一种基于视听率数据的广告响应人数预测模型

针对评价广告媒体组合效果时没有有效指标的问题,提出了一种基于视听率数据的广告响应人数预测模型.该模型由接触频次分布子模型和基于接触频次分布的响应人数预测子模型构成.对两个子模型的参数估计方法进行了介绍.采用遗传算法对基于接触频次分布的响应人数预测模型的参数进行了估计.通过某金融机构的实际数据对模型进行了验证.模型预测广告响应人数和实际广告响应人数的比较结果表明,在无决策者经验介入的情况下,提出的模型能够基于易于获取的视听率数据,比较准确地预测广告的响应人数,可以作为评价广告效果的量化指标在实际广告活动中使用.

A Model Based on Audience Rating Data to Predict the Numbers of Audience Responding to an Advertisement

Based on the data of audience rating, a model was developed to predict the number of audience who will respond to an advertisement, thus solving the problem that there are no effective indices to evaluate the efficiency of advertising activities. The model is composed of an exposure frequency distribution submodel and a prediction submodel based on the former one, and both are described for the estimate of their parameters. The genetic algorithm method is introduced to estimate the parameters of the prediction submodel. With the real data of a financial organization taken as example to verify the model developed, comparative results between predicted and actual number of the audience responding to an advertisement showed that the proposed model can offer a relative accurate prediction without the support of deciders' experience if the data of audience rating are easy to acquire. Therefore, the proposed model can be used to provide quantitative evaluation indices in practice at advertising activities.