Modeling the Effectiveness of Hourly Direct-Response Radio Commercials

The authors investigate the impact of direct-response commercials on incoming calls at a national call center. To this end, the authors analyze the data of a fast service for repairs of (parts of) a durable consumption good in Flanders, Belgium. The authors have access to data at the 15 minute interval covering 30 months in which 5172 radio commercials were broadcasted on six radio stations at various times of the day and at with differing commercial lengths. Their model is a two-level model, where the first-level estimates of the short-run and long-run effects are correlated with various aspects of the commercial is the second level. Their main conclusion is that GRPs are the key drivers of the effectiveness of commercials.HF5837;long-run elasticity;advertising response;short-run effects;advertising effectiveness;two-level model

To Aggregate or Not to Aggregate: Should decisions and models have the same frequency?

We examine the situation where hourly data are available to design advertising-response models, whereas managerial decision making can concern hourly, daily or weekly intervals. The key question is how models for hourly data compare to models based on weekly data with respect to forecasting accuracy and with respect to assessing advertising impact. Simulation experiments suggest that the strategy, which entails modeling the least aggregated data and forecasting more aggregate data, yields better forecasts, provided that one has a correct model specification for the higher frequency data. A detailed analysis of three actual data sets confirms this conclusion. A key feature of this confirmation is that aggregation affects data transformation to dampen the variance. The estimated advertising impact is sensitive to the appropriate transformation. Our conclusion is that disaggregated models are preferable also when decision have to be made at lower frequencies

Modeling the Effectiveness of Hourly Direct-Response Radio Commercials

The authors investigate the impact of direct-response commercials on incoming calls at a national call center. To this end, the authors analyze the data of a fast service for repairs of (parts of) a durable consumption good in Flanders, Belgium. The authors have access to data at the 15 minute interval covering 30 months in which 5172 radio commercials were broadcasted on six radio stations at various times of the day and at with differing commercial lengths. Their model is a two-level model, where the first-level estimates of the short-run and long-run effects are correlated with various aspects of the commercial is the second level. Their main conclusion is that GRPs are the key drivers of the effectiveness of commercials

Note--Competitive Bidding with Asymmetric Information Reanalyzed

This note reanalyzes the following problem, formerly treated by Wilson (Wilson, R. B. 1967. Competitive bidding with asymmetric information. Management Sci. 13 (July) 816-820): two parties have to submit bids for an object One of them knows the value with certainty, the other does not. The equilibrium derived differs from Wilson's solution and yields a simple explanation for the case cited by Wilson: the value of the game is essentially zero for the party with incomplete information.games/group decisions: bidding, games/group decisions: gambling

Forecasting time-varying arrivals: Impact of direct response advertising on call center performance

This study investigates manpower planning and the performance of a national call center for scheduling car repairs and responding to road interventions. We model the impact of advertising on the required capacity and develop a forecasting model for incoming calls, where the impact of direct-response advertising is considered. With the estimation results, we forecast the number of incoming calls to the call center. Next, the forecasts are input into the capacity planning simulation module to directly simulate a service process at the highly disaggregated level. This simulation mimics the service level requirements and queue behavior and shows that the call center is operating at a high level of efficiency and performance. We illustrate that advertising may cause a temporary overload of the system and increase the number of abandoned calls, which is suboptimal for call center performance