Presenting a Model for Creating Customer Loyalty Based on Business Technological Intelligence
محورهای موضوعی : International Journal of Finance, Accounting and Economics StudiesShahram Ajorlou 1 , soheila sardar 2 , mohsen rajabzadeh 3 , Angela Ameli 4
1 - PhD Student of Information Technology Management, North Tehran Branch, Islamic Azad University, Tehran, Iran.
2 - Department of Industrial Management, Faculty of Management, Tehran North Branch, Islamic Azad University, Tehran, Iran.
3 - Management Department, Tarbiat Modares University, Tehran, Iran
4 - Department of Business Management, Faculty of Management, Tehran North Branch, Islamic Azad University, Tehran, Iran.
کلید واژه: Multi-level Marketing, Customer Loyalty, Business Technological Intelligence,
چکیده مقاله :
Purpose: This research delves into the innovative factors that influence customer loyalty within the context of business technological intelligence.
Design/methodology/approach: The study adopts an applied approach, incorporating both quantitative and qualitative methodologies through surveys and data mining. The statistical population comprises 10 senior managers and experts from the Panberes cosmetics and hygiene company, selected via snowball sampling to pinpoint key components and factors. Subsequently, data mining was conducted on the company's data warehouse, encompassing 5,200,000 records from 2011 to 2019. Data analysis was performed using R software, employing data mining and customer clustering techniques.
Findings: The results identified six pivotal indicators for the model: duration of customer cooperation, purchase delay, purchase frequency, purchase amount, profitability, and discounts offered to customers. The research concludes that customer loyalty in multi-level marketing companies is shaped by these six indicators, in conjunction with business intelligence and considering five distinct customer clusters. To elevate customer loyalty and secure a competitive advantage, companies in this domain should prioritize these factors. Furthermore, the study recommends that multi-level marketing companies emphasize the role of discounts and credit sales while also ensuring the satisfaction of their primary customers through enhanced services and support.
Purpose: This research delves into the innovative factors that influence customer loyalty within the context of business technological intelligence.
Design/methodology/approach: The study adopts an applied approach, incorporating both quantitative and qualitative methodologies through surveys and data mining. The statistical population comprises 10 senior managers and experts from the Panberes cosmetics and hygiene company, selected via snowball sampling to pinpoint key components and factors. Subsequently, data mining was conducted on the company's data warehouse, encompassing 5,200,000 records from 2011 to 2019. Data analysis was performed using R software, employing data mining and customer clustering techniques.
Findings: The results identified six pivotal indicators for the model: duration of customer cooperation, purchase delay, purchase frequency, purchase amount, profitability, and discounts offered to customers. The research concludes that customer loyalty in multi-level marketing companies is shaped by these six indicators, in conjunction with business intelligence and considering five distinct customer clusters. To elevate customer loyalty and secure a competitive advantage, companies in this domain should prioritize these factors. Furthermore, the study recommends that multi-level marketing companies emphasize the role of discounts and credit sales while also ensuring the satisfaction of their primary customers through enhanced services and support.
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