Search Results

Customer Lifetime Value (CLTV) prediction is a critical task in business applications, such as customer relationship management (CRM), online marketing, etc. Accurately predicting CLTV is challenging in real-world business scenarios, as the distribution ...

This study analyses the complete trading records of 217,614 mobile stock traders in Korea to test how the buy-till-you-die (BTYD) class of probabilistic models work in predicting mobile transaction patterns. We find that BTYD models show satisfactory ...

We introduce a novel stochastic control model for the problem of a service firm interacting over time with one of its customers who probabilistically churns depending on the customer’s satisfaction. The firm has two service modes available, and they ...

Customer lifetime value (CLV) is the revenue expected from a customer over a given time period. CLV customer segmentation is used in marketing, resource management and business strategy. Practically, it is customer segmentation rather than revenue, ...

Managing player engagement is an important problem in the video game industry, as many games generate revenue via subscription models and microtransactions. We consider a class of online video games whereby players are repeatedly matched by the game to ...

Product experiments today need a long term view of impact to make shipping decisions truly effective. Here we will discuss the challenges in the traditional metrics used in experiment analysis and how long term forecast metrics enable better decisions.

...

Context matters when modeling customer purchases and attrition in noncontractual settings.

Customer base analysis of noncontractual businesses builds on modeling purchases and latent attrition. With the Pareto/NBD model, this has become a straightforward exercise. However, this simplicity comes at a price. Customer-level predictions often lack ...

We show that a simple, nontiered loyalty program can substantially increase customer lifetime value and that most of this benefit comes from increasing customer retention.

We study the impact of launching a non-tiered customer loyalty program on consumers’ spending per visit, frequency of visits and attrition rates, and overall customer value. We demonstrate these results both through descriptive difference-in-difference ...

Mobile games make up the largest segment of the games industry, in terms of revenue as well as players. Hundreds of thousands of games are available with most being free to download and play. In freemium games, revenue is predominantly generated by ...

The¹ free-to-play model in the online gaming industry is based on providing an online game at no charge on either mobile devices or on a PC. Monetization would occur with virtual items which players may purchase during the game. It has been demonstrated ...

We describe the Customer LifeTime Value (CLTV) prediction system deployed at ASOS.com, a global online fashion retailer. CLTV prediction is an important problem in e-commerce where an accurate estimate of future value allows retailers to effectively ...

We introduce a new methodology that can capture and explain differences across a series of cohorts of new customers in a repeat-transaction setting. More specifically, this new framework, which we call a vector changepoint model, exploits the underlying ...

Accurate predictions of a customer’s activity status and future purchase propensities are crucial for managing customer relationships. This article extends the recency–frequency paradigm of customer-base analysis by integrating regularity in interpurchase ...

A comprehensive understanding of individual customer value is crucial to any successful customer relationship management strategy. It is also the key to building products for long-term value returns. Modeling customer lifetime value (CLTV) can be ...

Service research has emphasized triad relationships between a firm, employees and customers. To coordinate these stakeholders effectively, it is highly important to understand what service activities are beneficial to all or some of these stakeholders. ...

Firms are increasingly looking to provide a satisfactory prediction of customer lifetime value CLV, a determining metric to target future profitable customers and to optimize marketing resources. One of the major challenges associated with the ...

This series of discussions presents commentaries and a reply on Zhang et al. [Zhang Y, Bradlow ET, Small DS 2015 Predicting customer value using clumpiness: From RFM to RFMC. Marketing Sci. 342:195-208].

In recent years, customer lifetime value CLV has gained increasing importance in both academia and practice. Although many advanced techniques have been proposed, the recency/frequency/monetary value RFM segmentation framework, and its related ...

This paper discusses the interaction between revenue management and customer relationship management for a firm that operates in a customer retention situation but faces limited capacity. We present a dynamic programming model for how the firm balances ...

The nature of marketing science is changing in a systematic, predictable, and irrevocable way. As information technology enables ubiquitous customer communication and big customer data, the fundamental nature of the firm's connection to the customer ...