Imperial College London


Business School

Associate Professor of Marketing



g.yildirim CV




Business School BuildingSouth Kensington Campus





Publication Type

12 results found

Valenti A, Srinivasan S, Yildirim G, Pauwels Ket al., 2023, Direct mail to prospects and email to current customers? Modeling and field-testing multichannel marketing, Journal of the Academy of Marketing Science, ISSN: 0092-0703

Multichannel retailers need to understand how to allocate marketing budgets to customer segments and online and offline sales channels. We propose an integrated methodological approach to assess how email and direct mail effectiveness vary by channel and customer value segment. We apply this approach to an international beauty retailer in six countries and to an apparel retailer in the United States. We estimate multi-equation hierarchical linear models and find that sales responsiveness to email and direct mail varies by customer value segment. Specifically, direct mail drives customer acquisition in the offline channel, while email drives sales for both online and offline channels for current customer segments. A randomized field experiment with the beauty retailer provides causal support for the findings. The proposed reallocation of marketing resources would yield a revenue lift of 13.5% for the beauty retailer and 9.3% for the apparel retailer, compared with the 6.5% actual increase in the field experiment.

Journal article

Yildirim G, Kübler R, 2023, Applied Marketing Analytics Using R, Publisher: SAGE Publications Limited, ISBN: 9781529613421

This book is essential reading for advanced level marketing students and marketing practitioners who want to become cutting-edge marketers.


Valenti A, Yildirim G, Srinivasan S, Vanhuele M, Pauwels Ket al., 2023, Advertising’s sequence of effects on consumer mindset and sales: A comparison across brands and product categories, International Journal of Research in Marketing, Vol: 40, Pages: 435-454, ISSN: 0167-8116

Advertising has the power to influence how consumers experience, think, and feel about brands, but the sequence of these mindset effects may differ by brand and category. This paper analyzes how the mindset factors of cognition, affect, and experience mediate advertising effects on sales, using data from 178 fast-moving consumer good brands in 18 categories over seven years. The authors compare the models proposed in the literature and conclude that the concept of sequentiality in advertising effects holds up well. Importantly, the sequence varies across brands, with the affect → cognition → experience (ACE) sequence being the most common. Brand differentiation and the hedonic versus utilitarian nature of the product category moderate the incidence of the ACE sequence: this sequence is even more likely for utilitarian products and less differentiated brands. For managers, the results show that the last mindset factor in the sequence is the most important in driving sales, with cognition being most responsive to advertising among the mindset factors. Moreover, in utilitarian categories, highly differentiated brands can expect about seven times higher advertising responsiveness of affect than less differentiated brands.

Journal article

Wanxin W, Yildirim G, 2021, Applied Time-Series Analysis in Marketing, Handbook of Market Research, Editors: Homburg, Klarmann, Vomberg, Publisher: Springer

Time-series models constitute a core component of marketing research and are applied to solve a wide spectrum of marketing problems. This chapter covers traditional and modern time-series models with applications in extant marketing research. We first introduce basic concepts and diagnostics including stationarity test (the augmented Dicky-Fuller test of unit roots), and autocorrelation plots via autocorrelation function (ACF) and partial autocorrelation function (PACF). We then discuss single-equation time-series models such as autoregressive (AR), moving average (MA), and autoregressive moving average (ARMA) models with and without exogenous variables. Multiple-equation dynamic systems including vector autoregressive (VAR) models together with generalized impulse response functions (GIRFs) and generalized forecast error variance decomposition (GFEVD) are then discussed in detail. Other relevant models such as generalized autoregressive conditional heteroskedasticity (GARCH) models are covered. Finally, a case study accompanied by data and R codes is provided to demonstrate detailed estimation steps of key models covered in this chapter.

Book chapter

Kuebler R, Pauwels K, Yildirim G, Fandrich Tet al., 2018, App popularity: where in the world are consumers most sensitive to price and user ratings?, Journal of Marketing, Vol: 82, Pages: 20-44, ISSN: 1547-7185

Many companies compete globally in a world in which user ratings and price are important drivers of performance but whose importance may differ by country. This study builds on the cultural, economic, and structural differences across countries to examine how app popularity reacts to price and ratings, controlling for product characteristics. Estimated across 60 countries, a dynamic panel model with product-specific effects reveals that price sensitivity is higher in countries with higher masculinity and uncertainty avoidance. Ratings valence sensitivity is higher in countries with higher individualism and uncertainty avoidance, while ratings volume sensitivity is higher in countries with higher power distance and uncertainty avoidance and those that are richer and have more income equality. For managers, the authors visualize country groups and calculate how much price should decrease to compensate for a negative review or lack of reviews. For researchers, they highlight the moderators of the volume and valence effects of online ratings, which are becoming ubiquitous in this connected world.

Journal article

Esteban-Bravo M, Vidal-Sanz JM, Yildirim G, 2017, Can retail sales volatility be curbed through marketing actions?, Marketing Science, Vol: 36, Pages: 232-253, ISSN: 1526-548X

For many years, marketing managers have used dynamic sales response models to compute expected sales conditional on the available information. These models fail to recognize that the volatility (conditional variance) of sales can vary over time. Moreover, the covolatilities (conditional covariances) between sales and marketing-mix variables can be time varying. Both concepts introduce a new range of strategic and tactical considerations for product and brand managers. Using a multivariate volatility model, we investigate the covolatility of sales and the marketing mix of a focal brand and competing brands in the market. We also examine carryover effects from a volatility perspective. The methodology is applied to six product categories sold by Dominick’s Finer Foods. The results reveal valuable implications for marketing managers.

Journal article

Pauwels K, Demirci C, Yildirim G, Srinivasan Set al., 2016, The impact of brand familiarity on online and offline media synergy, International Journal of Research in Marketing, Vol: 33, Pages: 739-753, ISSN: 0167-8116

Rooted in the integrated marketing communication framework, this paper conceptualizes how brand familiarity affects online and cross-channel synergies. The empirical analysis uses Bayesian vector autoregressive models to estimate long-term elasticities for four brands. The authors distinguish customer-initiated communication (typically online) from firm-initiated communication (typically offline). Their results indicate that within-online synergy is higher than online–offline synergy for both familiar brands but not for both unfamiliar brands. Managers of unfamiliar brands may obtain substantial synergy from offline marketing spending, even though its direct elasticity pales in comparison with that of online media while managers of familiar brands can generate more synergy by investing in different online media.

Journal article

Esteban-Bravo M, Vidal-Sanz JM, Yildirim G, 2015, Historical impact of technological change on the US mass media advertising expenditure, Technological Forecasting and Social Change, Vol: 100, Pages: 306-316, ISSN: 0040-1625

Historically, the U.S. advertising industry has been experiencing enormous movements as a result of rapid advances in the media technology and the business cycle. In this paper, we study the historical behavior of the U.S. advertising industry, correcting for inflation. We find that the introduction of new media cause structural breaks in the mean growth rates of advertising expenditure for the incumbent media. In addition, we find that random components of media advertising spending follow a long-term equilibrium where the cross-elasticities across newer and older media can show substitution or complementarity patterns depending on the type of audience. We examine the influence of the economic conditions on the aggregated advertising expenditure, and on each media spending. We also measure the impact of the recent takeoff in mobile advertising.

Journal article

Esteban-Bravo M, Vidal-Sanz JM, Yildirim G, 2014, Valuing customer portfolios with endogenous mass and direct marketing interventions using a stochastic dynamic programming decomposition, Marketing Science, Vol: 33, Pages: 621-640, ISSN: 0732-2399

The customer relationship management allocation in marketing budgets is potentially misleading when it uses individual customer lifetime value estimations from historical data. Planned marketing interventions would change the purchasing behavior of different customers, and history-based decisions would thus be suboptimal. To cope with this inherent endogeneity, we model the optimal allocation of the marketing mix by accounting simultaneously for mass interventions and direct marketing interventions for each customer. This is a large stochastic dynamic problem that, in general, is computationally rather intractable as a result of the “curse of dimensionality.” We present an algorithm to derive the optimal marketing policies (how the firm should allocate its marketing resources) and the expected present value of those decisions, which maximize the long-term profitability of firms. This allows the firm to value customers/segments and helps the firm to target those that maximize long-term profitability given the optimal marketing resources allocation. We apply the proposed approach in the context of a kitchen appliance manufacturer. The results identify the most effective marketing policies and the endogenous customer values. It is in this context that we also dynamically identify the most profitable customer and the short- and long-term effects of marketing activities on each customer.

Journal article

Hanssens DM, Pauwels KH, Srinivasan S, Vanhuele M, Yildirim Get al., 2014, Consumer attitude metrics for guiding marketing mix decisions, Marketing Science, Vol: 33, Pages: 534-550, ISSN: 0732-2399

Marketing managers often use consumer attitude metrics such as awareness, consideration, and preference as performance indicators because they represent their brand's health and are readily connected to marketing activity. However, this does not mean that financially focused executives know how such metrics translate into sales performance, which would allow them to make beneficial marketing mix decisions. We propose four criteria—potential, responsiveness, stickiness, and sales conversion—that determine the connection between marketing actions, attitudinal metrics, and sales outcomes.We test our approach with a rich data set of four-weekly marketing actions, attitude metrics, and sales for several consumer brands in four categories over a seven-year period. The results quantify how marketing actions affect sales performance through their differential impact on attitudinal metrics, as captured by our proposed criteria. We find that marketing–attitude and attitude–sales relationships are predominantly stable over time but differ substantially across brands and product categories. We also establish that combining marketing and attitudinal metrics criteria improves the prediction of brand sales performance, often substantially so. Based on these insights, we provide specific recommendations on improving the marketing mix for different brands, and we validate them in a holdout sample. For managers and researchers alike, our criteria offer a verifiable explanation for differences in marketing elasticities and an actionable connection between marketing and financial performance metrics.

Journal article

Erguncu S, Yildirim G, 2014, How consumer mindset response and long-term marketing effectiveness differ in emerging versus mature markets, Brand Management in Emerging Markets: Theories and Practices Theories and Practices, Editors: Cheng Lu Wang, Jiaxun He, Publisher: IGI Global, ISBN: 9781466662438

"This book provides valuable and insightful research as well as empirical studies that allow audiences to develop, implement, and maintain branding strategies"--Provided by publisher.

Book chapter

Pauwels K, Erguncu S, Yildirim G, 2013, Winning hearts, minds and sales: How marketing communication enters the purchase process in emerging and mature markets, International Journal of Research in Marketing, Vol: 30, Pages: 57-68, ISSN: 0167-8116

Journal article

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