIONS AND ISSUES FOR FURTHER RESEARCH
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The statistical model used here is based on statistical inference and hypothesis testing, and survival analysis with hazard methods are used to build churn prediction models.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“By combining the buyer behavior and survival distribution, the CLV can be calculated.and this method is simply referred to as the Pareto/NBD model.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, it is a performance measurement method that focuses on the prediction of churn customers.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Recently, deep learning techniques have emerged as a method of predicting customer churn.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Churn prediction analysis using deep learning algorithms has recently emerged.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Once a graph is built, it searches churning customers through the graph correlation analysis.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Further, the distribution of churn used gamma mixture of exponential, which is also known as the Pareto (of the second kind) distribution.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Apart from this, it seems to be different since the churn model that best interprets the relevant log data is applied.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“In the non-contractual settings, the repeat-buying behavior of customers have been previously expressed through negative binomial distributions (NBD) [151].”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
What the sources say
- Not matchedcites [151]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Churn prediction models using deep learning is a new solution with a good structure for predicting modern churn datasets.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As mentioned earlier in the text, traditional churn prediction algorithms including statistics methods are still actively used today.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The graph theory identifies churn as a mathematical relationship.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the past, when predicting customer churn, researchers used survival analysis or time series analysis using statistics, graph theory, and traditional machine learning algorithms.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The reason why the preferred model for each business field is different is that the types and cycles of log data used for each business are different.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
- Rests on an assumption: The types and cycles of log data used for each business are different.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Machine learning techniques also began to be utilized in customer churn for non-contractual settings.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, deep learning also has many variances and tend to be classified separately from conventional machine learning.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Unlike other modeling techniques, the deep learning model is capable of converting high dimensional sparse log data into low dimensional dense features by embedding time series features.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Deep learning is an intense extension of machine learning with neural network algorithms.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Churn analysis is used in the fields of Internet services and games, insurance, and management.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Loss costs for customer churn are calculated by CAC or CLV.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, because its academic significance has recently grown, it has established itself as a single academic field.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This is likely due to large quantities of customer log data being collected via computers and the churn pre-diction model utilizing the entire set of this acquired data to make churn predictions.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Also the deep learning model can learn customer's behavioral patterns from vast amount of data by layer-wise stacked neurons structure.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“On the other hand, some churn studies have often used a top 10% decline lift performance metric [13] [67].”
§ A Survey on Churn Analysis in Various Business Domains > C. PERFORMANCE EVALUATION
What the sources say
- Not matchedcites [13]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites [67]
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“The Pareto/NBD method has been actively used as a probability model for deriving the CLV until recently [19] [147] [148].”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
What the sources say
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the non-contractual settings, customer churn is not easy to define and trace.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Research on churn prediction usually begins to improve business outcomes.”
§ A Survey on Churn Analysis in Various Business Domains > VII. CONCLUSIONS
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“As another method, the beta-geometric/beta-binomial (BG/BB) model can be used.In this model, the beta-geometric model fits the retention rate and the beta-binomial distribution fits the consumer purchasing behavior [149].”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
What the sources say
- Not checked — no full text of the sourcecites [149] source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Compared to statistical methods, machine learning techniques have robust non-linear relationships between features and can learn heterogeneous effect when given diverse features.”
§ A Survey on Churn Analysis in Various Business Domains > VI. CHURN PREDICTION MODELS A. BUILDING CHURN PREDICTION MODELS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
The paper relies on this without support.
Customer churn behavior is quantitative.
“Customer churn behavior is quantitative.”
The paper relies on this without support.
It is difficult to directly relate customer churn to a decrease in sales.
“However, it is difficult to directly relate customer churn to a decrease in sales.”
The paper relies on this without support.
Communication costs arising from different churn criteria between service personnel in the process of fusing heterogeneous services have been sharply increasing.
“In the industry, communication costs arising from different churn criteria between service personnel in the process of fusing heterogeneous services (e.g., vehicle sharing service/insurance, online music service/department store) have been sharply increasing.”
The paper relies on this without support.
There are many difficulties for researchers to launch new research on churn because of fragmented previous studies.
“However, because of fragmented previous studies, there are many difficulties for researchers to launch new research on churn.”
The paper relies on this without support.
The trend of building churn prediction models is changing, and performance is rapidly improving.
“The trend of building churn prediction models is changing, and performance is rapidly improving.”
The paper relies on this without support.
The CAC cost is the minimum value to operate service makes from a customer with Return on Investing (ROI).
“The company measures the cost of acquiring a customer with the CAC, and that CAC cost is the minimum value to operate service makes from a customer with Return on Investing (ROI).”
The paper relies on this without support.
Pure log data includes all truthful customer information.
“Pure log data includes all truthful customer information.”
The paper relies on this without support.
Service indicators are generally sparse and have many outliers, and the data distribution is skewed to one side.
“This is because service indicators are generally sparse and have many outliers, and the data distribution is skewed to one side.”
The paper relies on this without support.
The distribution of service data is generally skewed to one side.
“The distribution of service data is generally skewed to one side.”
The paper relies on this without support.
In a stable service, the number of churned customers generally account for a small proportion compared to the number of retained customers.
“In a stable service, the number of churned customers generally account for a small proportion compared to the number of retained customers.”
The paper relies on this without support.
The types and cycles of log data used for each business are different.
“The reason why the preferred model for each business field is different is that the types and cycles of log data used for each business are different.”
The paper relies on this without support.
Most churn prediction models are related to customer relation management.
“Most churn prediction models are related to customer relation management.”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
The paper says there are 12 business fields but lists 14
MinorThe text states that churn prediction was performed in 12 business fields, while Table 2 lists 14 distinct business fields.
“There are 12 business fields that performed churn prediction.”
“| Energy 1 | | | | | Finance 10 | 2 | | 1 | | Telecommunications 26 | 3 | 3 | 1 | | Game 16 | 7 | | 2 | | Marketing 1 | | | | | Psychology 1 | | | | | Human Resources 1 | | | | | Insurance 3 | | | 1 | | Commerce 1 | | | | | Internet Commerce 1 | | | | | Internet Service 1 | 1 | | 1 | | Music Streaming Service 1 | | | | | Newspapers 4 | | | | | Retails 2 | | | |”
Citations
Cites
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126
Zero defections: quality comes to services.
Reichheld, F. F., & Sasser, W. E. (1990) · PubMed · Cited by 5,373
Witten, I. H., & Frank, E. (2002) · ACM SIGMOD Record · doi:10.1145/507338.507355 · Cited by 5,176
Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)
Breiman, L. (2001) · Statistical Science · doi:10.1214/ss/1009213726 · Cited by 4,340 · cited 1×
“(2019) and Bzdok, D., Altman, N. and Krzywinski, M. (2018) divided statistics and machine learning [60]–[62].”
BackgroundStatistics versus machine learning
Bzdok, D., Altman, N., & Krzywinski, M. (2018) · Nature Methods · doi:10.1038/nmeth.4642 · Cited by 1,508 · cited 1×
“(2019) and Bzdok, D., Altman, N. and Krzywinski, M. (2018) divided statistics and machine learning [60]–[62].”
Haughey, J. C. (2001) · Cited by 1,410
Reinartz, W. J., & Kumar, V. (2000) · Journal of Marketing · doi:10.1509/jmkg.64.4.17.18077 · Cited by 1,364 · cited 1×
“(2009) used the approach of multiplying individual cashflows for entire product to calculate the CLV in the retail service field [38], [146].”
MethodNgai, E. W. T., Xiu, L., & Chau, D. (2008) · Expert Systems with Applications · doi:10.1016/j.eswa.2008.02.021 · Cited by 1,267 · cited 1×
“The analytical CRM is focused on developing databases and resources containing customer characteristics and attitudes [24], [25], [30].”
BackgroundBalancing Acquisition and Retention Resources to Maximize Customer Profitability
Reinartz, W., Thomas, J. S., & Kumar, V. (2004) · Journal of Marketing · doi:10.1509/jmkg.69.1.63.55511 · Cited by 750 · cited 1×
“(2005) have shown that, for long-term business operations, putting efforts to increase the retention rate of all customers in terms of CRM is less efficient than putting efforts on a small number of targeted customer acquisition activities [22].”
BackgroundGerpott, T. J., Rams, W., & Schindler, A. (2001) · Telecommunications Policy · doi:10.1016/s0308-5961(00)00097-5 · Cited by 741
Flagged first, then by citations
15 of the 157 references couldn’t be matched to a known paper.
Research works printed but not linked: 10
- komenar, 1996, Electronic Market
- nielsen, 2001, Major study to track store switching, Retail World
- almana, 2014, A survey on data mining techniques in customer churn analysis for telecom industry, Int J Eng Res Appl, 4, 165
- 2020, Investopedia
- lewis-evans, 2012, Finding out what they think: A rough primer to user research, Part 2, Gamasutra
- umayaparvathi, 2017, Automated feature selection and churn prediction using deep learning models, Int Res J Eng Technol, 4, 1846
- nozhnin, 2012, Predicting churn: When do veterans quit, Gamasutra
- stewart, 2019, The Actual Difference Between Statistics and Machine Learning
- chandar, 2006, Modeling churn behavior of bank customers using predictive data mining techniques, Proc Nat Conf Soft Comput Techn Eng Appl (SCT), 24
- nath, 2003, Customer churn analysis in the wireless industry: A data mining approach, Proc Annu Meet Decis Sci Inst, 561, 505
Cited by
Sorted by citations
Manzoor, A., Qureshi, M. A., Kidney, E., & Longo, L. (2024) · IEEE Access · doi:10.1109/access.2024.3402092 · Cited by 151
Imani, M., Joudaki, M., Beikmohammadi, A., & Arabnia, H. R. (2025) · Machine Learning and Knowledge Extraction · doi:10.3390/make7030105 · Cited by 70
“…churn rates leading to substantial revenue losses, businesses in subscription-based services, telecommunications [1,7], retail [8], banking [9], education [10], healthcare [11], Insurance [12], and other sectors increasingly rely on data-driven approaches to enhance customer retention strategies.”
Ensemble Methods in Customer Churn Prediction: A Comparative Analysis of the State-of-the-Art
Bogaert, M., & Delaere, L. (2023) · Mathematics · doi:10.3390/math11051137 · Cited by 59
“Because of the significant financial implications of correctly predicting customer churn [1,2], customer churn prediction (CCP) models have become utterly important in customer relationship management (CRM) to identify the customers who are most likely to terminate their relationship [3].”
BackgroundMethodMachine learning based customer churn prediction in home appliance rental business
Suh, Y. (2023) · Journal Of Big Data · doi:10.1186/s40537-023-00721-8 · Cited by 60
“Currently, as the need to predict and prevent customer churn in various domains is increasing, many data-mining and machine-learning technologies are being used for this purpose [41].”
BackgroundFair evaluation of classifier predictive performance based on binary confusion matrix
Vanacore, A., Pellegrino, M. S., & Ciardiello, A. (2022) · Computational Statistics · doi:10.1007/s00180-022-01301-9 · Cited by 51
“…as in medical field for disease diagnosis, in industrial field for fault diagnosis or anomaly detection, and in fields of customer service and marketing for churn prediction (Ahn et al. 2020; Jo and Japkowicz 2004; Galar et al. 2011; Chawla et al. 2002; Dashtipour et al. 2016; Tang et al. 2015).”
Metadata
- Authors
- Ahn, J., Hwang, J., Kim, D., Choi, H., & Kang, S.
- Venue
- IEEE Access
- Published
- 2020
- Volume
- 8
- Pages
- 220816-220839
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W3112348427
- Semantic Scholar
- c4b810efe7f18ea3735744fb7c8fc768e7bb6e9e
- Cited by
- 108
- References
- 157
- Citations by year
- 2026: 12 · 2025: 18 · 2024: 27 · 2023: 23 · 2022: 19 · 2021: 8 · 2020: 1
- FWCI
- 13.15
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Research Foundation of Korea, Korean government (NRF-2019R1A2C1002525)
- Nexon Korea
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Customer churn and segmentation
- Social Sciences › Business, Management and Accounting › Marketing › Customer Service Quality and Loyalty
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Keywords
- customer churn prediction, feature engineering, prediction model, telecommunications, insurance, online services, business domain
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-12, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-12 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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