Spatial models for online retail churn: Evidence from an online grocery delivery service in Madrid

Montiel, Miguel Angel de la Llave; Hernández, Fernando A. López

doi:10.1111/pirs.12552

Cited by 8 publications

(3 citation statements)

References 55 publications

(79 reference statements)

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“…Online grocery is unique in its ability to directly attract shoppers into the store. One study conducted in Europe found that the majority of shoppers for a top online grocer found the retailer through promotions on search engines, social media, and email [120]. However, once in the online grocery platform, studies suggested that promotions may be less common compared to in brick-and-mortar stores.…”

Section: The Online Food Retail Landscapementioning

confidence: 99%

A scoping review of online food retail: Who’s using it, what they are buying, and what tactics are used to promote healthy or unhealthy purchases

Reimold,

Hall,

Rummo

et al. 2024

Preprint

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Online grocery shopping is an increasingly common part of the retail food environment. However, existing reviews have yet to synthesize the large swath of online grocery shopping research. We searched seven databases for studies reporting empirical data on online grocery retailing and shopping. Two reviewers screened search results and extracted information from 117 manuscripts containing 122 studies. Most studies were conducted in North America, Europe, and Asia. Younger, highly educated, and higher-income individuals were most likely to use online grocery and time savings, convenience, and website usability were the most common motivators for use. Common deterrents included the inability to pick perishable items and a lack of trust in the in-store shopper. Barriers included delivery and service fees, difficulty navigating online ordering, and limited availability. Individuals were more likely to purchase bulky/heavy items and less likely to purchase impulse items and perishables like fresh produce. The most common online retail promotion was price discounting. However, shoppers reported that marketing tactics seemed less noticeable online compared to brick-and-mortar stores. Online grocery has gained popularity; nevertheless, barriers may reflect inequities in access. Research is needed to further understand how shopping online influences overall food purchases and how to ensure equitable access.

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Section: The Online Food Retail Landscapementioning

confidence: 99%

A scoping review of online food retail: Who’s using it, what they are buying, and what tactics are used to promote healthy or unhealthy purchases

Reimold,

Hall,

Rummo

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Customer churn is addressed in many industries such as telecommunication [10][11][12][13], peer-to-peer lending market [14], retail industry [15,16], and banking [17,18]. As it is obvious, the telecom industry mostly conducts churn analysis in order to keep the customers in the existing company by analyzing the customer specifications and behaviors.…”

Section: Introductionmentioning

confidence: 99%

The Attitudes of the Telecommunication Customers in the COVID-19 Outbreak: The Effect of the Feature Selection Approach in Churn Analysis

DONAT

USTA

2022

Sakarya University Journal of Science

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Today's rising cutting-edge technology requirements and competitive environment in telecommunication industry has gained a remarkable importance due to the COVID-19 pandemics in terms of high need of information sharing and remote communication necessity. Telecommunication companies conduct significant analyses by highlighting that the customer data is the most valuable information. Besides, they obtain results emphasizing that acquiring new customers is costlier than retaining the existing ones. Therefore, the companies are willing to determine the important customer features in order to understand why they shift to the other telecommunication service providers. Hence, this study aims to conduct a churn analysis by feature selection approach with large volumes of telecommunication customer data in order to present what kind of customer behaviors and qualifications exist. Since there is a huge amount of data in this field, data mining is a vital requirement. The performance outputs were observed, and the features carrying these outputs to the highest value were identified. The data collection and analysis were carried out in mid-2019, and the same data collection and analysis were carried out again at the beginning of 2021, and these before and after results were compared. In addition, a comparison was made with the results obtained by the other churn analysis studies. This paper contributes to the practitioners by presenting the most important customer features in telecom customer churn, and a new approach in performance evaluation have been proposed specific to the telecommunication market with the industry experts’ guidance as a theoretical contribution.

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“…Churn analysis has been carried out in different industries in the academic literature. The most intense studies focus on B2C business models such as telecommunication [2], [4]- [10], financial services [11]- [14], and retail [15]- [17] industries. However, few studies have been conducted considering the B2B business model.…”

Section: Introductionmentioning

confidence: 99%

Using Machine Learning Algorithms to Analyze Customer Churn in the Software as a Service (SaaS) Industry

Çallı

KASIM>

2022

Academic Platform Journal of Engineering and Smart Systems

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Companies must retain their customers and maintain long-term relationships in industries with intense competition. Customer churn analysis is defined in the literature as identifying customers who may leave a company to take appropriate marketing precautions. While customer churn research is prevalent in B2C (Business to Customer) business models such as the telecoms and retail sectors, customer churn analysis in B2B (business to business) models is a relatively emerging topic. In this regard, the study carried out a customer churn analysis by considering an ERP (enterprise resource planning) company with a software as a service (SaaS) business model. Different machine learning algorithms analyzed ten features determined by selection methods and expert opinions. According to the analysis results, the random forest algorithm gave the best result. Additionally, it has been observed that the number of products and customer features has a relatively higher weight for the prediction of churner.

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Spatial models for online retail churn: Evidence from an online grocery delivery service in Madrid

Cited by 8 publications

References 55 publications

A scoping review of online food retail: Who’s using it, what they are buying, and what tactics are used to promote healthy or unhealthy purchases

A scoping review of online food retail: Who’s using it, what they are buying, and what tactics are used to promote healthy or unhealthy purchases

The Attitudes of the Telecommunication Customers in the COVID-19 Outbreak: The Effect of the Feature Selection Approach in Churn Analysis

Using Machine Learning Algorithms to Analyze Customer Churn in the Software as a Service (SaaS) Industry

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