Forecasting bloggers´ online behavior based on improved Pareto/NBD model

The bloggers´ online behavior was divided into posting behavior and churn behavior in this paper. Since these two behaviors are similar to customers´ buying behavior and churn behavior respectively in the transaction process, this paper chose to learn from the Pareto/NBD model in the field of customer base analysis to forecast them. Considering that the interaction between bloggers has a great influence on their online behavior, this paper tried to improve the original model to meet this feature by incorporating covariates which can reflect such interaction into the Pareto/NBD model through the Proportional Hazards Model. The empirical study chose both the total amount of comments and page views in each blogger´s space as covariates. The results showed that when setting the total amount of comments as a covariate to the churn behavior, the model´s accuracy was significantly improved. Further analysis also found that the positive impact of the total amount of comments on bloggers´ survival duration has a threshold.