Essays about: "Customer Retention"

Showing result 1 - 5 of 109 essays containing the words Customer Retention.

1. 1. "How can tech startups enhance their customer retention and acquisition

   University essay from Högskolan i Gävle/Avdelningen för ekonomi

   Author : Danut Avram; Oluwadamilola Olaitan; [2023]
   Keywords : Customer retention; Customer acquisition; Social media marketing; User engagement; Brand awareness; Tech startups; Customer relationship management CRM ; Trust; Targeted advertisement.;

   Abstract : This  research  emphasizes  the role  of  social  media  in  customer  acquisition  retention.Furthermore, it investigates insights that have the potential to benefit tech startups inshaping  their  strategies  and  effectively  allocating  resources  to  achieve  consistentcommunication with their customer base. READ MORE

3. 2. Brand Loyalty in the Context of Digital Food Retail : Understanding customer behaviour of meal kit delivery services towards brand loyalty: a focus on HelloFresh

   University essay from

   Author : Yiming Yuan; Ziying Lai; [2023]
   Keywords : ;

   Abstract : Abstract Background: Despite an increase in popularity, the meal kit delivery service is facing the challenge of high cancellations and difficulty with customer retention. As it is a comparatively novel concept in the context of digital food retail, more scholarly research should be conducted. READ MORE

4. 3. Predicting user churn using temporal information : Early detection of churning users with machine learning using log-level data from a MedTech application

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Love Marcus; [2023]
   Keywords : User churn; Customer attrition; Artificial neural networks; Log-level analysis; Random forests; Decision trees; Användarbortfall; Kundbortfall; Artificiella neurala nätverk; logganalys; Slumpskogar; Beslutsträd;

   Abstract : User retention is a critical aspect of any business or service. Churn is the continuous loss of active users. A low churn rate enables companies to focus more resources on providing better services in contrast to recruiting new users. READ MORE

5. 4. Customer churn prediction in a slow fashion e-commerce context : An analysis of the effect of static data in customer churn prediction

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Luca Colasanti; [2023]
   Keywords : Survival Analysis; Time To Event prediction; Churn retention; Machine Learning; Deep Learning; Customer Clustering; E-commerce; Analisi di sopravvivenza; Previsione del tempo a evento; Ritenzione dall’abbandono dei clienti; Apprendimento automatico; Apprendimento profondo; Segmentazione della clientela; Commercio elettronico; Överlevnadsanalys; Tid till händelseförutsägelse; Churn Prediction; Maskininlärning; Djuplärning; Kundkluster; E-handel;

   Abstract : Survival analysis is a subfield of statistics where the goal is to analyse and model the data where the outcome is the time until the occurrence of an event of interest. Because of the intrinsic temporal nature of the analysis, the employment of more recently developed sequential models (Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM)) has been paired with the use of dynamic temporal features, in contrast with the past reliance on static ones. READ MORE

6. 5. A Predictive Analysis of Customer Churn

   University essay from KTH/Matematisk statistik

   Author : Olivia Eskils; Anna Backman; [2023]
   Keywords : Churn prediction; CRM; optimization; applied mathematics; machine learning; gradient boosting; random forest; logistic regression; insurance industry; Kundbortfall; CRM; optimering; tillämpad matematik; maskininlärning; gradient boosting; random forest; logistisk regression; försäkringsbranschen;

   Abstract : Churn refers to the discontinuation of a contract; consequently, customer churn occurs when existing customers stop being customers. Predicting customer churn is a challenging task in customer retention, but with the advancements made in the field of artificial intelligence and machine learning, the feasibility to predict customer churn has increased. READ MORE