(2024) 22:341
Maganja et al. BMC Medicine
https://doi.org/10.1186/s12916-024-03557-y

BMC Medicine

RESEARCH ARTICLE

Open Access

Healthiness of food products promoted
through placement strategies in Australian
online supermarkets: a cross‑sectional study
Damian Maganja1* , Madeleine de Carle2, Tazman Davies1, Clara Gómez Donoso3, Tailane Scapin3,
Adrian J. Cameron3, Jimmy C. Y. Louie1,4, Mark D. Huffman1,5, Kathy Trieu1 and Jason H. Y. Wu1,6

Abstract
Background Prominent product placement is a core promotional tactic in retail food environments. How this practice has been adapted for online supermarkets, and the extent to which it is applied to healthier and less healthy foodproducts in this setting, is largely unknown. We aimed to investigate placement-type promotions of food productsin Australian online supermarkets.
Methods We developed a new method to assess placement promotions and applied it to the online storesof the two largest supermarket retailers in Australia. Each online store was audited across six ‘locations’ (input prior
to data collection), including a randomly selected high socio-economic position area and low socio-economic position area from each of the three largest Australian cities. The names, page locations and type of placement strategy
of promoted food products were captured, with product healthiness assessed using the Health Star Rating (HSR)
nutrient profiling system. Descriptive statistics summarised the page locations of promoted products and the placement strategies used to promote them, and chi-squared tests applied to compare product healthiness by retailer
and socio-economic position.
Results We recorded 12,152 food products promoted through placement strategies, 99% of which were eligible
for a HSR. Overall, 44% of products promoted through placement strategies were unhealthy. Cross-promotions
and recommendations was the most common strategy recorded overall (55.9% of all strategies), and advertisements and site content was the strategy most likely to promote unhealthy products (53.7% of products unhealthy).
One retailer was more likely to promote unhealthy products (46% v 43%, p = 0.004) and unhealthy products weremore likely to be promoted in more disadvantaged than less disadvantaged locations (45% vs 43%, p = 0.05),
though the magnitudes of difference were small.
Conclusions A considerable number of unhealthy products are likely presented to online grocery shoppers in Australia. Public health policies targeting unhealthy food promotions may need to be updated, including with consideration of the different ways that products can be prominently displayed online, to avoid exacerbating risks of dietrelated disease and health inequalities. Our novel methodology could be used for ongoing monitoring of online
supermarkets in Australia and elsewhere to inform such policies.
Keywords Online supermarkets, Product placement, Food environments, Product promotions*Correspondence:
Damian Maganja
dmaganja@georgeinstitute.org.au
Full list of author information is available at the end of the article© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0
International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as longas you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if
you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article orparts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicatedotherwise 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
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view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Maganja et al. BMC Medicine(2024) 22:341

Background
Products are strategically positioned on the shelves,
floors and counters of retail stores to boost sales, asa core retailer marketing strategy [1–3]. Retailers use
consumer browsing and sales data as well as psychological insights to inform place-based techniques suchas conspicuous lighting and end-of-aisle bins that more
subtly influence consumer purchasing decisions than
through overt advertising, though these strategies areoften used together [1, 2]. The practice of product placement in physical retail stores is well understood, and thisapproach can be applied to encourage both unhealthy
and healthy food purchases [1–10].
Online grocery shopping is becoming increasingly
popular in many countries. By 2020, online sales alreadymade up around a quarter of all expenditure on groceries in China and South Korea [11] and are projected tocomprise one-fifth of total grocery sales by 2030 in someWest European countries [12]. In Australia, just under
half of consumers already do at least some grocery shopping online [13]. Whether there is any differential application of product placement strategies to healthy andunhealthy products in online grocery stores is largely
unknown to date [14–17].
The layout of an online store is fundamentally different to a physical store, and marketing techniques arebeing adapted for the online setting [14, 18, 19]. Product placement may be particularly important in online
stores; unlike in physical stores, if a product is not in aprominent position online, a consumer may not see it atall [19]. With the increase in uptake of online shopping, it
is essential to understand how retailers are using productplacements in these increasingly important food retail
environments.
The primary aim of this study was to investigate theplacement of healthy and unhealthy food products on the
online stores of Australian supermarket retailers, including an assessment of the types and locations of placement strategies applied. We hypothesised that unhealthy
products would be heavily promoted through prominent
product placement overall, as has been seen in assessments and monitoring of Australian physical stores [20–23] and in emerging international research into online
retail settings [24]. There were two secondary aims. The
first was to assess whether the healthiness of productplacements differed by user area-level socio-economic
position; we hypothesised that unhealthy products would
be more commonly promoted when accessing the supermarket websites from more socio-economically disadvantaged areas, as there is some evidence that physicalstores in such areas are more likely to promote unhealthy
products using placement strategies in Australia [20–23]. The second secondary aim was to assess whether

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the healthiness of product placements differed between
major retailers; while only marginal differences in thehealthiness of products promoted through placement
strategies have previously been found between retailers
in physical stores in Australia [21–23], understanding
and comparing individual food company commitments
and actions forms an important part of accountability
mechanisms, encourages competitive improvements inpractices, and supports advocacy to improve government
regulations [25, 26].

Methods
Data collection

Two supermarket retailers in Australia, Woolworths andColes, dominate the sector with 37% and 30% of the total
market share, respectively [27]. Both offer online grocery
shopping and were selected for data collection. The next
largest retailer, Aldi, accounts for only 9% of the total
market share [27] and does not offer online shopping.
To the best of our knowledge, there is not yet a widely
accepted best practice for assessing online retail productplacement strategies [14, 16]. As such, drawing upon arecently developed framework for assessing online foodretail environments [14] and insights into consumer
behaviour in online grocery stores [28], the lead author(DM) developed an initial data collection protocol in
consultation with two senior colleagues (KT, JW). Subsequently, two researchers (DM, MdC) pilot tested thedata collection protocol across the online stores of both
retailers included in this study, with potential issues identified and resolved by consensus with KT and JW; acrossn = 1160 products collected through the pilot there werefew (< 10) discrepancies. This informed the final data collection protocol described below.
See Fig. 1 for an overview of the data collection process
and Additional File 1: Supplementary Fig. 1 for examples of how data was collected. In brief, the two retailers’
online stores were audited six times each, with the namesof products promoted by different placement strategies
recorded and the healthiness of those promoted products assessed using the Health Star Rating (HSR) system,a government-endorsed front-of-pack nutrition labelling
scheme in Australia and New Zealand. We generated
descriptive statistics to summarise the page locations ofthese promoted products, the placement strategies used
to promote them, and their healthiness.
Store ‘location’, timing of collection, user accounts
and computer settings

Data collection was conducted across six urban locations(suburbs) where both Woolworths and Coles stores are
physically present. We focussed on Sydney, Melbourneand Brisbane, as the three largest cities by population inMaganja et al. BMC Medicine(2024) 22:341

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Fig. 1 Data collection process. Note that not all strategies may be applied by all retailers across all page types. IRSAD, Index of Relative
Socioeconomic Advantage and Disadvantage

Australia, together accounting for 49.9% of the total Australian population [29]. Within each city, we randomly
selected two suburbs, one each from the highest and thelowest quintile by the Index of Relative Socioeconomic
Advantage and Disadvantage (IRSAD), which assesses
both the presence and absence of several social and economic factors to summarise area-level socio-economic
advantage and disadvantage [30]; a low score indicates
relatively greater disadvantage and a lack of advantage,
and a high score indicates a relative lack of disadvantage
and greater advantage. Randomisation was performed byassigning a number generated using the ‘randbetween()’function in Microsoft Excel against a list of suburbs, sorting those numbers from smallest to largest, and selecting
the top results (with replacement with the next suburb if
both Woolworths and Coles stores were not present inthat suburb, as determined using each retailer’s respective online store locator function). For each city and suburb, we assessed both Woolworths’ and Coles’ online
stores (i.e. 12 store postcodes/locations in total). Data

were collected over 8 days in early-October 2023, whenno significant public dates or events that might lead topotential outlier effects nationally or in any state or territory were current or imminent.
Personal user accounts were set up for each of thecollections using generic email addresses and genderneutral names (e.g. Alex Williams, Kim Smith), with thelocation of the store set using the pre-determined suburbs. As dates of birth were required by one retailer they
were input for both retailers, determined according to
the median age of residents in each suburb [31]. Neither
retailer required any other demographic information to
be provided to begin data collection.
To limit the influence of internet history and othertracking on the products presented to the researchers, browsing history and cookies were cleared prior tocommencing data collection for each store, websites
were viewed in incognito browsing mode, a new tab was
opened for each store collection and browser-based location tracking was disabled. Data were captured by one

Maganja et al. BMC Medicine(2024) 22:341

investigator (DM). Data for each ‘location’ was collectedin full in one sitting, without using that computer for any
other purpose.
Online supermarket pages assessed for product placement
strategies

For each store location, we assessed product placement
promotion strategies across five distinct displays/pages
commonly available in online supermarkets [14, 28]:
homepage (as the first screen users are presented with),
category pages (selecting retailer-determined food categories to view products), search results pages (entering
keywords into the search function), product pages (theindividual pages for a specific product) and basket andcheckout pages (as the final pages users are presentedwith). These were assessed in the following manner:
Homepage—we entered the retailer’s web address
into the web browser address bar to access the store
homepage.
Category pages—we navigated from the homepage toeach of the retailer’s major (i.e. first-level) category pages(e.g. pantry, bakery), including categories which may
contain both food and non-food products (e.g. baby) but
excluding those that did not contain any food products(e.g. household items such as cleaning products), standalone alcoholic beverages categories (e.g. liquor) and promotions-only categories (e.g. specials).
Search result pages—we pre-defined a list of ten genericproduct categories that have both more healthy andless healthy options (Health Star Rating ≥ 3.5 and < 3.5,
respectively; see below for further information) to use
as specific search terms (milk, soft drink, water, bread,juice, chicken, meat, yoghurt, cheese, sauce). These areamongst the categories with the highest per capita consumption (grams per day) in Australia according to theAustralian Bureau of Statistics’ 2020–2021 Apparent
Consumption of Selected Foodstuffs data [32] and, withthe exception of plain water, the highest contributions tototal energy, sugars, saturated fat and/or sodium intakes
according to the 2011–2012 Australian Health Survey(the most recent data available) [33]. The search terms
were entered, one-by-one, into the search bar, with thereturned search results examined for product placement
strategies.
Product pages—we randomly selected four products
available across both retailers from each of the 10 aforementioned categories (n = 40 products in total). For
each category, at least one private label (i.e. supermarket
home/generic branded) product was included to approximate the product split (25% private label v 75% branded
products) seen across both Coles and Woolworths ina study using 2022 online data [34]. Products were randomly selected from a set of n > 20,000 products collected

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online quarterly in 2023 [35]. Category-specific random
numbers were firstly generated and assigned to all products. These numbers were sorted from smallest to largest,with products then selected from the smallest number
downwards, ensuring those selected were available andcomparable (in terms of their size and price) across both
retailers. To navigate to the appropriate individual product page for collection, the specific URL for each product was entered. See Additional File 2: Supplementary
Table 1 for a full list of products randomly selected in thisstep.
Basket and checkout pages—each of the 40 randomly
selected products was added to the shopping cart. If
the specific product was out of stock, the first alternative suggested by the retailer was added. The shopping
cart and subsequent page/s (e.g. delivery, payment, final
review) were then navigated to and product placement
strategies assessed.
Product placement strategies assessed in the online stores

We appraised three types of promotional strategies relying on prominent product placement: advertisements
and site content, cross-promotions and recommendations, and default product listings, drawing upon arecently developed framework for assessing online foodretail environments and other insights into consumer
behaviour in online grocery stores [14, 16]. These wereassessed as below (also shown in Additional File 1: Supplementary Fig. 1):
Advertisements and site content—we recorded all
identifiable products in banners and other advertisements, displaying promotional flags not directly included
in default product listings, or otherwise embedded in
product pages or navigation (e.g. links to categories that
display a specific product), including those requiring
additional action such as scrolling in any direction.
Cross-promotions and recommendations—we captured
all suggested or highlighted products ostensibly tied toindividual products or categories selected by the user
and/or by other purported users (e.g. complementary,
bundled, most popular), including those requiring additional action such as scrolling in any direction.
Default product listings—we recorded all products
appearing in the top three rows of the default results
list, except for those products already captured underother strategies above, as appearing on the relevant pageusing the Google Chrome browser operating on a Windows OS, with medium font size and 100% zoom andmaximised to fit screen, on a single monitor displayed in
1920 × 1080 resolution in landscape. Though this may not
capture all product listings under a category or returned
through a search, when browsing online consumers may
focus most of their attention to the immediately visible

Maganja et al. BMC Medicine(2024) 22:341

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information displayed at the top of webpages and be lesslikely to scroll down [36, 37].
For each product identified, we recorded the page
where it was found and the relevant product placement
strategy applied, the product’s brand and name to assist
with subsequent assessment of product healthiness,and, where provided, the product’s HSR. Each individual
product identified was captured. Each repeat display ofthe exact same product across the retailer, store location
and/or page was recorded. The same product displayed in
multiple package sizes or formats was also recorded multiple times (e.g. milk 200 mL, milk 500 mL), whereas asingle product comprised of multiple bundled items wascounted only once (e.g. six-pack of milk 200 mL).

We further compared differences between retailers after
adjusting by location and between locations after adjusting by retailer using linear regression. A conventionalsignificance level (two-sided α = 0.05) was adopted, without adjustment for multiple testing (n = 8 comparisons in
total tested). The mean (SD) number of promoted products, median (IQR) HSR, distribution of strategies andproportion of unhealthy promotions is also disaggregatedby page, for both retailers combined and separately. Statistical analyses were conducted using StataBE v18.

Included and excluded products

In total, we captured 12,152 products promoted throughplacement strategies (n = 7810 for Woolworths, n = 4342
for Coles), of which 12,032 (99%) were eligible for a HSR(n = 7728 for Woolworths, n = 4304 for Coles).
Overall, homepages displayed the most product placement promotions, with 46.0 ± 18.5 (mean ± SD) products
promoted per homepage assessed, whereas basket andcheckout pages showed the fewest promotions (0.2 ± 0.3)
(Table 1). Cross-promotions and recommendations was
the most common strategy recorded (55.9% of all strategies), followed by default product listings (26.6%) andadvertisements and site content (17.5%). Distinct patterns emerged when assessing strategies across pages:
advertisements and site content formed the majority ofplacement promotions on homepages (61.8%) but were
not displayed at all on product pages and in basket andcheckout pages; cross-promotions and recommendations constituted all promotions on product pages andin basket and checkout pages but were not common on
category pages (16.6%); and default product listings provided over half of all promotions on search pages (59.7%)
but were not displayed on homepages, product pages andbasket and checkout pages.
Overall, 44% of products promoted through placement
strategies were categorised as unhealthy, with the median
HSR of promoted products 3.5 (IQR 2.0–4.0) (Table 1).
However, there appeared to be a bimodal distribution of
HSRs amongst promoted products, with 0.5 and 3.5–4.0
HSR products the most frequently promoted throughplacement strategies (Additional File 3: Supplementary
Fig. 2). A subsequent manual examination of products
receiving 0.5 HSR revealed the promotion of a large
number of sugar-sweetened beverages and confectionery
items.
Amongst placement strategies, advertisements andsite content were the most likely to promote unhealthy
products (53.7% of products unhealthy), with less thanhalf of cross-promotions and recommendations (43.5%)

Categories and products were included if they were foods
or non-alcoholic beverages. Alcoholic beverages andinfant formulas were excluded as they are not generalpurpose foods (i.e. generally consumed by the broader
population regardless of age). Non-human foods andnon-food items were also excluded.
Data analysis
Assessment of product healthinessOur assessment of the healthiness of promoted products
was based on product HSR. Here, we defined a productas ‘unhealthy’ if it had a HSR < 3.5; previous assessments
have found good alignment between the HSR system,
using this threshold, and relevant Australian guidelines[38, 39]. Products recorded in our placement promotion audit that did not display a HSR were searched for in
the Australian FoodSwitch database [40, 41], a comprehensive database of nutritional information of products
available in Australian supermarkets, including Woolworths and Coles, to obtain the applicable HSR. If the
product was not available in FoodSwitch we calculated
the HSR based on publicly available product data (nutrition information and ingredients list) using the official
HSR Calculator [42]. Certain products (plain tea andcoffee, chewing gum, plain salt and spices), where captured, were not included in assessments of healthiness as
the HSR system is considered ‘not appropriate’ for those
products [42].
Statistical analyses

The proportion of promoted products categorised as
unhealthy is reported overall, by high-/low-IRSAD locations and for each retailer. Differences in the proportionof promoted products considered unhealthy were compared (1) between retailers in total and by high- and lowIRSAD locations and (2) between high- and low-IRSAD
locations in total and by retailer, using chi-squared tests.

Results
Number of products promoted through placement
strategies, the types of strategies used, and overall
healthiness of products promoted

Maganja et al. BMC Medicine(2024) 22:341

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Table 1 Food products promoted through prominent placement on online stores of two retailers, Australia, 2023, all stores searched(n = 12)Mean (SD)number ofpromoted
products

Proportion of all
strategies (%)

Median(IQR) HSR of
promoted
productsa

Advertisements
and site content

Crosspromotions andrecommendations

Default
product
listings

Proportionof products <3.5 HSR (%)aTotal

Advertisements
and site content

Crosspromotions andrecommendations

Default
product
listings

Total (n= 756pages)

21.0 (17.8)

17.5%

55.9%

26.6%

3.5 (2.0–4.0)

44.0%

53.7%

43.5%

38.9%

Home‑
page
(n = 12
pages)

46.0 (18.5)

61.8%

38.3%

0%

2.5 (1.0–4.0)

54.0%

51.8%

57.9%

N.A.

Cat‑
egory
page (n= 132­pagesb)

24.6 (7.0)

35.5%

16.6%

47.9%

3.5 (2.0–4.0)

42.9%

53.4%

35.7%

37.7%

Searchresults(n = 120
pages)

23.0 (5.7)

22.1%

18.2%

59.7%

3.5 (2.0–4.0)

45.6%

55.2%

52.3%

40.0%

Productpages(n = 480
pages)

11.5 (4.8)

0%100.0%

0%

3.5 (2.0–4.0)

42.9%

N.A.

42.9%

N.A.

Basketandcheck‑outpages(n = 12
pages)

0.2 (0.3)

0%100.0%

0%0.5 (0.5–0.5)

100.0%

N.A.

100.0%N.A.

HSR Health Star Rating, N.A. Not applicable (as the particular product placement strategy was not used)a

After excluding products such as plain tea and coffee, chewing gum and plain salt and spices for which the HSR system is considered ‘not appropriate’ according to
official guidance (n = 120 in total, across all stores searched)b

For Woolworths, n = 12 categories were assessed per location: Fruit & Veg; Bakery; Poultry, Meat & Seafood; Dairy, Eggs & Fridge; Deli & Chilled Meals; Lunch Box;
Pantry; Freezer; Snacks & Confectionery; Drinks; Health & Wellness; Baby (promotions in the Health & Wellness and Baby categories were predominantly non-food). For
Coles, n = 10 categories were assessed per location: Back to School; Meat & Seafood; Fruit & Vegetables; Dairy, Eggs & Fridge; Bakery; Deli; Pantry; Drinks; Frozen; Baby
(promotions in the Baby category were predominantly non-food)and default product listings (38.9%) overall promoting
unhealthy products (Table 1). Different strategies dominated different pages, and though the proportion of promoted products that were unhealthy differed across pages
and strategies, at least a third (> 35%) of products promoted on any page and by any strategy were unhealthy.
The prevalence of placement product promotions for eachretailer

For Woolworths, the greatest number of promotions
were found on category pages (mean ± SD, 30.7 ± 0.1),
and the least on basket and checkout pages (no promotions identified across any location) (Additional File 4:
Supplementary Table 2). For Coles, the homepage displayed the greatest number of promotions (61.7 ± 7.1)
and basket and checkout pages had the least numberof promotions (0.3 ± 0.5). For both retailers, the mostcommon placement strategy was cross-promotions andrecommendations (Woolworths: 61.3% of total, Coles:
46.0%), followed by default product listings (Woolworths:
23.9%, Coles: 31.5%) and advertisements and site content(Woolworths: 14.8%, Coles: 22.4%).
The healthiness of placement product promotions
by area‑level socio‑economic position

Unhealthy products were more likely to be promoted in
low-IRSAD than high-IRSAD locations overall (unadjusted: 45% vs 43%, p = 0.05; adjusted by retailer: 45% vs
43%, p = 0.106) (Fig. 2). However, there were no statistically significant differences found by location within
retailers (Woolworths: low-IRSAD 44% v high-IRSAD
42%, p = 0.096; Coles: low-IRSAD 47% v high-IRSAD
45%, p = 0.270). Placement promotions per page, strategies applied and product healthiness across strategies

Maganja et al. BMC Medicine(2024) 22:341

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Fig. 2 Proportion of products promoted through prominent placement on the online stores of two retailers in Australia that were unhealthy(HSR < 3.5), by retailer and location. Error bars represent 95% confidence intervals. HSR, Health Star Rating; IRSAD, Index of Relative Socioeconomic
Advantage and Disadvantage

and pages were very consistent between both Woolworths’ high- and low-IRSAD stores and Coles’ highand low-IRSAD areas (results not shown).
The healthiness of placement product promotions for eachretailer

Coles was overall statistically more likely to promoteunhealthy products than Woolworths (unadjusted:
46% v 43%, p = 0.004; adjusted by location: 46% v 43%,p = 0.019) (Additional File 5: Supplementary Table 3).
This was the case for both low-IRSAD and high-IRSAD
locations (low-IRSAD: Coles 47% v Woolworths 44%,p = 0.05; high-IRSAD: Coles 45% v Woolworths 42%,p = 0.032) (results not shown).
By strategy, patterns were similar between retailers, with advertisements and site content most likely
to be unhealthy (Woolworths: 49.6% unhealthy, Coles:
58.5%), followed by cross-promotions and recommendations (Woolworths 43.6%, Coles: 43.3%) and default
product lists (Woolworths: 37.8%, Coles: 40.6%) (Additional File 5: Supplementary Table 3). Results differedby page, however. For example, in Woolworths’ online
store, the page type with the highest proportion of
unhealthy products was search results (47.0% of products unhealthy) and the page type with the lowest
proportion of unhealthy products was category pages(39.0%), while for Coles basket and checkout pages
were most likely to feature unhealthy products (100.0%
of products unhealthy) and product pages the least(41.7%).

Discussion
This study assessed the online stores of the two dominantsupermarket retailers in Australia and found that over
two-fifths of all products promoted through placement
strategies were unhealthy. While we identified differencesin the healthiness of promoted products by area-levelsocio-economic position and between retailers, the magnitude of differences were small. Across both retailers,
cross-promotions and recommendations was the mostcommon placement strategy, and advertisements and site
content were most likely to feature unhealthy products.
Results within retailers by area-level socio-economic
positions were very similar, suggesting that at the time ofcollection both retailers likely applied a similar approachto placement promotions in their online stores regardlessof customer location.
To our knowledge, this was the first study to investigate
placement strategies in Australian online supermarkets.
Overall, a typical start-to-finish shopping event would
likely result in a consumer being presented with a considerable number of unhealthy products, regardless ofretailer. Drawing explicit comparisons to studies conducted in physical supermarkets in Australia [20–23]
is difficult as consumer experiences of shopping andviewing the environment are fundamentally different inthese settings, thus methods to assess placement strategies are inherently different. However, as hypothesised,
we did find heavy promotion of unhealthy products
through such strategies overall. This is apparent whencomparing our results to that of a recent study of products available in Australian online supermarkets, with theMaganja et al. BMC Medicine(2024) 22:341

data presented indicating that 30% of all products would
score < 3.5 HSR [34]. An additional comparison can bemade between the distribution of HSRs for promoted
products in our study, where products scoring 0.5 HSR
were commonly promoted (14% of all placement promotions), to that recently seen for all products in Australian(physical) supermarkets, in which relatively few products(~ 7%) scored 0.5 HSR [43]; the heavy promotion of confectionery and sugar-sweetened beverages online likely
explains this contrast.
Similar to the findings here, recent research in-store
has found that the proportion of products promoted
through prominent placement that were unhealthy differed only marginally between Woolworths and Coles,
though diverging results were seen for other, smaller
chain and independent retailers [21–23]. Our findings on
differences by area-level socio-economic position, while
not conclusive, do not contradict other evidence on thepotential differential promotion of unhealthy products
according to location in physical stores in Australia; theinclusion of additional ‘stores’ (locations) in subsequentstudies of online food retail environments may help
explore this potential effect further. One study foundthat island bins near checkouts and elsewhere in store
were 14.1% and 15.6% more likely, respectively, to display
unhealthy food in stores in the most disadvantaged areas
compared to stores in the least disadvantaged areas [22],while another found an additional 9.7% of shelf space wasdedicated to unhealthy products in the most disadvantaged areas compared to the least disadvantaged areas[23].
In our study, the differential promotion of unhealthy
products through place-based strategies by location
seems to be less apparent in online settings. However,
online environments have other novel and unique features such as personalised marketing [14], which were
not considered in our assessment but may play a key rolein exposure to unhealthy placement promotions online.
This may be particularly important in light of associations between socio-economic position and diets in Australia [44, 45]; our limited findings regarding differencesby location may result from not capturing personalised
marketing of unhealthy products that is tied to tracking of regular shopping patterns and other internet use.
Future research could capture product placement promotions following the intentional, repeat collection of representative selections of products, according to patterns
seen in Australia by socio-economic position, to better
investigate potential personalised and differential marketing. Alternatively, actual use by representative samples
of consumers could be recorded, which would also facilitate the identification of ‘typical’ online grocery shopping
experiences; we discuss this in more detail below.

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Internationally, there has been limited research conducted into the use and healthiness of placement strategies in online supermarkets, with methods varying
considerably. A study of 21 retailers in the United Statesof America found that placement strategies, similar
to those assessed in the current study, were commonand frequently applied to unhealthy products with, forinstance, 60% of all products promoted through recommendations classified as unhealthy [24]. An English study
found, across three large retailers, that 73% of products highlighted on homepages were unhealthy [46].
Unhealthy products constituted 21.6% of total non-monetary (i.e. placement-based) promotions across a range ofmarketing strategies and pages in a survey of six online
supermarkets in Scotland [19].
Interestingly, this Scottish study found that placement
promotions were more common than promotions involving pricing, with the authors hypothesising that the former are more important than the latter online as “[w]hile in a physical store, a shopper can see many products on a shop’s shelves, even if they are not promoted,
an online shopper will only see a product if it appears on
the website (and therefore is promoted), or if they specifically search for it. Therefore, placing promoted goods ona grocery retailer’s website in areas that shoppers must
visit while shopping online (i.e. main page, product landing pages or checkout) is a logical strategy” [19]. Thissuggests the critical importance of understanding, identifying and addressing placement promotions online, as
well a future line of inquiry to understand the relative
or combined application of price and placement promotions in Australian online supermarkets. Findings froman earlier study of price promotions in an Australian
online supermarket [47] cannot be directly compared toour results due to considerable differences in methodologies, highlighting the need for further research and methodological development to investigate both pricing andplacement strategies.
We have found that a considerable proportion of products prominently located in the default order of category
pages and search results were unhealthy. Whether theplacement of some or all of these products is paid for is
unknown, though there is evidence of this practice inphysical stores [48]. Other relevant drivers may be sales,
profit margins or novelty, rather than the healthiness of
products per se; regardless, the outcome remains of primary concern to us. However, the potential diversity ofpromotional strategies, coupled with our findings which
do not indicate common priority locations or strategies, suggests that any restrictions on unhealthy productmarketing online must be comprehensive to ensure that
products are simply not promoted through other strategies. Multi-faceted government policies that consider

Maganja et al. BMC Medicine(2024) 22:341

not just advertisements and other overt product placement, but also other strategies (e.g. how default productlists are set), may be required to control the promotionof unhealthy products in online food retail environments. Regulation to restrict placement promotions of
unhealthy products, explicitly including online settings,
came into force in England in October 2022 [49] and isalso being considered by the Scottish Government [50].
These are a good first step, with the English regulation
intending to limit the display of certain products acrossa range of locations in online supermarkets (e.g. homepages and other equivalents of high-traffic in-store locations such as checkouts and aisle ends) [49]; noting thatstudies assessing the impact of this policy are not yet
available. However, in a clear attempt to navigate issues
with the need to intentionally display products to consumers in online stores (as opposed to shoppers being
able to walk past all products available on shelves instore), considerable exemptions have been set, highlighting difficulties when considering options to protect andsupport consumers in online food retail environments.
An alternative to regulation of promotions by locations
and/or strategies could be the mandatory display of relevant front-of-pack nutrition labelling, though existinglabelling-based strategies may not prove effective in thecontext of online shopping as they may not be visible on
or applicable to the promotions identified here and could
be circumvented by adding products to cart directlyfrom listings or other promotions [34]; a potential solution could be to require a relevant summary indicator ofhealthiness to be clearly visible in all instances where theproduct is displayed online.
While some of our approaches correspond, even if
roughly, to other assessments of placement promotions
in-store and online, we have also developed and tested
novel methods through this study. It is, to our knowledge, the first study to specifically look at the healthinessof default product listings, in addition to more obvious
placement promotions. We have also set out a broader
methodology for conducting a comprehensive, detailed
assessment of a range of pages and strategies online.
Repeat assessments of the online supermarkets assessedin this current study and evaluations in other countries
will provide further context to the findings reported
here and support benchmarking and accountability
mechanisms.
Strengths of our study include the use of multiple collections, which led to the identification of thousands of
relevant product promotions. We have intentionallyminimised the impact of search and browsing history,
both within and outside of the online supermarket, in
an attempt to control the influence of cookies, location tracking, previous purchases etc. and to facilitate

Page 9 of 12

comparable collections in what can be a rapidly changing
environment; noting however that additional or residual
tracking remains a possibility (via, for example, devices,
users and networks), and the approach we have taken
may also be considered a limitation (see below). The
use of pre-set displays and products/categories similarly
aimed to enable a standardised and replicable collection. Finally, this study used data from the two duopolistic supermarket retailers in Australia, likely representing
most Australian online grocery shoppers at the time.
There are also some limitations to our study. These arepartly to do with the representation of a ‘typical’ online
shopping experience and reproducibility of results. For
example, some promotions may change according tosearch, browsing and purchase history, while using online
supermarkets in other formats (e.g. mobile app) and/orwith different display settings (e.g. larger/smaller computer screen) is likely to alter what is seen on-screen.
Furthermore, the online environment changes rapidly, whether week-to-week, day-by-day, or even with arefresh of the screen; this may be mitigated somewhat in
our study by the use of multiple collections over multiple
locations and days, and our study does provide a general
representation of the online supermarket at a point intime. In addition, results of analyses of the prevalence ofstrategies should be interpreted with caution, as these areinfluenced to some extent by our methodology.
As such, our study is unable to suggest what a hypothetical typical user would be presented with acrossa typical shopping event; to some extent, this is dueto the novelty of this research and a lack of supporting
data regarding online shopping behaviours to inform themethodology. Rather, we have simply captured the prevalence of strategies, their location, and their application
to unhealthy products. This also means that reproducibility for duplicate or subsequent collection is extremely
difficult; the use of a sole data collector in this study is
acknowledged as a limitation given the potential forbiases or errors to be introduced. The current analysis
also cannot indicate the association of placement promotions with actual purchases and intakes, though it canbe presumed that the promotion of products by retailers
is intended to influence purchases [48]. While audits ofthe prevalence of certain features of food environments,
as per our methods, are a standard approach to assessing the healthiness of food environments [51], we suggest as a priority for future research an investigation of
the typical, actual display of placement-type promotions
in online supermarkets, and potentially the influence ofsuch displays on purchases, using data collected by or via
regular online grocery shoppers; screen-recording may
be a viable approach [52–54]. This would also assist with
providing evidence on the categories most commonlyMaganja et al. BMC Medicine(2024) 22:341

browsed or purchased online in Australia, which may
inform improvements to the methods applied in thisstudy and particularly decisions regarding the inclusionof product and/or category pages.
Additionally, though the use of HSRs as a categoricalarbiter of healthiness has been used in multiple studies[39, 55, 56] and in government guidelines [57] to categorise food according to healthiness, and is applied byAccess to Nutrition Initiative to assess company portfolios globally [58], the approach is also contested as thecalculation of a summary output that balances ‘negative’and ‘positive’ components may result in ultra-processed
products and/or products with high levels of added
sodium, unhealthy fats and sugars receiving high scores[59]; further research in this area may need to consider
other or additional food classification systems relevantto the Australian context. Finally, the use of yet moresophisticated and covert strategies such as artificial intelligence-driven ‘dark nudges’ [18] may be far more common than outsiders can reveal, including through thepresent assessment. Further investigation of strategies
that rely on personalisation may assist to uncover someof these practices, while consideration will also need to
be given to the matter of identifying the extent to whichalgorithms and artificial intelligence are embedded andinfluential within retail settings.

Conclusions
Novel methods for assessing placement strategies inonline supermarkets have been developed and tested. We
have identified that consumers are likely presented witha considerable number of prominently placed unhealthy
products when shopping in the online stores of the twoleading supermarkets in Australia. Comprehensive public health policies that cover a range of placement promotional strategies should be considered to ensure thatonline food retail environments do not exacerbate existing trends toward unhealthy dietary patterns and dietaryinequalities.
Abbreviations
HSR	Health Star Rating
IRSAD	Index of Relative Socioeconomic Advantage and Disadvantage

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12916-​024-​03557-y.
Additional file 1: Supplementary Fig. 1. Example of product placement
strategies assessed on different online supermarket pages, including A:
homepage, B: category pages, C: search result pages, D: product pages,
and E: basket and checkout pages
Additional file 2: Supplementary Table 1. Products used to assess placement strategies on product pages

Page 10 of 12

Additional file 3: Supplementary Fig. 2. Distribution of Health Star Ratingsfor all food products eligible for a HSRpromoted through prominentplacement on the online stores of two retailers in Australia, all storessearched.
Additional file 4: Supplementary Table 2. Placement-based food productpromotions on the online stores of two retailers in Australia, all storessearched.
Additional file 5: Supplementary Table 3. The healthiness of food products
promoted through prominent placement on the online stores of two
retailers in Australia, all stores searched.
Acknowledgements
Not applicable.
Authors’ contributions
DM and JHYW conceived the study. All authors contributed to the study
design. DM collected and analysed data. DM, TD, CG-D, TS, AJC, JCYL, MDH,
KT and JHYW contributed to the interpretation of results. DM led the initial
drafting of the manuscript and all authors contributed to subsequent drafts.
All authors read and approved the final manuscript.
Funding
DM was supported by an Australian Government Medical Research Future
Fund Cardiovascular Health Grant (MRF1200105) and an Australian Government Research Training Program Scholarship. The funders had no role instudy design, data collection, analysis or interpretation, or preparation of themanuscript.
Availability of data and materials
The data that support the findings of this study are available from The George
Institute for Global Health but restrictions apply to the availability of these
data, which were used under licence for the current study and so are notpublicly available. The data are, however, available from the authors upon
reasonable request and with the permission of The George Institute for Global
Health.

Declarations
Ethics approval and consent to participate
Not applicable as our study did not involve the use of any animal or humandata.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1
The George Institute for Global Health, University of New South Wales,
Sydney, Australia. 2 School of Rural Medicine, Faulty of Medicine and Health,
University of New England, Armidale, Australia. 3 Global Centre for Preventive
Health and Nutrition, Institute for Health Transformation, Deakin University, Burwood, Australia. 4 Department of Nursing and Allied Health, Schoolof Health Sciences, Swinburne University of Technology, Melbourne, Australia.
5
Cardiovascular Division, Global Health Center, Washington University in St.
Louis, St. Louis, USA. 6 School of Population Health, Faculty of Medicine &Health, University of New South Wales, Kensington, Australia.
Received: 24 January 2024 Accepted: 12 August 2024

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