Persistence Modeling for Assessing Marketing Strategy Performance

The question of long-run market response lies at the heart of any marketing strategy that tries to create a sustainable competitive advantage for the firm or brand. A key challenge, however, is that only short-run results of marketing actions are readily observable. Persistence modeling addresses the problem of long-run market-response quantification by combining into one measure of “net long-run impact†the chain reaction of consumer response, firm feedback and competitor response that emerges following the initial marketing action. In this paper, we (i) summarize recent marketing-strategic insights that have been accumulated through various persistence modeling applications, (ii) provide an introduction to some of the most frequently used persistence modeling techniques, and (iii) identify some other strategic research questions where persistence modeling may prove to be particularly valuable.long-run effectiveness;marketing strategy;time-series analysis

Veranderende datasets binnen de marketing. puur zegen of ook bron van frustratie?

De voorbije jaren heeft zich een ware explosie voorgedaan aan modelmatige marketing toepassingen. Eén van de voornaamste drijfveren van die evolutie is de toename in de kwaliteit en kwantiteit van marketing data. Aan de hand van drie toepassingen, i.c. het meten van de effectiviteit van prijspromoties, de evolutie in merkentrouw, en de diffusie van technologische innovaties in een globale context, wordt aangetoond hoe grotere data bases een bijdrage hebben geleverd tot het verwerven van nieuwe of verbeterde marketing inzichten. Vervolgens wordt echter aangetoond dat die evolutie naar steeds grotere en meer gedetailleerde data sets niet steeds een pure zegen hoeft te zijn, maar ook een mogelijke bron van frustraties kan worden. Er wordt ingegaan op de moeilijker communicatie tussen onderzoekers onderling, alsook op de veranderende communicatie met zowel studenten als marketing beslissingsnemers.

Veranderende Datasets Binnen de Marketing: Puur Zegen of Ook een Bron van Frustratie?

Rede in verkorte vorm uitgesproken bij de openbare aanvaarding van het ambt van hoogleraar Bedrijfskunde, in het bijzonder Marketing Models aan de Faculteit Bedrijfskunde van de Erasmus Universiteit Rotterdam op 7 maart 200

On The Predictive Content Of Production Surveys: A Pan-European Study

For over forty years, Business Tendency Surveys have been collected in multiple member states of the European Union. Previous research has studied the predictive accuracy of the expectation variables included in those surveys through bivariate, within-country, Granger-causality tests, which has resulted in mixed conclusions. We extend previous research in various ways, as we (i) explicitly allow for cross-country influences, and (ii) do so using both bivariate and multivariate Granger-causality tests. Specifically, the multivariate El-Himdi and Roy test is adapted to jointly test the forecasting value of multiple production expectation series, to assess whether part of this joint effect is indeed due to cross-country influences, and to determine which countries' expectation series have most "clout" in predicting the production levels in the other member countries, or have higher "receptivity", in that their production levels are Granger-caused by the other countries' expectations.business surveys;cross-correlations;granger causality;production expectations

Time-Series Models in Marketing

Marketing data appear in a variety of forms. An often-seen form is time-series data, like sales per month, prices over the last few years, market shares per week. Time-series data can be summarized in time-series models. In this chapter we review a few of these, focusing in particular on domains that have received considerable attention in the marketing literature. These are (1) the use of persistence modelling and (2) the use of state space models.Marketing;Persistence;State Space;Time Series