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Food Marketing Practices of Major Online Grocery Retailers in the United States, 2019-2020

Published:April 11, 2022DOI:https://doi.org/10.1016/j.jand.2022.04.003

      Abstract

      Background

      Food marketing influences consumers’ preferences for and selection of marketed products. Although a substantial body of research has described food-marketing practices in brick-and-mortar stores, no research has examined food marketing in online grocery retail despite its growing importance as a source of food-at-home purchases.

      Objective

      To develop and apply a coding instrument to describe food marketing and the nutritional quality of marketed products in online grocery stores.

      Design

      Quantitative content analysis and review of product Nutrition Facts labels and ingredients lists to calculate nutrient density and level of processing using the NOVA classification system.

      Participants/setting

      Foods and beverages (n = 3,473) marketed in the top revenue-generating online grocery retailers and those participating in the US Department of Agriculture Supplemental Nutrition Assistance Program Online Purchasing Pilot (n = 21) in 2019-2020.

      Main outcome measures

      Use of marketing mix strategies (ie, product, placement, promotion, and pricing) across retailers and nutritional quality of marketed products. Products were considered of poor nutritional quality in the case that they were ultraprocessed (NOVA category 4) and excessive in sodium, saturated fat, free sugars, and/or other sweeteners. Products were also classified into 13 mutually exclusive food groups.

      Statistical tests performed

      The proportion of retailers using each marketing strategy, proportion of products of poor nutritional quality, and proportion of products in each food group were calculated.

      Results

      Retailers commonly used product recommendations, search result ordering, branded website content, user-generated content, and social media engagement to market products online. Candy, sweets, and snacks made up the largest percentage of marketed products (17.3%), followed by fruit, vegetables, and legumes (16.7%). Most (62%) marketed products were of poor nutritional quality. Staple food categories such as fruits, vegetables, and grains were frequently marketed, particularly through price reductions and product recommendations.

      Conclusions

      Online grocery retailers use a variety of customizable food marketing strategies on their websites. Although most marketed products are of poor nutritional quality, there is potential for marketing of staple food categories online that is not feasible in a brick-and-mortar store.

      Keywords

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      References

        • Redman R.
        Online grocery to more than double market share by 2025. Supermarket News. September 18, 2020.
      1. 2020 online grocery shopping statistics: pre and post covid-19. Superfood.com. April 16, 2020.
      2. Prime is just $5.99/month∗ for qualifying government assistance recipients.
        • Moran A.
        • Headrick G.
        • Khandpur N.
        Promoting equitable expansion of the SNAP Online Purchasing Pilot. July 2021.
        • Rivlin G.
        Rigged: Supermarket shelves for sale. September 2016.
        • Hecht A.A.
        • Perez C.L.
        • Polacsek M.
        • Thorndike A.N.
        • Franckle R.L.
        • Moran A.J.
        Influence of food and beverage companies on retailer marketing strategies and consumer behavior.
        Int J Environ Res Public Health. 2020; 17: 7381
        • Glanz K.
        • Bader M.D.
        • Iyer S.
        Retail grocery store marketing strategies and obesity: an integrative review.
        Am J Prev Med. 2012; 42: 503-512https://doi.org/10.1016/j.amepre.2012.01.013
        • Khandpur N.
        • Zatz L.
        • Bleich S.
        • et al.
        Supermarkets in cyberspace: a conceptual framework to capture the influence of online food retail environments on consumer behavior.
        Int J Environ Res Public Health. 2020; 17: 8639https://doi.org/10.3390/ijerph17228639
        • McCarthy J.
        • Minovi D.
        • Wootan M.
        Scroll and shop: Food marketing migrates online. January 2020.
        • Jilcott Pitts S.B.
        • Ng S.W.
        • Blitstein J.L.
        • Gustafson A.
        • Niculescu M.
        Online grocery shopping: promise and pitfalls for healthier food and beverage purchases.
        Public Health Nutr. 2018; 21: 3360-3376https://doi.org/10.1017/S1368980018002409
        • Chester J.
        • Kopp K.
        • Montgomery K.C.
        Does buying groceries online put SNAP participants at risk? How to protect health, privacy, and equity. July 2020.
        • Mathur A.
        • Acar G.
        • Friedman M.J.
        • et al.
        Dark patterns at scale: findings from a crawl of 11K shopping websites.
        Proc ACM Hum Comput Interact. 2019; 3: 1-32https://doi.org/10.1145/3359183
        • Chester J.
        • Montgomery K.C.
        • Kopp K.
        Big food, big tech, and the global childhood obesity pandemic. May 12, 2021.
        • Bhatnagar P.
        • Scarborough P.
        • Kaur A.
        • Dikmen D.
        • Adhikari V.
        • Harrington R.
        Are food and drink available in online and physical supermarkets the same? A comparison of product availability, price, price promotions and nutritional information.
        Public Health Nutr. 2021; 24: 819-825https://doi.org/10.1017/S1368980020004346
        • Euromonitor International
        Top U.S. supermarkets by revenue. February 2021.
        • US Dept of Agriculture
        USDA launches SNAP Online Purchasing Pilot: Participants may buy groceries online in New York. April 18, 2019.
        • US Census Bureau
        American Community Survey 2014-2018 5-year estimates now available. December 19, 2019. Updated October 8, 2021.
      3. Moran A, Perez C, Headrick G Taillie LS, Khandpur N. Capturing marketing and policy practices of online food retailers: a codebook. Accessed April 21, 2022. https://doi.org/10.17605.OSF.IO/VY9T

        • McMillan S.J.
        The microscope and the moving target: the challenge of applying content analysis to the world wide web.
        Journal Mass Commun Q. 2001; 77https://doi.org/10.1177/107769900007700107
        • Kim I.
        • Kuljis J.
        Applying content analysis to web-based content.
        J Comput Inf Technol. 2010; 18: 369-375
        • Garasky S.
        • Mbwana K.
        • Romualdo A.
        • Tenaglio A.
        • Roy M.
        Foods typically purchased by SNAP households: Appendices. November 2016.
      4. Best sellers grocery gourmet food. Updated November 19.
        • Nutrition & Obesity Policy Research and Evaluation Network (NOPREN)
        Healthy Retail Work Group.
      5. Qualtrics. Qualtrics; 2020.

        • Monteiro C.A.
        • Cannon G.
        • Levy R.B.
        • et al.
        Ultra-processed foods: what they are and how to identify them.
        Public Health Nutr. 2019; 22: 936-941https://doi.org/10.1017/S1368980018003762
        • Crimarco A.
        • Landry M.J.
        • Gardner C.D.
        Ultra-processed foods, weight gain, and co-morbidity risk.
        Curr Obes Rep. 2021; : 1-13https://doi.org/10.1007/s13679-021-00460-y
        • Popkin B.M.
        • Barquera S.
        • Corvalan C.
        • et al.
        Towards unified and impactful policies to reduce ultra-processed food consumption and promote healthier eating.
        Lancet Diabetes Endocrinol. 2021; 9: 462-470https://doi.org/10.1016/S2213-8587(21)00078-4
        • Khandpur N.
        • Neri D.A.
        • Monteiro C.
        • et al.
        Ultra-processed food consumption among the paediatric population: an overview and call to action from the European Childhood Obesity Group.
        Ann Nutr Metab. 2020; 76: 109-113https://doi.org/10.1159/000507840
        • Mozaffarian D.
        • El-Abbadi N.H.
        • O’Hearn M.
        • et al.
        Food Compass is a nutrient profiling system using expanded characteristics for assessing healthfulness of foods.
        Nat Food. 2021; 2: 809-818https://doi.org/10.1038/s43016-021-00381-y
        • Pan American Health Organization
        Nutrient Profile Model.
        https://www.paho.org/en/nutrient-profile-model
        Date: 2016
        Date accessed: October 26, 2021
        • Franckle R.L.
        • Moran A.
        • Hou T.
        • et al.
        Transactions at a northeastern supermarket chain: differences by Supplemental Nutrition Assistance Program use.
        Am J Prev Med. 2020; 59: 305https://doi.org/10.1016/j.amepre.2017.06.019
      6. Stata Statistical Software: Release 15. StataCorp LP; 2017. www.stata.com

        • Headrick G.
        • Khandpur N.
        • Perez C.
        • Taillie L.S.
        • Bleich S.N.
        • Rimm E.B.
        • Moran A.
        Content analysis of online grocery retail policies and practices affecting healthy food access.
        J Nutr Educ Behav. 2022; 54: 219-229
        • Olzenak K.
        • Fresnch S.
        • Sherwood N.
        • Redden J.P.
        • Harnack L.
        How online stores support consumer nutrition information needs.
        J Nutr Educ Behav. 2020; 53: 952-957https://doi.org/10.1016/j.jneb.2020.07.009
        • Pomeranz J.L.
        • Cash S.B.
        • Springer M.
        • Del Guidice I.M.
        • Mozaffarian D.
        Opportunities to address the failure of online food retailers to ensure access to required food labelling information in the USA.
        Public Health Nutr. 2022; : 1-9https://doi.org/10.1017/S1368980021004638
        • Cheyne A.D.
        • Dorfman L.
        • Bukofzer E.
        • Harris J.L.
        Marketing sugary cereals to children in the digital age: a content analysis of 17 child-targeted websites.
        J Health Commun. 2013; 18: 563-582https://doi.org/10.1080/10810730.2012.743622
        • NielsenIQ
        Which health and food segments are missing out on the e-commerce boom? March 9, 2021.
        (Accessed on May 26, 2021)
        • Karpyn A.
        • McCallops K.
        • Wolgast H.
        • Glanz K.
        Improving consumption and purchases of healthier foods in retail environments: a systematic review.
        Int J Environ Res Public Health. 2020; 17: 7524https://doi.org/10.3390/ijerph17207524
        • Greene J.
        Understanding the value of academic research partnerships with food retailers. December 2020.
        • Hannak A.
        • Soeller G.
        • Lazer D.
        • Mislove A.
        • Wilson C.
        Measuring price discrimination and steering on e-commerce web sites. Paper presented at: IMC ’14: Proceedings of the 2014 Conference on Internet Measurement. Vancouver, BC, Canada, November 5-7, 2014.
        • Coffino J.A.
        • Udo T.
        • Hormes J.M.
        Nudging while online grocery shopping: a randomized feasibility trial to enhance nutrition in individuals with food insecurity.
        Appetite. 2020; 152: 104714https://doi.org/10.1016/j.appet.2020.104714
        • Vadiveloo M.
        • Guan X.
        • Parker H.W.
        • et al.
        Effect of personalized incentives on dietary quality of groceries purchased: a randomized crossover trial.
        JAMA Network Open. 2021; 4e2030921https://doi.org/10.1001/jamanetworkopen.2020.30921
        • Koutoukidis D.A.
        • Jebb S.A.
        • Ordonez-Mena J.M.
        • et al.
        Prominent positioning and food swaps are effective interventions to reduce the saturated fat content of the shopping basket in an experimental online supermarket: a randomized controlled trial.
        Int J Behav Nutr Phys Act. 2019; 16: 50https://doi.org/10.1186/s12966-019-0810-9
        • Eubanks V.
        Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor.
        St Martin’s Press, 2018

      Biography

      A. J. Moran is an assistant professor, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.

      Biography

      C. Perez is a doctoral degree candidate, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.

      Biography

      G. Headrick is a doctoral degree candidate, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.

      Biography

      A. Greatsinger is a senior health care analyst, Analysis Group, Boston, MA.

      Biography

      L. S. Taillie is an assistant professor, Department of Nutrition, Gillings School of Global Public Health, Carolina Population Center, University of North Carolina, Chapel Hill.

      Biography

      L. Zatz is a senior advisor, The Behavioral Insights Team North America, City, State; at the time of the study, she was a doctoral degree candidate, Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA.

      Biography

      S. N. Bleich is a senior advisor for COVID, Office of the Secretary, US Department of Agriculture, City, State; at the time of the study, she was a professor, Department of Health Policy and Management, Harvard TH Chan School of Public Health, Boston, MA.

      Biography

      E. B. Rimm is a professor, Departments of Nutrition and Epidemiology, Harvard TH Chan School of Public Health, Boston, MA.

      Biography

      N. Khandpur is a research scientist, Department of Nutrition, University of Sao Paulo, Sao Paulo, Brazil, and a visiting scientist, Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA.