Attractive displays can stimulate sales in the retail setting. With most plants still sold in physical retail outlets, the influence of display layout on visual behavior and purchasing is of interest to academicians and practitioners. Using a within-subjects in-lab experiment and eye tracking technology, we explored how the cognitive load imposed by horticultural retail displays affects visual attention and choice. Display layouts were varied for six choice tasks in which participants indicated their most preferred alternative and their likelihood-to-purchase that alternative. Our study suggests that as the number of plant genera increases, perceived display complexity increases, and participants ignore a larger percentage of the products in the display while spending a lower percentage of their gaze sequence fixated on their choice product. Implications for retailers include increasing horizontal merchandising, reducing vertical merchandising, and diversifying the product mix in the display.

Index words: cognitive load, eye tracking, marketing, retail displays, complexity.

Species used in this study:Buddleia davidii Franch. Little Nugget', Campanula portenschlagiana Resholt (Roem. & Schult.), Coreopsis grandiflora L. Sunburst', Echinacea purpurea Moench Delicious Candy', Hydrangea paniculata L. Limelight', Lupinus spp. L. ‘Tutti Fruitti', Sempervivum cv. L, Spirea japonica L. ‘Double Play Red'.

#### Sample characteristics

Participants were 28.9% male and 71.1% female with a mean age of 30.2 years (s.e.=1.0). Nearly half (40.2%) had completed a four-year college degree with 23.1% having less education and 36.7% having more education. The sample was predominately Caucasian (57.7%) with Asian (17.5%), African-American (9.3%) and other ethnic heritages (15.5%) comprising the remainder of the sample. Median household income fell into the category of $60,000 to$79,999. Purchases of plants were made by a majority of the sample, including herbs (purchased by 65.0% of the sample), vegetables (46.4%), indoor plants (43.3%), flowering annuals (38.1%), flowering perennials (25.8%), flowering shrubs (20.6%), and other plants (23.9%) spending an average of $79.50 (s.e.=$9.63) on plants in the three months prior to the study. Thus, the sample was representative of plant purchasers in the Midwest.

#### Visual non-attendance

The average VNA for the 18 plant displays ranged from 9.97% to 19.97% (Table 2), indicating plant number was not the only signal of VNA, in contrast to Staples et al. (2021). The lowest VNA was for the three genera perennial display merchandized in a horizontal layout where each tier contained a different plant genus. One potential explanation for the low VNA is that horizontal marketing is easier for participants to visually process. Indeed, the display with the greatest VNA (19.97%) was the two genera perennial display using vertical merchandising (side-by side placement). The large and statistically significant difference between VNA levels supports the argument that vertical marketing is more cognitively taxing than horizontal marketing (Deng et al., 2016). We saw a similar trend for the two- and three-genera shrub displays, but the difference in means was not significant at the 10% level.

Table 2

Mean visual non-attendance (VNA) or the percent of all plants ignored, the position of plant with greatest VNA percentage in each display (n=97 participants), and the percentage of the gaze sequence devoted to each shelfz. Display identification number shows number of plants (12 or 18), display layout (H=horizontal, V=vertical), number of genera (1, 2, 3), and whether the display is comprised of perennials (P) or shrubs (S).

The plant with the greatest VNA was a corner in all six displays (Table 2), with the bottom-right corner ignored to the greatest extent (50.2%) for the two-genera shrub display (18V2S). Across all six displays, the three AOI locations with the highest VNA rates were in the corners or outer edge of the displays (Table 3), signaling that consumers' visual attention gravitated towards the center of the display. Indeed, while plants were not merchandised to the ground level, it was the center of the top and middle shelves that often had the lowest VNA rates. This finding is consistent with Atalay et al. (2012), which showed that visual attention moved to the brand located centrally in a horizontal array of movie titles and energy drinks, both of which were located on only one shelf. This finding expands their Central Gaze Theorem to include multiple shelves with both horizontal and vertical merchandising.

Table 3

Percentage of respondents (n=97) that never visually fixated on each area of interest (AOI) for each displayz. Display identification number shows number of plants (12 or 18), display layout (H=horizontal, V=vertical), number of genera (1, 2, 3), and whether the display is comprised of perennials (P) or shrubs (S).

Furthermore, the average TFD did not differ by shelf (average gaze time on each shelf top: 25.16%, middle: 24.99%, bottom 23.47%). Thus, placement of higher quality plants on a higher shelf may not produce the intended effect of a perception of higher quality. In the fast-moving consumer-goods (FMCG) arena, shelves at eye-level are more likely to be seen by consumers and thus command higher prices (known as slotting fees) from retailers to have the product merchandised there (Chiakpo n.d.). Results here are contrary to this and would indicate that consumers are paying more visual attention to shelves that are not necessarily at eye-level in order to make their product selection. Coupling our findings with the existing retail and marketing literature suggesting that product placement affects visual attention, and ultimately choice (Chandon et al. 2009), our insights on VNA have significant implications for retail display layout.

More complex displays—either through increasing the number of purchasing alternatives or introducing multiple genera within a display—could potentially impose a greater cognitive load on the consumer, leading to increased TTC. However, more visually appealing displays—using tiered layouts and employing horizontal marketing—could increase TTC for the average consumer without imposing a higher cognitive burden as the lower cognitive burden imposed by a more functional product display invites consumers to accept the higher search costs to find an optimal alternative. Retailers may want to utilize tiered displays with horizontal merchandising to capitalize on consumers' “reading” displays and ease of processing horizontally and increase to a modest extent, a limited number of products, perhaps 2-3, that might be effectively cross merchandised with the plants. These may be other plants, containers, or fertilizers. Horizontal striping would facilitate visual processing while limiting the number of additional products could increase purchase alternatives without substantially increasing cognitive load.

The literature on choice overload suggests that complex choice settings invite unintended consequences, where consumers may become less confident in their choice (Haynes 2009), regret their choice decision (Inbar et al. 2011), or refrain from entering the market entirely (Berger et al. 2007). As such, it is plausible to suspect that individuals who experience cognitive overload from the choice settings to opt-out more frequently or have a lower LTB.

The three-genera shrub display with 18 plants merchandised horizontally (18H3S) had the highest “no choice” or opt-out rate at 10.3% (10 participants), followed by the two-genera shrub display (18V2S) at 9.3% and the one-genus perennial display (12H1P) at 7.2% (Table 4). Only 1% of respondents opted-out of the two- and three-genera perennial displays, and these had the highest average LTB at 7.32 and 7.65, respectively. Because the experiment used different perennial plants and shrubs, lower opt-out rates and higher LTB to display layout could be driven by plant type or introducing variety in the display (i.e., multiple genera).

Table 4

Summary statistics by display ID showing time to choice (TTC), number of “no choice” selections, and mean likelihood to buy across all choices (n=97 participants). Display identification number shows number of plants (12 or 18), display layout (H=horizontal, V=vertical), number of genera (1, 2, 3), and whether the display is comprised of perennials (P) or shrubs (S).

Display opt-our rates could also be driven by consumer heuristics related to visual attention and cognitive processing. As the display complexity increases, the consumer could consciously or subconsciously choose to devote attention to fewer alternatives in the display. In doing so, they simplify their choice setting and may devote a larger share of their gaze sequence to the alternative that they eventually select. Staples et al. (2021) show how average VNA rates increase as the number of plants included in this display increase, and we see here that including multiple genera and using different merchandizing strategies can influence VNA rates. Thus, it is necessary to explore how time devoted to a given AOI affects choice and whether the time devoted to the selected alternative varies based on the complexity of the display.

#### Time devoted to choice and time to first fixation

Study participants, on average, chose the alternative that they fixated on the longest, a finding that coincides with much of the literature on visual attention and choice (Behe et al. 2015, Gidlöf et al. 2017, Reutskaja et al. 2011). Of the 547 observations (of 581) where a plant was selected, 81% of respondents (449 observations) fixated the longest on the alternative they eventually selected (Table 5). Moreover, participants tended to fixate on their selected alternative rather quickly, averaging their first fixation on the selected alternative within the first 25% of their gaze sequence, or, in this study, in approximately 4.6 seconds. However, we do see that as display complexity increases, it took longer for participants to have their first fixation on their selected alternative. For instance, it took an average of 7 seconds for respondents to have their first fixation on their choice alternative in the vertically merchandized, two genera, shrub display (18V2S).

Table 5

Summary statistics for choice by display ID for mean time to choice (TTC), mean time to first fixation (TTFF) of choice plant, mean percent of gaze devoted to choice plant, and the percentage odds that the plant with the greatest TFD was the chosen plantz. Display identification number shows number of plants (12 or 18), display layout (H=horizontal, V=vertical), number of genera (1, 2, 3), and whether the display is comprised of perennials (P) or shrubs (S).

The TTFF and TTC findings support much of the literature suggesting visual attention is a leading driver of purchasing behavior. The average consumer fixated the longest on the option selected, suggesting that visual attention is indeed an important indicator of purchasing behavior. Coupling this finding with the increased rates of VNA as display complexity increases suggests that for complex displays, a consumer may make a sub-optimal choice given that they are not considering all choice alternatives. However, the similar opt-out rates and LTB in this experiment suggest some ambiguity in this argument.

Even in the absence of time constraints, we saw consumers ignore a non-trivial share of the product displays; up to 20% for a vertically merchandised display. Indeed, this suggests that consumers sometimes cope with challenging choice scenarios by not looking at all the options. We demonstrated that as display complexity increases, so too does VNA. Furthermore, while visual attention is a leading indicator of choice, the percentage of a respondent's gaze sequence devoted to choice decreases as display complexity increases. However, participants' LTB was not strongly impacted by the increased display size and complexity despite higher rates of VNA and less time devoted to the choice product. In other words, they quickly found the desired product without examining all alternatives. Further, increased complexity led to heightened LTB on some occasions (e.g., display 18V2S versus display 18H1S).

Consumers can devote 31% to 40% of their product selection time looking away from the product set to assist in cognitive processing of information before deciding (Behe et al. 2020). Our results are consistent with participants' desire (if not need) to disengage from stimulus input to make a choice; they also support the notion that eye tracking measurements can be used as a sole indicator to predict choice (Chavez et al. 2018), where the most visually attended to alternative is chosen between 70 and 91% of the time.

ET technology enables us to explore the relationships between display complexity, visual attention, and choice. However, one shortcoming from using ET metrics is that visual attention does not imply cognitive processing. We capture participants' fixations on AOIs through the ET technology, but a positive fixation count on an AOI does not imply the participant could recall and may not necessarily indicate that the participant can recall visually attending to the alternative. In other words, the ET glasses are so light and comfortable, participants may forget they are wearing them. Furthermore, the technology is so accurate that participants may not remember they looked at a specific plant but the technology can track it. Nonetheless, our measurement of VNA serves as a lower-bound estimate of the percentage of the display a consumer ignores, as the share of the display a consumer does not cognitively process is at least as large as the VNA tracked by the ET software.

The other central limitation to our experiment is the possibility of hypothetical bias. While a binding experiment in which participants purchased their selected alternative would alleviate this concern, we believe that the non-binding nature of our horticulture study was a necessary condition to avoid introducing bias into the experimental design. That is, if participant i purchased plant x, then this plant would need to be replaced and thus it would bias the experimental design. Unlike processed food products with standardized labeling across identical alternatives, horticulture alternatives of the same genus are subject to heterogeneous product characteristics.

Future research might collect subjective measurements of cognitive load directly after each choice task to provide an avenue to better understand the role of working memory on the assessment of retail displays and help marketers mitigate adverse consequences from consumer heuristics in decision making. Future studies may also include other minimally packaged products (e.g., fresh produce) and inclusion of branded products as part of a choice heuristic would also be an interesting dimension for studying VNA.

Despite these shortcomings, this study has important implications for horticulture retailers where the tendency may be to develop complex displays. Display layout can mediate VNA and choice, where tiered displays may be more visually appealing to the consumer than flat displays, and horizontal marketing is a more visually appealing layout than vertical marketing, a finding that matches Deng et al. (2016). Display fixtures for vertical merchandising may carry added expense, but the investment may provide a fair return to create some visual difference from horizontal displays. Horizontal displays may have a greater labor expense to keep them stocked. More frequent merchandise stocking of perishable products may also reduce merchandise wear and tear (loss of foliage, for example), thus minimizing loss.

Practically, retailers will benefit by examining how their display layout reduces or increases the cognitive burden of their consumers. Vertical tiers are a practical strategy for merchandising horticultural products, offering shoppers easier visual processing compared to flat displays, particularly if the steps utilize horizontal marketing techniques.

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## Author notes

2

Professor, Department of Horticulture, Michigan State University.

3

Ph.D. Student, Department of Agricultural, Food, and Resource Economics, Michigan State University.

4

Professor, Department of Advertising and Public Relations, Michigan State University.

5

Assistant Professor, Department of Agricultural, Food, and Resource Economics, Michigan State University.