Early Marketing Matters: A Time-Varying Parameter Approach to Persistence Modeling

Osinga, Ernst C.; Leeflang, Peter S. H.; Wieringa, Jaap E.

doi:10.1509/jmkr.47.1.173

Cited by 60 publications

(43 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Since then, DTCA expenditures have increased faster than expenditures on other marketing instruments in the pharmaceutical industry (IMS Health 2009). Empirical research establishes only moderate short-and long-term sales effects from DTCA (e.g., Berndt et al 1995;Kremer et al 2008;Narayanan, Desiraju, and Chintagunta 2009;Osinga, Leeflang, and Wieringa 2010;Wittink 2002). According to Kremer and colleagues (2008), DTCA elasticities vary across therapeutic classes, with an average of .073.…”

Section: Background On Pharmaceutical Dtcamentioning

confidence: 99%

“…We estimate our model with Kalman filtering, as has been applied previously in marketing contexts by, among others, Naik, Mantrala, and Sawyer (1998), Naik and Raman (2003), and Osinga, Leeflang, and Wieringa (2010) in their efforts to model advertising and promotion effects over time and by Xie and colleagues (1997) To apply this method, we first write our model in statespace form and specify it in terms of observation and transition equations. The transition equations describe how the time-varying parameters evolve over time and link to the endogenous variable using the observation equations (Durbin and Koopman 2001;Naik, Mantrala, and Sawyer 1998).…”

Section: Model Estimationmentioning

confidence: 99%

See 1 more Smart Citation

Why Do Firms Invest in Consumer Advertising with Limited Sales Response? A Shareholder Perspective

Osinga¹,

Leeflang²,

Srinivasan³

et al. 2011

Journal of Marketing

View full text Add to dashboard Cite

Marketing managers increasingly recognize the need to measure and communicate the impact of their actions on shareholder returns. This study focuses on the shareholder value effects of pharmaceutical direct-to-consumer advertising (DTCA) and direct-to-physician (DTP) marketing efforts. Although DTCA has moderate effects on brand sales and market share, companies invest vast amounts of money in it. Relying on Kalman filtering, the authors develop a methodology to assess the effects from DTCA and DTP on three components of shareholder value: stock return, systematic risk, and idiosyncratic risk. Investors value DTCA positively because it leads to higher stock returns and lower systematic risk. Furthermore, DTCA increases idiosyncratic risk, which does not affect investors who maintain well-diversified portfolios. In contrast, DTP marketing has modest positive effects on stock returns and idiosyncratic risk. The outcomes indicate that evaluations of marketing expenditures should include a consideration of the effects of marketing on multiple stakeholders, not just the sales effects on consumers. Recent research has demonstrated that a firm's advertising affects stock returns, beyond the effect of advertising on revenues and profits (e.g., Joshi and Hanssens 2010). Similarly, communicating the added value created by product innovation yields greater firm value effects (e.g., Srinivasan et al. 2009). As McAlister, Srinivasan, and Kim (2007) report, a firm's advertising also lowers its systematic market risk. Consequently, to evaluate marketing expenditures properly and improve marketing resource allocations, models that consider the effects of marketing expenditures on multiple stakeholders, such as customers and investors, are necessary (e.g., Luo 2007). KeywordsIn this study, we examine the influence of advertising expenditures on investors and thus (1) the levels of stock returns and the risk associated with these returns, distinguishing (2) systematic (market risk factor) and (3) idiosyncratic (firm-specific) risks. Our framework also moves beyond the theories and variables used in previous studies to determine whether firms should invest in marketing actions with limited sales response. In doing so, this study offers new contributions over previous research (e.g., Joshi and Hanssens 2010;McAlister, Srinivasan, and Kim 2007). In particular, we simultaneously estimate the effects of marketing on all three components of shareholder value using Kalman filtering. Building on the four-factor model that Carhart (1997) proposes, we develop a dynamic model to relate pharmaceutical direct-to-consumer advertising (DTCA) and direct-to-physician (DTP) marketing expenditures to stock returns and volatilities while controlling for financial performance.Pharmaceutical DTCA is a relatively new, and heavily debated, phenomenon: The Food and Drug Administration (FDA) relaxed regulations on DTCA only in 1997. Recent research suggests limited short-and long-term effects of DTCA on sales, which places pharmaceutical marketers, simil...

show abstract

Section: Background On Pharmaceutical Dtcamentioning

confidence: 99%

Section: Model Estimationmentioning

confidence: 99%

Why Do Firms Invest in Consumer Advertising with Limited Sales Response? A Shareholder Perspective

Osinga¹,

Leeflang²,

Srinivasan³

et al. 2011

Journal of Marketing

View full text Add to dashboard Cite

show abstract

“…US $ 600 millions marketing support within the 3-year period around product launch today. I shall later report on recent studies (Narayanan and Manchanda 2009;Osinga et al 2010) that provide reasons for this high launch investment. To summarize, the marketing investment into a new drug is substantial.…”

Section: Industry Facts On Marketing Spendingmentioning

confidence: 99%

Marketing Spending Models

Fischer

2013

International Series in Quantitative Marketing

View full text Add to dashboard Cite

To the surprise of many, pharmaceutical firms belong to the biggest spenders on marketing. The marketing spend-to-sales ratio may be as high as 30 %. Expenditures in the USA alone were $10.9 billion in 2009. Hence, there is a strong interest in understanding how effectively this industry spends its marketing money.The objective of this chapter is to review and synthesize the literature on marketing spending in the pharmaceutical industry. It reviews recent trends in pharmaceutical marketing. It looks at how marketing managers in the pharmaceutical industry actually arrive at spending decisions. The author further discusses models that describe how pharmaceutical demand responds to marketing expenditures. He summarizes findings on the responsiveness and profitability (ROI) of various spending categories.Another focus of the chapter is on normative applications of marketing spending models. Normative models help finding the right budget across spending categories, customer groups, and products. The discussion covers static and dynamic optimization approaches. The author identifies fields of promising future research from this synthesis of the extant literature. IntroductionThe pharmaceutical industry is one of the largest and most profitable industries From 1995 to 2002, the pharmaceutical industry was the leading industry in the USA in terms of return on sales. Pharmaceutical firms still ranked third, realizing a return on sales of 19.3 % in 200819.3 % in (Lundy 2010. Due to the long, complex, and highly regulated development process, firms needed to invest ca. US $ 1,318 million into a new drug in 2005 (EFPIA 2011). The market success of the new product, however, is uncertain. It depends on several factors, among them the entry order position (e.g., Berndt et al. 1995), perceived drug effectiveness (Venkataraman and Stremersch 2007), etc. As a consequence, marketing becomes crucial in order to maximize revenues over the life cycle of the new product. Since product development, distribution, and pricing are highly regulated across the world, pharmaceutical firms are not as flexible as firms in other industries in using these elements of the marketing mix.

show abstract

“…At the aggregate level, sales response models are widely used (e.g., Kamakura and Kang (2007) and Osinga et al (2010)). Our data set contains the information of individual customers of an online ticket marketplace; therefore, we focus on individual-level analysis and use purchase rate as the response variable.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Inference for Assessing Effects of Email Marketing Campaigns

Liu

2018

Journal of Business & Economic Statistics

View full text Add to dashboard Cite

Email marketing has been an increasingly important tool for today's businesses. In this paper, we propose a counting-process-based Bayesian method for quantifying the effectiveness of email marketing campaigns in conjunction with customer characteristics. Our model explicitly addresses the seasonality of data, accounts for the impact of customer characteristics on their purchasing behavior, and evaluates effects of email offers as well as their interactions with customer characteristics. Using the proposed method, together with a propensity-scorebased unit-matching technique for alleviating potential confounding, we analyze a large email marketing data set of an online ticket marketplace to evaluate the short-and long-term effectiveness of their email campaigns. It is shown that email offers can increase customer purchase rate both immediately and during a longer term. Customers' characteristics such as length of shopping history, purchase recency, average ticket price, average ticket count, and number of genres purchased also affect customers' purchase rate. A strong positive interaction is uncovered between email offer and purchase recency, suggesting that customers who have been inactive recently are more likely to take advantage of promotional offers.

show abstract

Early Marketing Matters: A Time-Varying Parameter Approach to Persistence Modeling

Cited by 60 publications

References 55 publications

Why Do Firms Invest in Consumer Advertising with Limited Sales Response? A Shareholder Perspective

Why Do Firms Invest in Consumer Advertising with Limited Sales Response? A Shareholder Perspective

Marketing Spending Models

Bayesian Inference for Assessing Effects of Email Marketing Campaigns

Contact Info

Product

Resources

About