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Sandrine Macé is a professor at ESCP Europe. She holds a Doctorate in Marketing and is a graduate of ENSAE (School specializing in Statistics) and ESSEC. She is in charge of the Executive Specialized Master’s in Marketing and Communication both at ESCP Europe and at ESA Beirut (Ecole Supérieure des Affaires), a sister school of ESCP Europe. She is also in charge of a Marketing Research seminar for Executives.
She is the author of La politique commerciale du point de vente (Vuibert, 2001) and has made contributions to other publications (Distribution et Prospective : Prospective et Stratégies, Economica 2005 ; Le Marketeur, Pearson 2003 ; Manuel de Gestion, Ellipses 2004 ; Encyclopédie Vente et de distribution, Economica 2001 ; Encyclopédie Vente et de distribution, Economica 2001 ; Etudes et recherches en distribution, Economica 2000). She has worked for Pearson-Village Mondial, on the French adaptation of several books: The Highly Effective Marketing Plan, Smarter Pricing and Blog Marketing.
In 2000, Sandrine Macé was a research fellow at Amos Tuck Business School, Dartmouth College, where she conducted research in sales promotion. She is authorized to supervise doctoral students. Her fields of research are: sales promotion, retailing and quantitative techniques applied to marketing.
Since 2010, she has been the Vice President in charge for Research of the Association Française du Marketing (French Marketing Academy).
The Determinants of Pre- and Post-Promotion Dips in Sales of Frequently Purchased Goods (with Scott A. Neslin, Dartmouth College, Journal of Marketing Research, 2004).
This paper is an empirical study of the relationships between pre- and post-promotion dips in weekly store data and UPC, category, and store trading area customer characteristics. Drawing on recent advances in econometric modeling (Van Heerde, Leeflang, and Wittink 2000), we estimate 39,441 pre- and post-promotion dip elasticities in 83 stores in 10 product categories. We relate these elasticities to 24 characteristics such as UPC price and market share, category budget share and storability, and store trading area demographics. We find that UPC, category, and store trading area customer characteristics all explain significant variation in these behaviors. For example, both pre- and post-promotion dips are stronger for high priced, frequently promoted, mature, high market share UPCs. We find that post-promotion dips are not significant for private labels but more prominent for UPCs with less predictable promotion patterns. We find that stores with trading areas consisting of older customers living in larger ouseholds and owning cars are particularly prone toward post-promotion dips. Our findings potentially deepen our understanding of stockpiling and deceleration and blend two trends in promotion response research – an increased focus on pre- and post-promotion effects, and a greater emphasis on examining cross-sectional differences in promotion response.
The impact and determinants of nine-ending pricing in grocery retailing.
Whatever the channel (e.g., stores, catalogs, websites), the practice of setting prices that end in the digit 9 (e.g., $XX.X9) is common. But why? Perhaps the reasons pertain to the traditional belief that nine-endings boost sales. This research, performed with thousands of fast-moving consumer goods, provides evidence of a strong impact of nine-ending prices. Similar to price reductions ranging from 4.7% to 22.7% in the most responsive cases, retailers can generate an increase in sales between 9.8% and 23.7% simply by setting nine-ending prices, without marking down or diminishing their profit. This research also reveals great variability in the impact of nine-endings on sales, including effects that are substantial, medium, weak, or even negative in some cases. Thus, how can retailers avoid an indiscriminate practice that leads to counterproductive nine-ending pricing policies? There is a compelling need to achieve deeper insight into the effectiveness of nine-endings and their impact on actual sales. This research attempts to fill this important research gap and to determine key success factors that might enable retailers and manufacturers to improve their nine-ending pricing policy. More broadly, this research investigates whether the effectiveness of nine-ending prices varies across items, categories, stores, and store clientele area characteristics.
The empirical analysis uses store-level scanner data from the Dominick’s Finer Food grocery chain database, pertaining to 10 product categories across 83 stores. The numerous empirically supported hypotheses clearly demonstrate that manufacturers and retailers should not practice nine-ending pricing widely and indiscriminately but rather should contemplate the cases with significant impacts. With this perspective, this study helps them select precise conditions (i.e., items, categories, and store profile) in which to set prices with nine-endings to optimize their impact on sales.
Are there specific items that should not be included in the nine-ending pricing practice? The findings reveal that premium brand manufacturers (i.e., brands that have been available for a long time, with high market shares and high prices) should be suspicious of this practice because the impact of nine-endings is weaker for premium brands and can lead to sales losses.
What are the most responsive items and categories to nine-ending practice? Nine-endings seem more effective for increasing the sales of smaller brands (i.e., inexpensive brands, low-market-share brands, and new products) that belong to low-involvement categories (i.e., low-priced and low-budget-share categories).
Should retailers be concerned with overuse of nine-ending prices? The results reveal that the effectiveness of nine-ending prices decreases when a store intensifies its use of the practice. Then, which tactic is most profitable: setting nine-ending prices for most SKUs, even though doing so weakens their effectiveness, or selecting a few SKUs for which responses are greatest to nine-ending prices?
To address this question, a simulation calculates the impact of a store’s nine-ending pricing practice and its variation on category sales. For category sales, the simulation reveals the existence of a threshold for which overuse is counterproductive. For example, category sales are at their maximum when the nine-ending pricing practice pertains to 50% of the SKUs in the oatmeal category and 60% in the refrigerated juices and toilet paper categories.
Finally, should retailers adapt their nine-ending practice policies to the stores and the profile of their potential shoppers? For example, what is the impact on sales when lower-income customers patronize stores, and is there a difference in stores with higher-income clientele? The results reveal that retailers can adapt their nine-ending pricing policies to their trade area, placing greater emphasis on the practice in stores in which the area mixes working women, higher-income households, and less educated people.
The research notes other drivers of nine-ending effects and provides easily applicable results to help marketing practitioners make better pricing decisions.