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Customer loyalty is considered an attitudinal construct reflecting the customer intention to purchase again from a brand (Frank et al. 2012, 2014).
FactGem is able to connect Prosper's customer intention data, with information from an organization's many customer data files, to create a truly single view of the customer — past, present and future.
In a blog post on the subject, he wrote that Google, "has mastered the art of understanding customer intention with a few words that they type in the search box". CRM software collects lots of data, lots of words, about customer behavior but does not conveniently package that data in a way that is immediately available to machine learning.
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It opens the door to a wealth of information about customer intentions, identifying influencers, and locating hidden preferences that are literally gold to marketers.
With the problems in predicting future customer intentions, and the potential lack of clarity in feedback, one has to wonder if there is any point to listening to customers.
The results provide support of the extended TAM model and confirm its robustness in predicting customers' intention of adoption of IB.
We defined "loyalty" as customers' intention to continue doing business with a company, increase their spending, or say good things about it (or refrain from saying bad things).
In this study, we use a response surface model based on a conjoint analysis of service profiles in the context of mobile phone service to examine the dynamics of multi-channel service attributes and their influence on customers' intention to renew a service agreement.
We evaluated the predictive power of three metrics customer satisfaction (CSAT), the Net Promoter Score (NPS), and a new metric we developed, the Customer Effort Score (CES)—on customer loyalty, defined as customers' intention to keep doing business with the company, increase the amount they spend, or spread positive (and not negative) word of mouth.
Therefore, it was not possible to discuss the detailed effects and outcomes on the customers after conversation with owners/managers, e.g., how many people avoided suicide, and the customers' intention to talk and consult with a professional regarding their personal/private problems.
The key objective of this study is to propose and examine a conceptual model that best explains the key factors influencing Jordanian customers' intentions and adoption of Internet banking.
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CEO of Professional Science Editing for Scientists @ prosciediting.com