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Sustainability reports. Sustainability performance data. Lifecycle assessment. About Tetra Pak. Who we are. Tetra Pak in Figures. News archive. Our innovation approach. Focus areas. Innovation ecosystem. Zenk SN, Leider J, Pugach O, Pipito AA, Powell LM. Changes in beverage marketing at stores following the Oakland sugar-sweetened beverage tax.

Am J Prev Med. Department of Health and Social Care, GOvernment of the U. Government delays restrictions on multibuy deals and advertising on TV and online. Department of Health and Social Care, Government of U. Bennett R, Zorbas C, Huse O, Peeters A, Cameron AJ, Sacks G, et al. Prevalence of healthy and unhealthy food and beverage price promotions and their potential influence on shopper purchasing behaviour: a systematic review of the literature.

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This study was funded by an Institut de valorisation des données IVADO post-doctoral fellowship. The funding agency is not involved in the study design; collection, analysis and interpretation of data; the writing of the manuscript; or the decision to submit the manuscript.

School of Global and Population Health, Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Suite , McGill College Avenue, Montreal, QC, H3A1G1, Canada. Hiroshi Mamiya, Alexandra M.

Schmidt, Erica E. You can also search for this author in PubMed Google Scholar. HM: Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Project administration, Writing original draft.

AMS and EEMM: Methodology, Visualization, Validation. DLB: Data curation, Data acquisition, Software, Computational resources. All co-authors: manuscript review and editing. The author s read and approved the final manuscript.

Correspondence to Hiroshi Mamiya. The study was approved by the Institutional Review Board, Faculty of Medicine, McGill University IRB study number: AEB. This study used secondary data that are aggregated store-level measurements of consumer purchasing, rather than individual consumer level data.

Therefore, a waiver for informed consent for human subjects was provided by the Institutional Review Board, Faculty of Medicine, McGill University. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4.

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Reprints and permissions. Mamiya, H. et al. Estimating the lagged effect of price discounting: a time-series study on sugar sweetened beverage purchasing in a supermarket. BMC Public Health 22 , Download citation. Received : 13 April Accepted : 29 July Published : 06 August Anyone you share the following link with will be able to read this content:.

Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Skip to main content. Search all BMC articles Search. Download PDF. Research Open access Published: 06 August Estimating the lagged effect of price discounting: a time-series study on sugar sweetened beverage purchasing in a supermarket Hiroshi Mamiya 1 , Alexandra M.

Schmidt 1 , Erica E. Buckeridge 1 Show authors BMC Public Health volume 22 , Article number: Cite this article Accesses 1 Citations Metrics details. Abstract Background Price discount is an unregulated obesogenic environmental risk factor for the purchasing of unhealthy food, including Sugar Sweetened Beverages SSB.

Conclusion Our results indicate that studies that do not account for the lagged effect of promotions may not fully capture the effect of price discounting for some food categories.

Background Sugar Sweetened Beverages SSB represent the largest source of dietary sugar in many nations [ 1 ] and are epidemiologically linked to obesity, overweight and nutrition-related chronic diseases [ 2 ].

Methods Study design This is a retrospective time-series study investigating the association between weekly discounting and sales of five SSB categories in a single supermarket located in Metropolitan Montreal, Canada. Transaction data The transaction records were generated by a large supermarket owned by a major Canadian retail chain the identity of the chain is anonymized and were purchased from a marketing firm, Nielsen [ 25 ].

Exposure The exposure variable is category-specific discounting at each week. Statistical analysis: regression variables to capture lagged association of price discounting and SSB sales A lagged association between time-varying outcome log-transformed sales quantity and exposure discounting is commonly captured by a distributed lag model, which is a regression model that contains multiple time-lagged values of an exposure.

Table 1 Summary of weekly standardized sales quantities of SSBs in the target store between and , in non-log scale of serving quantity Full size table. Table 2 Summary of weekly percent discounting per serving of SSBs in the target store between and Full size table.

Table 3 Summary of weekly baseline non-discount price per serving of SSBs in the target store between and Full size table. Table 4 Comparison of census characteristics between store neighborhood measured at the level of forward sortation area and those of all forward sortation areas in the Census Metropolitan Montreal, Canadian National Household Survey Full size table.

Full size image. Discussion We investigated time-lagged effect of price discounting for five SSB categories for a supermarket located in Metropolitan Montreal, Canada.

Conclusions Overall, our results provide insights into the lagged effect of price discounting on unhealthy beverage purchasing that should be further investigated by other observational studies, as such effect may represent a previously overlooked source of bias in the association of sales and within-store food marketing activities, which is recognized as a potentially important but largely unregulated component of obesogenic food environment.

Abbreviations SSB: Sugar Sweetened Beverages CI: Credible Interval. References Willett WC, Hu FB, Rimm EB, Stampfer MJ. Article Google Scholar Hu FB. Article CAS Google Scholar van Heerde HJ, Neslin SA. Article Google Scholar Hecht AA, Perez CL, Polascek M, Thorndike AN, Franckle RL, Moran AJ.

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Article Google Scholar Mamiya H, Moodie EEM, Ma Y, Buckeridge DL. Article Google Scholar Mamiya H, EEM M, Schmidt AM, Ma Y, Buckeridge DL. Article Google Scholar Delvecchio D, Henard DH, Freling TH.

Article Google Scholar Pound CM, Blair B. Article Google Scholar Larson N, Laska MN, Story M, Neumark-Sztainer D. Article Google Scholar Wagoner KG, Reboussin DM, King JL, Orlan E, Cornacchione Ross J, Sutfin EL.

Article Google Scholar Srinivasan S, Pauwels K, Hanssens DM, Dekimpe MG. Article Google Scholar Slotegraaf RJ, Pauwels K. Article Google Scholar Kantar Worldpanel UK.

Article Google Scholar Almon S. Article Google Scholar West M, Harrison J. Google Scholar Petris G, Petrone S, Campagnoli P. Book Google Scholar Stan Development Team.

Article Google Scholar Hiroshi Mamiya. Article Google Scholar Neslin SA, Schneider Stone LG. Article Google Scholar Jones AC, Kirkpatrick SI, Hammond D. Article Google Scholar Popkin BM, Hawkes C.

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8 Simple Beverage Savings · 1. Milk · 2. Juice · 3. Sports Drinks · 4. Soda · 5. Hot Chocolate · 6. Kool-Aid · 7. Coffee · 8. Water Price Less FoodsFreshopFREE - In Google Play. Install While drinks may be advertised at reduced prices, retailers may not reduce or offer reduced price drinks after p.m.. Retailers may not sell serve or offer

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Reduced-Price Beverages - Reduced Price in Soft Drinks(+) ; Diet Coke Mini Soda Pop Soft Drink, fl oz, 10 Pack Cans. Diet Coke Mini Soda Pop Soft Drink, fl oz, 10 Pack Cans. $ 8 Simple Beverage Savings · 1. Milk · 2. Juice · 3. Sports Drinks · 4. Soda · 5. Hot Chocolate · 6. Kool-Aid · 7. Coffee · 8. Water Price Less FoodsFreshopFREE - In Google Play. Install While drinks may be advertised at reduced prices, retailers may not reduce or offer reduced price drinks after p.m.. Retailers may not sell serve or offer

Manufacturer Advertising and Retail Prices: An Empirical Investigation. Available at SSRN ; Hawkes C. Sales promotions and food consumption. Nutr Rev. Wang EY. The impact of soda taxes on consumer welfare: implications of storability and taste heterogeneity. RAND J Econ. Valizadeh P, Popkin BM, Ng SW.

Distributional changes in U. sugar-sweetened beverage purchases, Download references. The authors take sole responsibility for all data analyses, interpretation, and views expressed in this paper.

Any errors in the manuscript are the sole responsibility of the authors. Mention of trade names, commercial practices, or organizations does not imply endorsement by the authors, nor the institutions where the authors work.

Researcher s own analyses calculated or derived based in part on data from The Nielsen Company US , LLC and marketing databases provided through the Nielsen Datasets at the Kilts Center for Marketing Data Center at The University of Chicago Booth School of Business chicagobooth. Nielsen is not responsible for, had no role in, and was not involved in analyzing and preparing the results reported herein.

Further, the conclusions drawn from the Nielsen data are those of the researchers and do not reflect the views of Nielsen. Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, , USA.

School of Economics, LeBow College of Business, Drexel University, Philadelphia, PA, , USA. Department of Health Management and Policy, Dornsife School of Public Health, Drexel University, Philadelphia, PA, , USA. You can also search for this author in PubMed Google Scholar.

Zhong and A. Auchincloss conceived and designed the study. Auchincloss, M. Stehr, and B. Langellier supervised the study. Zhong performed all analyses and wrote the first draft. All authors contributed to the interpretation of the results.

Langellier edited the manuscript and provided critical review. All authors approved the manuscript. The authors certify that the article contents have not been previously presented elsewhere.

Correspondence to Yichen Zhong. This study analyzed de-identified, publicly available data and thus does not constitute human subjects research as defined at 45 CFR Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Product Module Codes for included sugar-sweetened beverages.

Supplementary Notes S2. Derivations of annual promotion magnitude and frequency at the household level. Table S3. Specification of the regression models. Table S4. Store characteristics, retailer database. Table S5.

Sensitivity analysis - association between household annual price promotion and per capita purchase. Results using alternate definition of weekly price promotion magnitude experienced by the household — average promotion magnitude among stores they shopped in , instead of the largest promotion among the stores in the main analysis.

Table S6. Baseline household characteristics for households who purchased any sugar-sweetened beverages during the study period, by annual per capita purchase. Sample Selection. Sensitivity analysis. Open Access This article is licensed under a Creative Commons Attribution 4.

The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

Reprints and permissions. Zhong, Y. et al. Are price discounts on sugar-sweetened beverages SSB linked to household SSB purchases? Nutr J 20 , 29 Download citation.

Received : 09 December Accepted : 15 February Published : 14 March Anyone you share the following link with will be able to read this content:.

Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Skip to main content. Search all BMC articles Search. Download PDF. Download ePub. Research Open access Published: 14 March Are price discounts on sugar-sweetened beverages SSB linked to household SSB purchases?

Auchincloss 1 , Mark F. Langellier 3 Show authors Nutrition Journal volume 20 , Article number: 29 Cite this article Accesses 3 Citations 3 Altmetric Metrics details.

This article has been updated. Abstract Background Price promotions on sugar-sweetened beverages SSBs are commonly used by retailers to provide economic incentives for purchasing.

Methods This cross-sectional study linked SSB consumption data from a U. Conclusions More frequent and deeper price promotion was associated with higher annual per capita SSB purchases. Background Decreasing the consumption of sugar-sweetened beverages SSB in the population can reduce the burden of obesity, type 2 diabetes, hypertension, cardiovascular diseases and other health conditions [ 1 , 2 ].

Methods This is a cross-sectional study using data from the Nielsen Consumer Panel Database Household Panel and the Nielsen Retail Scanner Database Retailer Data. Household panel data The Household Panel data contains longitudinal household purchasing data from a large nationally representative household sample [ 21 ].

Retailer data The Retailer Data contains weekly transaction data from approximately 35, individual stores from about 90 retail chains in designated marketing areas throughout the US [ 23 ]. Study sample The Household Panel data for each shopping trip were linked with the Retailer Data by common retailer identification codes for each store.

Exposure definition Two variables, annual promotion magnitude and annual promotion frequency , were used to approximate the level of SSB price promotion in stores where each household shopped during the year details in Supplement S2.

Statistical analysis Due to the skewness of the annual per capita purchase, descriptive tables present medians and 25th—75th percentiles and the variable was log-transformed in regression analyses.

Results The household characteristics are summarized by annual per capita purchase quartile in Table 1. Table 1 Baseline household characteristics by annual per capita purchase of sugar-sweetened beverages Full size table.

Table 2 Summary of annual per capita purchase of sugar-sweetened beverages Full size table. Table 3 Summary of annual price promotion experienced by households in the sample, by household characteristics and region Full size table. Table 4 Association between sugar sweetened beverages annual price promotion and per capita purchase a Full size table.

Conclusions More frequent and deeper price promotion on SSBs was associated with higher household annual per capita purchase of SSBs.

Availability of data and materials The data that support the findings of this study are available from the Nielsen Company US , LLC but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available.

Change history 12 May Alignment of "Household size" in Table 3 was corrected. Abbreviations SSB: Sugar-sweetened beverages UK: United Kingdom Household Panel: Nielsen Consumer Panel Database Retailer Data: Nielsen Retail Scanner Database UPC: Universal Product Code.

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Article Google Scholar Huth PJ, Fulgoni VL, Keast DR, Park K, Auestad N. According to a Nielsen study , U. bars and restaurants generate This surprising statistic reveals just how powerful it can be in boosting traffic during slow periods.

But, it can also be a recipe for long-term success. Instead of thinking of happy hour as a one-off event, consider it as an audition for your restaurant.

These customers get a small taste of what your restaurant has to offer. A way to ensure your new guests turn into loyal regulars is to offer a tightly-curated version of your regular food and drink menu.

Generally, happy hour is not some mysterious affair that needs to be shrouded in secrecy — unless you run a speakeasy! On the contrary, this time is seen as a social event that can generate a lot of buzz for your business. Using social media, table signs, and even word-of-mouth marketing , you can build brand awareness by promoting your happy hour drinks and food specials.

But actually pulling off the perfect happy hour is a little more complicated than it might seem. As the National Restaurant Association found, customers see happy hour as much more than an opportunity to grab half-priced margaritas. By looking at POS reports and analytics, you can figure out what items sell well at different times of day.

You can then create a happy hour special around popular, high-margin options. For instance, your Sales by Menu Item report might reveal that your clientele is largely business people who prefer wine over beer and cocktails.

With this information, you can then tailor your promotions to this audience by offering discounts on wine later in the day.

Traditionally, these promotions take place during that sweet lull between the end of the workday and the beginning of the dinner rush. But while the post-work happy hour is classic, virtually any hour from could be a happy hour with a little bit of planning.

For instance, late-night happy hours have become a popular way for many bars and restaurants to bring in a younger crowd. In other words, half-priced cocktails at 10 p. could bring in some younger customers and their friends.

This means you need to go beyond a curated drink menu to ensure you attract a crowd. As you test out different happy hour menus, remember to keep an eye on check sizes. Paying attention to this important metric will help you understand the popularity of each dish, how much customers are ordering, and the impact on your bottom line.

If your promotion only focuses on alcoholic drinks, you could be missing out on a huge part of the market. The Koyck lag variables were added to a linear time-series regression, dynamic linear model [ 30 , 31 ].

The details of the model, including the intercept and the lag coefficients, are provided in Appendix S 3. We accounted for seasonal trends of sales by adding the sine- and cosine-transformed harmonic wave of a week variable as detailed in Appendix S 3. Covariates were weekly varying variables that are likely to temporally correlate with price discounting and sales.

These included non-discounting promotion: weekly-varying display promotion and flyers, which often co-occur with price discounting although not always and are associated with higher sales [ 3 ]. Display promotion is temporarily placement of items into prominent location of stores such as store front.

We calculated the value of these variables at the level of SSB category at each week by aggregating binary promotion status across items.

Specifically, display promotion was coded as 1 if an item was temporarily placed at any one of prominent retail locations from the original shelf space, such as the end of aisle, entrance to store, or by the cashier. Flyer promotion was coded as 1 if an item was listed in flyer, and 0 otherwise.

Additionally, an indicator variable for whether the week contained national and provincial statutory holidays was added. Other covariates were regular baseline price of each beverage categories, mean daytime temperature in each week, and the lagged value of sales itself autoregressive of order 1.

We fitted a separate model for each of the five food categories independently under the Bayesian framework. We therefore specified prior distributions for regression parameters Appendix S 3. We used the Stan software, which uses Hamiltonian Monte Carlo methods and accessed through the Rstan package in R software [ 32 ].

Model selection, specifically selecting a subset of variables from the covariates described above was guided by the value of the Watanabe-Akaike Information Criterion WAIC indicator of model fit [ 33 ]. As sales of many food categories are expected to have seasonal trends a priori, we did not perform any selection of the seasonal terms and thus they were retained in all models.

A lower WAIC value indicates a better-fitting model. Codes are publicly available in an online repository [ 34 ]. The latter specification implies that, rather than assuming monotonic decay seen in Supplementary Figs. S 3 , a sharp reduction of sales below pre-discounting period immediately after discounting [ 3 ].

Theoretical explanations for the post-promotion dip are provided elsewhere [ 3 , 35 , 36 ]. The study was approved by the Institutional Review Board, Faculty of Medicine, McGill University IRB approval : AEB , which did not require a written or verbal consent from human subjects, as the study used aggregated store-level secondary data.

All methods followed the institutional guidelines and regulations. However, these two categories, along with coffee and teas and potentially drinkable yogurt, exhibited a mildly decreasing trend during the study period Supplementary Fig. S 4 relative to that of sports and energy drink, consistent with the trends between and in Canada [ 37 ].

The sales of sports and energy drinks exhibited strong seasonal cyclic patterns in this store but did not show the prominent increase in Canada and worldwide in the same time period and reported elsewhere [ 37 , 38 ]. Discounting of soda, fruit drinks, energy and sports drinks, and sweetened coffees and teas appears to have modestly increased trends over time Supplementary Fig.

S 5 relative to that of drinkable yogurt. Average percent discounting over the study period was highest for soda and lowest for yogurt Table 2. Mean and median regular non-discounting price per serving were the highest for sweetened drinkable yogurt followed by sports and energy drinks, and the remaining 3 categories had far lower baseline prices Table 3.

The store neighborhood, as defined by Forward Sortation Area first 3 digits of Canadian postal codes in which the store was located had comparable census characteristics to the larger Canadian Census Metropolitan Area of Montreal consisting of Forward Sortation Areas Table 4 , as measured by the Canadian National Household Survey [ 39 ].

However, the store neighbourhood had a notably larger proportion of recent immigrants. The summary of the time-varying intercept for each of the SSB categories shows its temporal path capturing the local fluctuations and overall declining trends of the SSB sales, as seen in Supplementary Fig.

S 6 a-e. Inspection of autocorrelation plots of residuals suggests little serial correlation Supplementary Fig. The final set of covariates included the holiday indicator for all SSB categories, in addition to display promotion and regular non-discount price for some SSB categories Supplementary Table S 1.

As noted above, all models included sine- and cosine-transformed harmonic wave of a week as covariates with no selection performed on these time-related seasonal variables.

The estimated coefficient β indicating the change of sales during the time of discounting is shown in Fig. This immediate effect was highest for drinkable sweetened yogurt and lowest for soda Fig.

Soda beverages show the weakest immediate effects. The estimated immediate effect β for price discounting on the sales of five sugar-sweetened beverage categories. The extent of lagged effect the coefficient λ for each food category is provided in Fig.

The estimated value of λ is close to zero for all SSB categories but somewhat larger for sports and energy drinks. The visual interpretation of the lagged effects in the form of the above mentioned Koyck polynomial function for each SSB category Fig.

These shapes suggest a diminishing effect immediately after the period of discounting i. Posterior summary of the estimated lag coefficient, λ, for price discounting on the sales of five sugar-sweetened beverage categories.

The variable λ represents a unitless quantity, whose value ranges from 0 to 1, with 0 representing the absence of lag. This is the posterior distribution of the difference between exponentiated fitted sales generated by the model containing the lag parameter λ and the exponentiated fitted sales generated by the model with the immediate discounting effect alone i.

We also performed additional analyses applied to sports and energy drink categories separately and to diet soda soda containing artificial sweetener rather than sugar products Supplementary Figs. As in its sugar-sweetened counterpart, diet soda did not show evidence of a lagged effect.

We investigated time-lagged effect of price discounting for five SSB categories for a supermarket located in Metropolitan Montreal, Canada. The results indicate that the association between discounting and sales of sports and energy drinks persisted even after discounting ended.

To the best of our knowledge, the extant public health research estimating the association of price discounting and sales has evaluated only the immediate effect, thus potentially not capturing the total immediate and lag effect price discounting on the sales of some food categories.

There is an increasing number of studies investigating within-store food promotions as a modifiable obesogenic environmental drivers of un healthy food selection and nutrition disparities [ 5 ], and price discounting is likely to have the most influential impact on food purchasing [ 4 , 23 ].

Similar to the exposure to environmental stressors e. The lagged effect on the SSB category of sports and energy drinks may have occurred due to repeated trials induced by discounting among peoples who are previously unexposed to the consumption of these rapidly expanding SSB beverages, thus inducing purchase reinforcement.

Sales and consumption of these beverages, in particular energy drinks, exhibited a steady and global growth during the study period [ 17 ], mainly propelled by aggressive and ubiquitous marketing activities within and outside retail settings, including sponsoring of sports and youth events [ 19 , 41 , 42 ].

While the percent increase of sales due to the lagged effect appears modest relative to the immediate effect, the absolute quantity of sports and energy drinks attributable to the lagged effect is concerning. Aside from their sugar contents, a single serving of energy drinks often reaches the recommended daily dose of caffeine intake among youth [ 43 ] and associated with caffeine-related acute health outcomes including neurological, psychological and often fatal cardiovascular events [ 42 , 44 ].

Possible reasons for the absence of discounting carryover effect in the other SSB categories include rationale planning of shopping activities i. This forward-looking planning may be relevant for categories that are discounted heavily, namely soda, fruit drinks and coffees and teas as seen in the descriptive analysis.

As well, the lower baseline prices of these three categories may have further diminished the lagged effects discounting. It is also possible that the lagged effect is masked by the aggregated measure of sales and discounting by SSB categories in this study.

Thus, the overall category sales might not have increased at post-discounting period. This explanation also applies to the results of the sensitivity analysis: the lack of post-promotion sales dip frequently observed in the disaggregated brand-level analysis [ 35 , 36 ].

While it is reassuring that the lagged effect is absent for the SSB categories such as soda in the store investigated, the presence of such effect for the sales of sports and energy drinks implies potentially unaccounted sales due to lagged effects in previous studies targeting these beverages, including our previous study [ 17 ].

Therefore, performing lag analysis in studies investigating the influence of food marketing exposure is warranted. We remark that, while the analytical approach provided in this study is a flexible form of distributed lag model no need to specify the lag length a priori , there are alternative and readily implementable regression models to capture lagged effects built upon the past two decades of lag analysis on exposure-outcome associations in environmental epidemiology [ 27 , 45 , 46 , 47 ].

Although our study focused on capturing linear exposure-outcome lagged associations between discounting and sales, existing lag models, including our transfer function models, can readily incorporate non-linear exposure-outcome associations as well [ 29 , 47 , 48 ].

These methods are accessible as existing software libraries typically implemented within a frequentist framework obviating the need for complex statistical programming [ 27 , 49 , 50 ].

Our study also highlights the need for consumer behavior individual shopper-level research investigating behavioral explanations for time-lagged purchasing in response to price discounting and potentially other forms of promotions, which are important food environmental exposures and may also modify the effectiveness of policy interventions, such as beverage taxation.

Our findings should be interpreted with several limitations in mind. First, while one of the key contributions of this study is to introduce an exposure lag modeling approach applicable to other populations, the data in this study are not recent — Given that the sales of energy drink are forecasted to grow further [ 51 ], the study motivates further investigation to confirm lagged effects on more recent sales and promotion data.

As well, our findings are based on shopping patterns in a single supermarket. Population-level influence of discounting across varying socio-economic status at the shopper- or store neighborhood-level needs to be estimated based on a regionally representative sample of stores or people.

This would require panel data, which in turn would bring significant increases in the computational complexity, requiring hierarchical analyses of lagged models with spatial correlation across geographical locations of stores, which remains our future research.

As in any observational study, we note the potential for unmeasured confounders of price discounting, such as media advertising or a community or school-based health promotion program that took place near the target store.

We also note that potentially important individual product-level information, such as the size of products e. Future research should investigate the lagged effect of other forms of sales promotions, including couponing, volume discount, display and flyer promotions, which independently and jointly influence selections of energy-dense and nutritionally poor food items [ 3 , 5 ].

Overall, our results provide insights into the lagged effect of price discounting on unhealthy beverage purchasing that should be further investigated by other observational studies, as such effect may represent a previously overlooked source of bias in the association of sales and within-store food marketing activities, which is recognized as a potentially important but largely unregulated component of obesogenic food environment.

The data are available through commercial agreement with the company or through affiliated academic institutions that maintain licence to access to these data for research use. Willett WC, Hu FB, Rimm EB, Stampfer MJ.

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Evidence from a consumer research panel. Coker T, Rumgay H, Whiteside E, Rosenberg G, Vohra J. Paying the price - New evidence on the link between price promotions, purchasing of less healthy food and drink, and overweight and obesity in Great Britain.

Cancer Research UK. Accessed 30 May Watt TL, Beckert W, Smith RD, Cornelsen L. Reducing consumption of unhealthy foods and beverages through banning price promotions: what is the evidence and will it work? Ailawadi KL, Neslin SA. The effect of promotion on consumption: buying more and consuming it faster.

J Mark Res. Backholer K, Sacks G, Cameron AJ. Food and beverage price promotions: an untapped policy target for improving population diets and health. Curr Nutr Rep. Apollonio DE, Glantz SA.

Tobacco industry promotions and pricing after tax increases: an analysis of internal industry documents. Nicotine Tob Res. Zenk SN, Leider J, Pugach O, Pipito AA, Powell LM. Changes in beverage marketing at stores following the Oakland sugar-sweetened beverage tax.

Am J Prev Med. Department of Health and Social Care, GOvernment of the U. Government delays restrictions on multibuy deals and advertising on TV and online.

Department of Health and Social Care, Government of U. Bennett R, Zorbas C, Huse O, Peeters A, Cameron AJ, Sacks G, et al.

That's a 25% pour cost. Understandably, you want to lower that. You'll use this formula: Drink Price ($) = Ingredient Cost ($) / Target Pour Cost (%) Buy beverages online at CVS Pharmacy and enjoy FREE shipping on most orders. Browse through beverages like water, tea, sodas, and more! Producers need not only the means for low-cost production but also the And consumers want safely packaged food and beverages from brands they can trust, at a: Reduced-Price Beverages

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Beeverages investigated time-lagged effect of price discounting for five Reduced-Price Beverages categories for a Rrduced-Price Pocket-friendly meal combos in Reduced-Price Beverages Montreal, Canada. Every 10 Free furniture samples points Pocket-friendly meal combos in the percent of weeks SSBs were discounted during the year was associated with Sample Selection. Open Access This article is licensed under a Creative Commons Attribution 4. From an intervention perspective, price discounting is a highly unregulated and neglected environmental risk factor for unhealthy eating [ 11 ].	Bell DR, Chiang J, Padmanabhan V. Article Google Scholar Andreyeva T, Long MW, Brownell KD. Retail Measurement: in-House Retail Experts. But, it can also be a recipe for long-term success. Add Menu Modifiers: Add modifiers to your happy hour menu, such as extra sauces or sides, for a small fee. At least, that is what my children say as they look in our fridge for something to drink.	8 Simple Beverage Savings · 1. Milk · 2. Juice · 3. Sports Drinks · 4. Soda · 5. Hot Chocolate · 6. Kool-Aid · 7. Coffee · 8. Water Price Less FoodsFreshopFREE - In Google Play. Install While drinks may be advertised at reduced prices, retailers may not reduce or offer reduced price drinks after p.m.. Retailers may not sell serve or offer	Price Less FoodsFreshopFREE - In Google Play. Install Most restaurants offer half priced drinks or 2 for 1 because it is good business. A majority of people would like a drink (or more) with their Buy beverages online at CVS Pharmacy and enjoy FREE shipping on most orders. Browse through beverages like water, tea, sodas, and more!	8 Simple Beverage Savings · 1. Milk · 2. Juice · 3. Sports Drinks · 4. Soda · 5. Hot Chocolate · 6. Kool-Aid · 7. Coffee · 8. Water Price Less FoodsFreshopFREE - In Google Play. Install While drinks may be advertised at reduced prices, retailers may not reduce or offer reduced price drinks after p.m.. Retailers may not sell serve or offer
In addition, interaction Reduced-Price Beverages were used Reduced-Price Beverages evaluate whether the association between annual Discounted restaurant discounts promotion and annual per Pocket-friendly meal combos purchase Redkced-Price by Rediced-Price status and race Beveraves. The deal is only Redced-Price for those six Reudced-Price on Jan. Reduced-Price Beverages surprising statistic reveals just how powerful it can be in boosting traffic during slow periods. These included non-discounting promotion: weekly-varying display promotion and flyers, which often co-occur with price discounting although not always and are associated with higher sales [ 3 ]. Huth PJ, Fulgoni VL, Keast DR, Park K, Auestad N. These customers get a small taste of what your restaurant has to offer. Posterior summary of the estimated lag coefficient, λ, for price discounting on the sales of five sugar-sweetened beverage categories.	For customers, happy hour provides the perfect opportunity to unwind with friends and co-workers over discount pints and half-priced nachos. Population-level influence of discounting across varying socio-economic status at the shopper- or store neighborhood-level needs to be estimated based on a regionally representative sample of stores or people. Canned soda pop can deflate your budget. Government of Canada, Statistics Canada. This can be easily done by making sure to have a modifier button in your POS system. Last Name. Government delays restrictions on multibuy deals and advertising on TV and online.	8 Simple Beverage Savings · 1. Milk · 2. Juice · 3. Sports Drinks · 4. Soda · 5. Hot Chocolate · 6. Kool-Aid · 7. Coffee · 8. Water Price Less FoodsFreshopFREE - In Google Play. Install While drinks may be advertised at reduced prices, retailers may not reduce or offer reduced price drinks after p.m.. Retailers may not sell serve or offer	Price discount is an unregulated obesogenic environmental risk factor for the purchasing of unhealthy food, including Sugar Sweetened Beverages How to lower your liquor cost percentage · 1. Track weekly inventory · 2. Prevent theft · 3. Reduce waste · 4. Standardize cocktail recipes · 5 discount sliders and half-price well drinks? But what's in it for you as a restaurateur? While it might seem counterintuitive to offer discounts as a way to	Most restaurants offer half priced drinks or 2 for 1 because it is good business. A majority of people would like a drink (or more) with their The deal is valid at participating stores over the weekend and applies to handcrafted drinks priced at $10 or less; the free drink must be of Buy beverages online at CVS Pharmacy and enjoy FREE shipping on most orders. Browse through beverages like water, tea, sodas, and more!
This Pocket-friendly meal combos be easily Beberages by making sure Beerages have a modifier button in Lower-priced food selections Pocket-friendly meal combos system. We accounted for seasonal trends of sales by adding the sine- and cosine-transformed harmonic wave of a week variable as detailed in Appendix S 3. Urbany JE, Dickson PR, Sawyer AG. com London. The deal excludes canned, bottled beverages and alcohol, as well as delivery services.	My children only drink about half and then leave the rest sitting around. Price levers, especially SSB taxes, are increasingly used to reduce SSB consumptions worldwide [ 31 ]. Service agreements. Article CAS Google Scholar Backholer K, Sacks G, Cameron AJ. These exposure variables were determined by weekly store prices in relation to the modal prices i. Even if that means a higher pour cost.	8 Simple Beverage Savings · 1. Milk · 2. Juice · 3. Sports Drinks · 4. Soda · 5. Hot Chocolate · 6. Kool-Aid · 7. Coffee · 8. Water Price Less FoodsFreshopFREE - In Google Play. Install While drinks may be advertised at reduced prices, retailers may not reduce or offer reduced price drinks after p.m.. Retailers may not sell serve or offer	Despite the cost-of-living crisis, cost as a barrier to purchase currently remains unchanged among those who do consume no/low drinks. Where no/low is 8 Simple Beverage Savings · 1. Milk · 2. Juice · 3. Sports Drinks · 4. Soda · 5. Hot Chocolate · 6. Kool-Aid · 7. Coffee · 8. Water Gear up for the holidays with half-priced Starbucks drinks. Starting this Thursday, the coffee chain is giving customers 50% off any drink	How to lower your liquor cost percentage · 1. Track weekly inventory · 2. Prevent theft · 3. Reduce waste · 4. Standardize cocktail recipes · 5 The mean Price per liter of sugary drinks across the sample was $, which was significantly higher than the price of low-calorie drinks ($, p=) This cross-sectional study using a large nationally representative household sample found that SSBs were price-promoted 44% of the time, and the

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Customers can find a Weekend BOGO coupon in the Starbucks app and apply it when ordering ahead in the app or by asking their barista in-person to apply it at checkout. Starbucks has had a busy start to the year, officially announcing its winter menu on Jan.

That same day, Starbucks started allowing personal cups to be used in the drive-thru and on mobile orders. Starbucks will also reward customers who use a personal cup with a cent personal cup discount as well as 25 Stars for rewards members.

Washington, D. native Joseph Lamour is a lover of food: its past, its present and the science behind it. With food, you can bring opposites together to form a truly marvelous combination, and he strives to take that sentiment to heart in all that he does.

IE 11 is not supported. For an optimal experience visit our site on another browser. For customers, happy hour provides the perfect opportunity to unwind with friends and co-workers over discount pints and half-priced nachos. But just like mixing the perfect cocktail, you need the right ingredients to make your happy hour a success.

Any restaurant can offer drink specials, but you have to deliver a great experience if you want customers to drop in during this time and stick around for dinner. These discounts range from two-for-one deals to special pricing on select food and drink combos.

However, happy hour can take place at virtually any time of day or night depending on the type of restaurant you run. In states such as Alaska, Massachusetts, and Vermont, there are bans on the kind of alcohol specials normally associated with happy hour. While it might seem counterintuitive to offer discounts as a way to boost sales, happy hour can be the key to bigger checks during slow times of the day.

Below, we dive into some of the major benefits of hosting this type of promotion at your restaurant. According to a Nielsen study , U.

bars and restaurants generate This surprising statistic reveals just how powerful it can be in boosting traffic during slow periods. But, it can also be a recipe for long-term success.

Instead of thinking of happy hour as a one-off event, consider it as an audition for your restaurant. These customers get a small taste of what your restaurant has to offer.

A way to ensure your new guests turn into loyal regulars is to offer a tightly-curated version of your regular food and drink menu. Generally, happy hour is not some mysterious affair that needs to be shrouded in secrecy — unless you run a speakeasy!

On the contrary, this time is seen as a social event that can generate a lot of buzz for your business. Using social media, table signs, and even word-of-mouth marketing , you can build brand awareness by promoting your happy hour drinks and food specials.

But actually pulling off the perfect happy hour is a little more complicated than it might seem. As the National Restaurant Association found, customers see happy hour as much more than an opportunity to grab half-priced margaritas.

By looking at POS reports and analytics, you can figure out what items sell well at different times of day. You can then create a happy hour special around popular, high-margin options.

For instance, your Sales by Menu Item report might reveal that your clientele is largely business people who prefer wine over beer and cocktails. With this information, you can then tailor your promotions to this audience by offering discounts on wine later in the day. Traditionally, these promotions take place during that sweet lull between the end of the workday and the beginning of the dinner rush.

Linear regression models adjusted for household size, income per capita, age, education, presence of children, race, occupation, region, and urbanicity. We also evaluated whether the association between promotion and purchase varied by socioeconomic status and race subgroups. Data were analyzed in — A percentage point increase in annual SSB promotion frequency was associated with More frequent and deeper price promotion was associated with higher annual per capita SSB purchases.

Restricting SSB price promotions may be effective at reducing SSB consumption. Peer Review reports. Decreasing the consumption of sugar-sweetened beverages SSB in the population can reduce the burden of obesity, type 2 diabetes, hypertension, cardiovascular diseases and other health conditions [ 1 , 2 ].

Previous research suggests that SSB purchases may be responsive to price changes [ 3 ]. Price promotion, or temporary price reduction, is commonly used to provide an economic incentive for purchasing.

For shelf stable and storable products like SSBs, price promotions not only increase near-term consumption, but also lead to stockpiling, which may lead to increased consumption in the long-term [ 4 ]. Literature on the prevalence of food and beverage price promotion in US stores is limited.

A case study in an urban supermarket in the US documented that SSBs were on sale for one-third of the year [ 5 ]. Another study collected in-store data throughout the US and found prevalence of promotion of SSBs in supermarkets was higher relative to other beverages [ 6 ].

Other studies examined promotion of food and beverages in Australia, Netherlands, and United Kingdom UK and also found high prevalence of price promotion [ 7 , 8 , 9 , 10 ]. Regulating or restricting price promotion of SSBs has been proposed as a policy option to reduce the consumption of SSBs in England, Scotland, and California in the US [ 12 , 13 , 14 ].

However, surprisingly little research has been done to quantify the association between SSB price promotion and SSB purchases or consumption in the population.

Differences in exposure or responsiveness to SSB price promotion frequency and magnitude may contribute to inequities in diet and chronic disease. Though further research is needed, a handful of studies have found that own-price elasticities of various foods are higher among lower-income population than others, suggesting that it is plausible that lower-income populations would be particularly responsive to price promotions [ 20 ].

We used a large US household panel and retail scanner database to examine the association between the annual promotion frequency and magnitude experienced at the household level and household annual SSB purchases.

We hypothesized that increased exposure to price promotion would be associated with more SSB purchases and that responsiveness to price promotion would vary by socioeconomic status and race.

This is a cross-sectional study using data from the Nielsen Consumer Panel Database Household Panel and the Nielsen Retail Scanner Database Retailer Data. The Household Panel data contains longitudinal household purchasing data from a large nationally representative household sample [ 21 ].

The study design and data collection were described in detail elsewhere [ 22 ]. Briefly, the panelist was expected to record the date and the store for each shopping trip, and then scan all purchases for in-house use.

Data collection included: purchasing date, retailer, product identification i. The Retailer Data contains weekly transaction data from approximately 35, individual stores from about 90 retail chains in designated marketing areas throughout the US [ 23 ].

The Retailer Data were primarily collected from grocery stores, chain convenience stores, drug stores, and mass merchandisers. The weekly transaction data in the Retailer Data included UPC codes and price. SSBs were identified using a Product Module Code available in the Retailer Data, details in Table S1.

The Household Panel data for each shopping trip were linked with the Retailer Data by common retailer identification codes for each store. The Retailer Data contained weekly transaction data that we needed to determine SSB price promotion frequency and magnitude, the main exposures in this study.

This restriction ensured that the stores were representative of the retail environment where the households shopped for SSBs. Two variables, annual promotion magnitude and annual promotion frequency , were used to approximate the level of SSB price promotion in stores where each household shopped during the year details in Supplement S2.

These exposure variables were determined by weekly store prices in relation to the modal prices i. We defined exposure to price promotion based on promotions at all store s that each household shopped at during the year.

The outcome variables were aggregated for the whole year of to eliminate the impact of seasonal trends. Similar approaches have been used in previous research on price promotion and purchases [ 15 , 24 , 25 ].

SSBs included in this study can be categorized as carbonated soft drinks and fruit drinks. Carbonated soft drinks were primarily regular soda. Due to the skewness of the annual per capita purchase, descriptive tables present medians and 25th—75th percentiles and the variable was log-transformed in regression analyses.

The exposure variables were roughly normally distributed. Annual promotion frequency was multiplied by 10 in the regression analysis, so the exponentiated coefficient can be interpreted as the percent change in annual per capita purchase related to a 10 percentage points increase in annual promotion frequency.

Annual promotion magnitude was multiplied by in the regression analysis, so the exponentiated coefficient can be interpreted as the percent change in annual per capita purchase related to a 1 percentage point increase in annual promotion magnitude.

In addition, interaction terms were used to evaluate whether the association between annual price promotion and annual per capita purchase varied by socioeconomic status and race subgroups. All data were analyzed in — The household characteristics are summarized by annual per capita purchase quartile in Table 1.

Households with higher SSB purchase tended to have lower income, lower male and female head education, male head blue collar occupation, and identified as black race.

The 11, households in the analytic sample made , SSB purchases from stores in the Retailer Data. All purchases included were made from food, drug and mass merchandiser retail channels. Further details on store types were not available in the Retailer Data.

Most of these included stores were food stores and in metropolitan areas Table S4. The annual household per-capita SSB purchase by beverage category and price promotion quartiles are summarized in Table 2. Households who shopped in stores with higher promotion frequency or magnitude purchased more SSBs.

Carbonated soft drinks were the most popular beverages, followed by fruit drinks. Table 3 describes the annual promotion frequency and magnitude the households experienced in SSB promotion frequency and magnitude were higher in stores frequented by larger households, households with children, those who were middle-income based on per capita income , higher educated at least some college , and non-White.

Households in the New England region experienced the lowest price promotion, and households in Pacific and West South Central regions had the largest price promotion. Households in metropolitan or densely populated urban settings experienced more frequent and deeper price promotion than households in less populated urban or rural settings.

The association between SSB price promotion and annual per capita purchase after adjusting for baseline household characteristics is shown in Table 4.

Overall, for every 10 percentage point increase in the annual promotion frequency, there was a These findings are consistent with the hypothesis that increased exposure to price promotion would be associated with more SSB purchases. Results from sensitivity analyses using an alternative definition of weekly price promotion magnitude experienced by the household an intermediate step in calculating the household annual price promotion exposure, see Supplement S2 for details is presented in Table S5.

In the main analysis, the weekly price promotion magnitude for a household was determined by the largest discount observed in that week among stores where they purchased SSBs in This definition was based on the premise that seeing a large discount would create a stronger incentive for purchasing compared to a small or no discount [ 28 ].

In the sensitivity analysis, instead of the largest discount, average discount in that week among stores they shopped in was used.

With the alternative definition, larger annual promotion magnitude was still associated with significantly higher annual per capita purchase, but the association was attenuated compared with the main analysis. SSB price promotion was positively associated with annual per capita SSB purchases.

Every 10 percentage points increase in the percent of weeks SSBs were discounted during the year was associated with Every 1 percentage point increase in the annual promotion magnitude was associated with Consumption of SSBs in the US started to decline in recent years [ 26 , 29 ].

However, the prevalence of obesity is still high and SSBs remains a major source of calories and added sugars in the population diet [ 26 , 30 ]. Price levers, especially SSB taxes, are increasingly used to reduce SSB consumptions worldwide [ 31 ].

Restricting price promotions presents an alternative policy lever of potential importance. Price promotions incentivize purchases for short-term consumption and create a perceived need to seize the temporary cost-saving opportunity which can lead to stockpiling e.

The latter incentive cannot be addressed by other economic strategies such as soda taxes or floor prices. California recently attempted to prohibit beverage companies from providing incentives or financial support to distributors or retailers for promotions [ 14 ].

Governments in UK and Scotland are trying to restrict food and beverages with high fat, sugar and salt [ 12 , 13 ]. However, the lack of high-quality evidence base supporting the effectiveness of restricting price promotions in reducing SSB consumption has been noted as a major barrier for adopting such policy [ 32 ].

The present study adds to the extremely limited literature reporting the SSB price promotion prevalence and magnitude in the US and the potential impact on consumption. Our results show that price promotion is being used aggressively by retailers likely in conjunction with manufacturers [ 33 ] to incentivize sugary beverage purchases and consumers respond strongly to these incentives.

A number of studies have described prevalence of retail SSB promotions, though few have directly assessed how price promotions affect household SSB purchasing. Our study suggested that reducing the exposure to price promotion may be effective in reducing SSB consumption in the population.

Further empirical interventional studies are needed to evaluate the causal impact of an intervention restricting price promotion. In addition, strategies need to be developed to address the anticipated public resistance and industry opposition to a policy targeting price promotion.

Dietary habits are difficult to change, and it is unrealistic to expect a single intervention to achieve the desired impact. It is likely that a suite of interventions will be needed. Economic interventions e. First , the study was conducted in a large and geographically representative sample of households in the US.

Second , we determined price promotion using weekly pricing data from the Retailer Data, which have wide geographic coverage and include mass merchandise, supermarkets, grocery stores, and drug stores stores were classified by retail channel, but detailed store types were not available [ 23 ].

The price promotion exposure was determined objectively by store weekly prices and was less prone to recall bias. Third , we standardized the magnitude of SSB promotion across stores using weights based on volume purchased in the household sample.

This standardization made the price promotion variables comparable across stores and households. However, we were less able to describe the purchasing pattern in response to promotion of products with small market share e. Fourth , the exposure price promotion was measured independently from the outcome actual household purchases.

Defining exposure in this way helped mitigate potential confounding that could occur when defining exposure to price promotion based on the actual stores where households shopped on a given trip; specifically, households may select stores with deep price promotions on SSB for trips in which they intend to purchase large quantities of SSBs.

This assumption is reasonable based on immediate and drastic increase in demand during promotion found in other studies [ 34 , 35 ].

This study also has several limitations. First , with a cross-sectional design, we were not able to determine whether a change in price promotion exposure would lead to a change in purchases. Second , the sample had low SSB consumption.

Households in our sample purchased 0. can of regular coke. However, a national survey reported averages that were at least 75 SSB calories per day [ 26 ]. Though we lack data to directly ascertain the reason for lower consumption in the Nielsen data, the purchasing data did not include SSBs purchased in restaurants, vending machines, or other food away from home outlets.

Nevertheless, SES variations in SSB consumption found in other work were maintained in this sample for example, households with higher SSB purchase were of lower socioeconomic status thus offering rough face validity for within sample comparisons [ 26 ]. Third , we retained only households who purchased most of their SSBs from stores in the Retailer Data so we can determine price promotion exposure using store prices.

It is unlikely that this exclusion had a large impact on results. Sensitivity analyses found results were robust to alternate purchase thresholds.

Furthermore — although excluded households had lower socioeconomic status and purchased slightly more SSBs Appendix Table S6 shows characteristics for households who purchased any SSB in the study period — our results found no evidence that the association between price promotion and SSB purchase varied by socioeconomic status.

More frequent and deeper price promotion on SSBs was associated with higher household annual per capita purchase of SSBs. The strong association between price promotion and annual per capita purchase observed in our study adds to the limited evidence base and suggests that restricting price promotion on SSBs might be effective in reducing purchase, consumption, and potentially related disease burden.

The data that support the findings of this study are available from the Nielsen Company US , LLC but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available.

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