An important problem in marketing is understanding the impact of various marketing efforts on sales and revenue. If specific measures have not been taken before hand to distinguish responders across the various marketing initiatives, it becomes increasingly difficult to assess the effectiveness of investment across individual marketing channels. We present State Space model to estimate the individual channel effects using aggregate sales or response data across all channels. The proposed framework allows for varying carry over effects across marketing channels. Also, the proposed framework allows for differing rates of decay across marketing channels. We demonstrate its use when data on sales due to individual marketing channels is not available and only aggregated sales data are available. The proposed State Space modeling approach offers the advantage of: (1) allowing for varying rates of decay across marketing channels, and (2) allowing for a natural way of modeling time series dynamics. The approach also opens the way for more comprehensive marketing-mix optimization by allowing varying rates of decay.

营销中的一个重要问题是了解各种营销工作对销售和收入的影响。如果事先没有采取具体措施来区分各种营销计划中的响应者，那么评估各个营销渠道的投资有效性就变得越来越困难。我们提出状态空间模型，以使用跨所有渠道的总销售额或响应数据来估算各个渠道的影响。提议的框架允许跨营销渠道的不同结转效应。而且，提出的框架允许跨营销渠道的不同衰减率。当由于各个营销渠道而产生的销售数据不可用并且仅汇总的销售数据可用时，我们将演示其用法。提议的状态空间建模方法具有以下优点：（1）允许跨营销渠道的衰减率变化，以及（2）允许采用自然方式对时间序列动力学进行建模。通过允许变化的衰减率，该方法还为更全面的营销组合优化开辟了道路。