journal of shopper research flower power! · 2018-03-21 · snelders (2001) propose that pleasant...

By Elissa Moses, Laura Beavin, Lisa Zaval, & Kirk Hendrickson

FLOWER POWER!THE INFLUENCE OF AN IN-STORE GIFT ON EMOTIONAL AROUSAL AND SHOPPER BEHAVIOR

Marketers invest significant innovation and communication

effort across media channels to predispose consumers

to purchase, and yet the natural in-store shopping

environment remains underleveraged for motivating

consumers. The current research introduces a simple in-

store method of inducing a positive emotional response and

demonstrates its impact on a range of shopping behaviors

and perceptions. Results reveal that when shoppers

receive an in-person gift of a flower early in the shopping

experience, it significantly increases their emotional

arousal, reduces visual attention to price, boosts shopping

enjoyment, and improves touch-to-purchase conversion

rates, compared to shoppers who did not receive the flower

gift. These findings suggest an opportunity for retailers and

marketers to leverage environmental cues at the point of

purchase to improve shopper satisfaction and potentially

drive purchases.

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JOURNAL OF SHOPPER RESEARCH

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5www.journalofshopperresearch.com

INTRODUCTIONMarketers heavily invest in advertising across a variety of media channels to predispose consumers to purchase, but often neglect the potential of the in-store shopping environment to influence shoppers. Beyond standard point-of-purchase materials, such as coupons and displays, the in-store experience can serve as a communication and experiential channel in and of itself, and small changes in the physical surroundings can influence shoppers’ perceptions and behaviors. The literature suggests that uplifting emotional states can be readily influenced by retailers, and the positive emotions that are generated may drive multiple aspects of shopper behavior and decision making (Sherman, Mathur and Smith 1997; Watson and Spence 2007).

There is a need for research that links emotional experience and broader marketing and retail variables with useful predictive outcomes (Yoo, Park and MacInnis 1998). Neurophysiological and biometric approaches, including eye-tracking, skin conductance response, heart rate, and voice analytics, can complement traditional measures of consumer behavior by providing insight into the role of affect, arousal, and attention in driving complex consumer decision making (Venkatraman et al. 2015). Such methods, when combined with behavioral and attitudinal measures, help to address longstanding research questions regarding how uplifting in-store experiences impact consumers' emotional arousal, perceptions, and shopping behavior at the point of purchase. In the current research, we employ a range of neurophysiological, biometric, behavioral, and attitudinal measures to explore whether gifting a shopper with an unexpected flower gift can influence response frameworks for emotional arousal, boost shopper satisfaction, and improve shopping behavior with respect to visual price fixation, basket size, and total spending.

BACKGROUNDDecades of research have explored how pleasurable in-store sensory experiences influence shopper attitudes and behaviors. Store atmosphere has been shown to add value, impact spending, increase the amount of time spent in the store, raise the likelihood of future visits, and contribute to positive attitudes towards the store (see Spence et al. 2014). Individual store features, including lighting, color, music, scent, temperature, signage and layout have all been shown to have a positive effect on shopping behavior (e.g., Spence et al. 2014; Turley and Milliman 2000).

Extending this work on atmospherics, other research has explored how uplifting in-store experiences, such as rewarding shoppers with an unanticipated gift early in the shopping trip, can positively impact spending. Heilman, Nakamoto and Rao (2002) conducted an experiment in a grocery store where half of the shoppers were given a coupon for a product they were planning to buy. Results showed that receipt of the

unexpected coupon increased unplanned purchases and shopping basket size compared to shoppers who were not given a coupon. The authors speculate that the underlying mechanism driving the purchase effect was a more positive mood state; however, they did not measure whether consumers experienced a change in emotional state as a result of receiving the coupon. Thus, it remains unclear whether the effect of an unexpected gift on shopper behavior would extend beyond in-store discounts or incentives directly related to purchase.

Prior research suggests that hedonic aspects of the in-store environment can impact the affective emotional state of customers, which may then influence subsequent decision-making. Emotion refers to a relatively short-lived episode of coordinated brain, physiological, and behavioral changes that facilitate a response to a specific event (Davidson, Scherer and Goldsmith 2009). The outward expression of emotion is often classified into two affective dimensions: valence (positive or negative subjective

feeling) and arousal (physiological intensity), which can be measured via changes in physiological response, such as changes in heart rate, skin conductance, vocal characteristics, and/or facial expressions (Venkatraman et al. 2015). Consumers may experience a wide range of positive and negative emotions during the shopping experience (Ruth, Brunel and Otnes 2002), and accumulated evidence suggests that consumer emotion is sensitive to even subtle changes in the retail environment (Turley and Milliman 2000). For example, Yoo et al. (1998) demonstrated that when store personnel provide exceptional customer service, shoppers feel more content, excited, and attractive.

A robust body of research in marketing and psychology has also explored the effect of a consumer’s emotional state on shopping behavior, and findings suggest that positive emotions can influence what is purchased, how much is purchased, and intent to repurchase a brand or product (Babin, Dardin and Griffin 1994). For example, in a large field study that measured shoppers’ mood state using self-report questionnaires, Sherman

A robust body of research in marketing and psychology has ... explored the

effect of a consumer’s emotional state on shopping behavior, and findings suggest that positive emotions can

influence what is purchased, how much is purchased, and intent to repurchase

a brand or product .

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and colleagues (1997) found that feelings of pleasure were positively associated with money spent and store likability, while higher arousal levels (excitement) were associated with money spent in the store, time spent in the store, and the number of items purchased. DiMuro and Murray (2012) manipulated sensory aspects of the store environment (ambient music and scent) to prime changes in emotional valence and arousal levels. Results demonstrated that the level of arousal associated with a product or experience can impact purchase behavior. However, this study relied only on participant self-report to assess changes in arousal levels.

While a large body of research has explored the effects of positive emotions on shopping behavior, less attention has been given to the impact of directly improving customer well-being at the point of purchase. Scanner data analysis suggests that the distribution of product samples can boost short- and long-term sales (Chandukala, Dotson and Liu 2017), but it does not reveal the mechanism for this effect. Little has been done to scientifically isolate the measurable impact of an ecologically valid, emotionally uplifting cue on consumers’ physiological, attitudinal and behavioral response.

In the current experiment, the gift of a flower was selected as a means to induce an emotional response due to its universal symbolism as an expression of hospitality and appreciation. Indeed, prior research has confirmed that cultivated flowers may have a particularly powerful influence on people’s happiness. In a comparison of multiple pleasant stimuli, including candles and fruit baskets, Haviland-Jones and colleagues (2005) showed that flowers were most effective at inducing short- and long-term expressions of positive emotion. The authors suggest that the gift of cultivated flowers may be particularly rewarding because flowers have evolved to rapidly induce positive emotion in humans.

Other research provides insight into the way unexpected gifts may more generally enhance emotional experience and impact consumer choice (e.g., Valenzuela, Mellers and Strebel 2009). Specifically, Vanhamme and Snelders (2001) propose that pleasant surprises may increase customer arousal and the salience of positive emotion and satisfaction judgments in memory. However, it should also be noted that retailers’ attempts to use surprise gains to improve the customer experience can sometimes backfire. Recent research using a low-price guarantee context suggests that surprises related to bigger refunds than expected can lead to subpar outcomes if shoppers become suspicious about the intentions of the retailer (Dutta et al. 2017). A flower gift, which is not related to a monetary sales promotion, may side-step this issue.

Although much of the prior research on this topic has improved our understanding of how components of the retail environment affect

consumer behavior, experimental research on the effects of emotion has been hampered by two difficulties. First, it’s hard to objectively evaluate shoppers’ emotional arousal in a store environment, so the majority of research in this area has relied on participant self-report measures (e.g., DiMuro and Murray 2012), which may encourage response bias and be less appropriate in directly assessing experienced emotion ( Jaeger, Cardello and Schutz 2013). Although a number of approaches exist for measuring changes in consumers' emotional state and arousal, experimental research using neurophysiological measures of response is currently lacking. Our research advances our understanding of how an in-store cue influences complex consumer response by implementing a broader range of complementary measures, including eye-tracking, voice analysis and biometric approaches.

Second, in controlled experimental designs, subjects’ emotional states are often artificially induced using methods that are not ecologically valid, due to the difficulty and expense of manipulating elements of a real store setting. The current field experiment took place in an actual supermarket with consumers who shopped as intended and spent their own money. This research provides valuable insights for developing in-store marketing strategies and empirical evidence of the positive impact of in-store uplift (via a simple gift) to improve shoppers’ retail experience and drive purchase.

HYPOTHESESBased on prior research, we predict that providing a shopper with an unexpected flower gift will (1) measurably impact the shopper’s emotional response, increasing arousal; (2) positively affect purchasing behavior, specifically with respect to reduced attention to price, increased basket size, and increased total purchasing; and (3) enhance enjoyment of the shopping experience. A randomized between-group experiment was conducted in a grocery store to assess the effect of an unexpected flower gift on physiological markers of emotional response (using measures of heart rate and galvanic skin response), actual shopping behavior (using eye-tracking and behavioral measures), and customer enjoyment (using survey data and voice analytics).

METHODOLOGYA multi-modality approach using biometrics, eye-tracking, and behavioral science techniques was used to test the study hypotheses in a naturalistic grocery store setting.

PARTICIPANTS

A sample of 60 randomly selected participants between the ages of 18 and 65 were recruited at a Midwestern supermarket using an in-



store intercept paradigm. Participants were mostly female, with an even distribution across age groups. (Table 1 presents gender and age distributions by experimental condition.) Shoppers entering the store were approached and invited to participate in a shopping study in exchange for a $50 gift card to the store. Recruiters approached shoppers of all types, including those shopping with friends and families, as the goal was to mirror a naturalistic shopping experience to the extent possible. Shoppers were assumed to be familiar with the store, as it is one of the few groceries located in the suburban area where data were collected. Upon expressing initial interest, individuals were informed that if they qualified to participate, they would be fitted with equipment to track eye movements and physiology during their shopping trip. Those who agreed were then asked a series of screening questions to ensure they fit the target sample criteria (see Appendix A for a copy of the recruitment questionnaire). Those working in occupations related to marketing or marketing research, advertising, journalism, food and beverage manufacturing and grocery distribution or service were screened out to avoid biased results. Individuals with no major vision impairments, who reported at least shared responsibility for shopping, and who were shopping for one or more of the target categories (carbonated beverages, cereal and yogurt) were invited to participate. Not all shoppers intercepted expressed interest in participating; however, no data were maintained on the number of those who declined to be screened. Participation rate for those invited to take part after screening was 100%.

BIOMETRIC MEASURES

Biometric data were measured in this study as a marker of physiological arousal. Specifically, galvanic skin response (GSR) and heart rate (HR) data were collected using mobile biometric equipment developed by Shimmer Sensing (Shimmer Sensing, Dublin, Ireland). To record GSR, two Ag/AgCl electrodes were placed on the medial phalanges of participants’ middle and pointer fingers on their non-dominant hand. To record heart rate, an optical pulse sensor was clipped to the earlobe

corresponding with the side of the body where the other electrodes

were placed. All electrodes were attached to biophysical leads, which

logged data at a rate of 16Hz onto a small, lightweight Shimer3 GSR+

unit clipped into a wrist strap worn by the participant. Data were then

wirelessly transmitted to ShimmerCapture software on an Android tablet

for real-time recording.

The biometric technology in this study enabled us to track real-time

changes in physiological arousal of participants for the duration of their

shopping experience. Both GSR and HR are processes governed by the

body’s autonomic nervous system, which is implicated in unconscious

bodily processes, including emotional arousal, attention and motivation

(Mauss and Robinson 2009). Changes in these measures over time indicate

shifting emotional arousal and engagement, though they do not provide

information on emotional valence. Using these measures, we were able to

track changes in emotional arousal and engagement before and after flower

receipt, as well as track between-group differences in physiological changes

from baseline.

GSR AND HR PRE- AND POST-FLOWER RECEIPT

GSR and heart rate levels were tracked throughout the duration of the

shopping trip. For the experimental group, levels of GSR and HR averaged

for the three minutes prior to flower receipt were compared to levels of

GSR and HR averaged for five minutes following flower receipt.

GSR AND HR CHANGE FROM BASELINE.

Individual GSR and HR change from baseline was also quantified and

then averaged across the experimental and control groups. Given the

goal of maintaining a natural experience, resting biometric baselines

were not collected for the shoppers. Instead, individual baselines for

the study were quantified by averaging the lowest 10% of data collected

during data collection.

Table 1Gender and Age Distributions for the Flower and Control Samples

Gender Age

CellSample Size

(N)Females Males 18-24 25-34 35-44 45-54 55-64

Flower 32 87% 13% 0% 30% 23% 23% 23%

Control 28 75% 25% 7% 14% 25% 21% 32%

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EYE-TRACKING MEASURES

Eye-tracking data were collected using lightweight Applied Science Laboratories (ASL) mobile eye-tracking glasses. This approach was selected because mobile eye-tracking is considered a useful and generally non-intrusive method for tracking consumer behavior in more naturalistic settings (Meissner, Pfeiffer, Pfeiffer and Oppewal 2017). The eye-tracking glasses have an appearance similar to standard safety glasses, but have two small cameras attached to them, as well as a small clear disc in front of the right eye. One camera points forward and records a video of the participant’s eye, which is reflected back by the clear disc, while the second camera provides a view of what the participant sees (POV camera). A cable connects the glasses to a small, lightweight DVCR recorder, which fits into a small backpack worn by the participant. For each participant, the glasses were fitted to the individual and calibrated using a 5-point chart before the shopping session began.

The eye-tracking technology used in this study created video which, upon playback, displayed crosshairs indicating precisely where the shopper was looking with respect to shelves, signage and anything else that came into view. This video enables the analysis of a set of variables related to shopping behavior, including shopper path, time spent in aisles, product touch to purchase conversion (proportion of purchasing vs. rejection once an item is picked up from the shelf ), and price and product fixations.

Individual shopper paths were identified qualitatively for each participant using the shopper’s POV video, and all were then overlaid to create an aggregate shopper path. This approach has an accuracy of +/- 2 feet with respect to each location assessed on the shopping trip. Time spent in aisles was also identified qualitatively for each participant using a time-tracking system linked to the shopper’s POV video. For price and product fixations, which reflect the quantity and length of time individuals fixate on price tags or products on the shelves, the spatial tolerance on fixation was +/- 0.5 degrees, and the minimum cutoff for fixation was 160 ms.

BEHAVIORAL MEASURES

Following completion of their shopping trip, and upon return to the conference room, shoppers’ receipts were photographed and inventoried to track behavioral data on items purchased and amount of money spent. The total quantity of items purchased during the shopping trip was tabulated from shopper receipts. Total basket dollar spend reflected the amount of money spent during the shopping trip, which was gathered from the shopper’s receipt.

SHOPPING EXPERIENCE MEASURES

Perceptions of the shopping experience were recorded using a post-shopping survey, where participants were first asked to verbally respond in detail to a set of questions about their shopping experience (e.g., “Please tell us about your shopping experience today. Did you enjoy shopping at this store? Why or why not?”). Verbal responses to the questions were recorded using the voice memo recording app on an Android tablet for later voice analysis. Participants also answered additional closed-scale questions via pen and paper about their shopping experience, purchase behavior, and demographic information (see Appendix B for the post-shopping survey).

The post-shopping survey was designed to evaluate shopper satisfaction and enjoyment. The survey assessed how the shopper felt both during and after his/her shopping trip, and also provided context for interpreting shifts in physiological arousal. Participants were asked to rate their enjoyment of their overall shopping experience on a 5-point Likert-style scale, where 1 = ‘Not enjoyable at all’, 3 = ‘Somewhat enjoyable’, and 5 = ‘Extremely enjoyable’. Additionally, shoppers reported whether they shopped in nine store categories, including cereal, produce, meat / seafood, dairy, frozen, carbonated beverages, deli, wine, and floral.

VOICE ANALYTICS MEASURES

Voice analytics were conducted on the verbal responses collected during the post-shopping survey. Recordings of the research participants discussing their shopping experiences were analyzed using Emotions AnalyticsTM software (Beyond Verbal Communication, LTD, Tel Aviv, Israel), which uses AI to evaluate unconscious vocal modulations to evaluate shopper emotions (arousal and valence).

In the current study, this technology analyzed the extent to which participants expressed high vocal arousal (excitement) and “embracive” (positively-valenced) emotion while describing their shopping experience. Arousal measured by voice analytics is a measure of the speaker’s degree of excitement and alertness. Low levels of arousal are common in cases of sadness, comfort, relief, and sleepiness, while high levels are registered in cases of excitement, surprise, and passion about a topic. Embracive emotion is a measure of the extent to which a person’s vocal modulations reflect a happy, friendly and embracing demeanor. Low scores on this dimension correlate with more gloomy or depressive expressions. The Emotions AnalyticsTM software measures a speaker’s vocal arousal and embraciveness on a continuous scale of 0 (low arousal and embracive emotion) to 100 (high arousal and embracive emotion).



PROCEDURE

Data collection took place between 9:00 am and 7:30 pm across four consecutive days (Friday through Monday) during late summer. Data collection times were mutually agreed upon with the store and aimed to target the busiest shopping times as reported by the store. Matching experimental/control sessions were also conducted across dayparts to prevent bias.

All study participants were first led to the store’s conference room for biometric equipment fitting and calibration. Participants were set up with eye-tracking glasses and calibrated using a 5-point chart, which took about two minutes per shopper. During this time, each participant tried on the eye-tracking glasses and the technician made any necessary adjustments to the cameras in order to get clear images of both the participant’s eye and their point of view (POV). For calibration, the numbers on the calibration chart were called off, in sequence, three or more times to ensure the crosshairs on the video were accurately corresponding to the person’s gaze.

Next, each participant was outfitted with the biometric device. A technician placed a wristband on the participant’s non-dominant wrist and electrodes on the medial phalanges of the first and middle finger on the same hand. If necessary, sensors were adjusted or moved until clear signals were being captured from the device. Finally, the device’s tablet recorder was held up to the eye-tracking POV camera to capture the start of recording biometrics, so that the data could be properly synced for analysis.

Next, participants were led to the store’s entrance, and were instructed to go about their shopping trip as planned upon arrival. To minimize chances of participants interacting with one another, only one participant fitted with equipment shopped the store at a time. Once a participant reached the check-out location, the next participant was led to the front of the store to begin their shopping session. Upon completion of their shopping trip, participants checked out, and then returned to the conference room to take the post-shopping survey.

A final calibration was completed with the eye-tracking equipment, and the end of the biometric recording was logged for data syncing. All eye-tracking and biometric equipment were then removed, and participants were asked to provide their shopping receipt for study documentation. Participants were then taken to a corner of the room and instructed to complete the first six survey questions, which required verbal responses. After confirming the

Figure 1Store “Host” Distributing Flowers to Research Participants in the Experimental Condition

participant understood the instructions, the experimenter began recording using the

voice memo tablet app. Participants responded in private, without the experimenter

present. Upon completion of verbal responses, the recording was stopped, and

participants were asked to complete the rest of the survey via pen and paper.

MANIPULATIONS

Participants were assigned to either the experimental or control condition in rotated

blocks, to ensure equal distribution of experimental and control participants across

different days as well as different dayparts.

The experimental condition differed from the control condition in only one respect:

the 32 participants in the experimental group were unexpectedly handed a brightly

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colored Gerbera Daisy, which was given to them by a male store “host” as they entered the soft drink aisle. The host was scripted to say, “Today we are giving out flowers in honor of customer appreciation at [name of store]” (see Figure 1).

RESULTS

BIOMETRIC MEASURES

To prepare for analysis, data were first cleaned and processed to identify key metrics. The Matlab-based software Ledalab (Graz, Austria) was used to clean and transform the GSR waveform. As a first step, data artifacts were visually diagnosed, and the GSR curve was reconstructed via interpolation between bounding data. Next, a 2Hz low-pass filter was applied to remove noise due to shopping movement. Data were then square-root transformed to adjust for the natural presence of skew that occurs with this data. Finally, data for each participant were normalized for comparison, and the average GSR value was added back to normalized data for reporting to aid in interpretation.

During data collection, the ShimmerCapture software automatically extracted HR in the form of beats per minute (bpm). Data artifacts were diagnosed as falling below the threshold of 50 bpm or above 130 bpm. The HR waveform was reconstructed via interpolation between bounding data.

To assess whether receiving a flower had a physiological effect on individuals in the experimental condition, a paired t-test was used to compare means for levels of HR and GSR three minutes before flower receipt, as well as three and five minutes after flower receipt. Figures 2 and 3 depict the GSR and HR waveforms during this period. Due to small sample sizes in the experimental and control groups, a more liberal 90% confidence interval was used to evaluate comparisons. Results from

1.4

1.5

1.6

1.7

1.8

1.9

2

Flower Receipt

-3 min +5 minPre-FlowerReceipt

Post-FlowerReceipt

Note: Galvanic skin response data demonstrates the flower gift significantly increases consumer arousal; receiving a flower increases skin conductance (.3%, 90% CI), which continues to increase five minutes later, compared to controls. Note: Skin conductance has been transformed to adjust for natural drift that occurs over time.

Figure 2Skin Conductance Pre- and Post- Flower ReceiptGSR Response Over Time

Skin Conductance Average Throughout In-Store Experience

89.5

90

90.5

91

Post-FlowerReceipt

+5minFlower Receipt

Pre-Flower Receipt

-3min

Note:. Heart rate as measured in beats per minute (BPM) shows significant variation, making direct patterns following flower receipt difficult to discern; however, when HR is compared to baseline for both groups, those in the flower condition show larger increases from baseline compared to those in the control group.

Figure 3Heart Rate Pre- and Post- Flower ReceiptBPM Over Time

Heart Rate Average Throughout In-Store Experience



these comparisons demonstrated no significant increases in HR in the three or five minute period following flower receipt (M = 89.53 and 89.63 bpm, respectively) relative to the period before flower receipt (M = 89.62 bpm). This absence of change may indicate a lack of reaction to receiving the gift; however, it is also possible that navigating the store may have already increased HR for participants, making any gift-related shifts difficult to detect.

Results demonstrated a significant positive shift in GSR, with pre-flower levels being significantly lower (M = 1.59 μS, SD = .05 μS) compared to GSR three minutes (M = 1.78 μS, SD = .03 μS) and five minutes (M = 1.94 μS, SD = .08, μS) after flower receipt (both p < .05). Thus, levels of GSR tracked around the time of flower receipt provide evidence for a physiological effect of receiving the gift, while levels of HR did not.

One reason a difference in HR was not detected may be due to the highly individual and rapidly shifting nature of HR. To further explore whether this physiologic marker was impacted by receipt of the flower, we compared whether those in the experimental vs. control conditions had differing levels of change in physiology from baseline while shopping in the carbonated beverages aisle (where flower delivery occurred for the experimental group). Individual baseline HR was inferred by averaging the bottom 10% of each participant’s data. Individual percent change values were created by computing the difference between baseline and average HR levels while shopping this aisle, and then dividing by baseline levels. Results from an independent-groups t-test showed that those who received a flower had a higher percent increase from baseline in HR while shopping the carbonated beverages aisle

* p < 0.05

Table 2Behavioral Response for Those Receiving a Flower vs. Control

CellSample Size (N)

% Eye Fixations on Product vs.

Price

Touch-to-Purchase

Conversion

Basket Size (# of Items)

Amount Spent

Flower 32 96%* 80%* 33 $91.61

Control 28 89% 67% 27 $87.14

+ p < 0.10, ** p < 0.01

Table 3Attitudinal and Emotional Response for Those Receiving a Flower vs. Control

CellSample Size (N)

Shopping Enjoyment (5-pt Scale Rating)

Excitement (Voice Analysis)

Embracive (Voice Analysis)

Flower 32 4.24+ 47** 52**

Control 28 3.89 33 36

(24.90%) compared to those who did not receive a flower (17.23%, p < .10), providing further evidence to suggest the flower gift had a general physiological effect on shoppers (Figure 4).

EYE-TRACKING AND BEHAVIORAL MEASURES

Eye-tracking data collected while participants shopped the carbonated beverages, yogurt and cereal aisles were combined to analyze attention paid to price and product. Fixation data in the areas of interest were analyzed by quantifying frequency of fixation and total fixation time. A z-test of two population proportions was used to assess whether fixation on price vs. products varied for the experimental and control conditions. Results demonstrated a significant difference in fixation behavior (p < .05), such that flower receivers focused less on price tags and more on products (4% and 96%, correspondingly) compared to the control group (11% and 89%, correspondingly; see Table 2). We next explored whether flower receipt impacted touch-to-purchase conversion rate as recorded by mobile eye-tracking. Specifically, the POV camera was used to track the proportion of time each participant picked up an item for consideration (touch) and either placed the item in their cart (conversion) or returned the item to the shelf (non-conversion). A z-test of two population proportions was then used to compare whether touch-to-purchase conversion rate differed for the experimental vs. control group. Results from this test demonstrated that those who received a flower displayed a significantly higher conversion rate (80%) for products that were touched, compared to the control group (67%, p < .05). Thus, those who received a flower were more likely to purchase a product they were considering than those who received no flower.

As an additional behavior-tracking method, the total number of items purchased and total shopping trip spend were recorded from

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participants' receipts. An independent-groups t-test was used to compare

these metrics across the experimental and control groups, and results

demonstrated no significant differences (p > .10). While between-groups

differences on these metrics were non-significant, basket size and total spend

were directionally larger for those receiving the flower versus not (M = 33

and 27 items purchased, and $91.61 and $87.14 spent, respectively). See

Table 2 for a summary of eye-tracking and behavioral measures.

Finally, general shopping behaviors were compared, including

average shop time and proportion of those who shopped certain store

categories. An independent-groups t-test demonstrated no significant

difference in time spent shopping for those who received a flower

(M = 21.9 min, SD = 11.5 min) vs. those who did not (M = 28.9

min, SD = 10.5 min, p > .10), suggesting the length of time spent in

store was unaffected by flower receipt. Further, z-tests of proportions

demonstrated no significant difference across groups in proportion of

those who shopped across the nine store categories (all p > .10).

ATTITUDINAL AND EMOTIONAL RESPONSE MEASURES

The final outcome variables assessed in this study included attitudinal and

emotional response measures. Shoppers’ perceptions of their shopping

experience were measured by asking participants to rate how satisfied they

were with their shopping experience that day on a 5-pt scale. Results from an independent-groups t-test comparing average shopper rating revealed a favorable impact of flower receipt on shopper perceptions, such that those who received a flower rated their experience as more enjoyable (M = 4.24, SD = 0.62) compared to those who did not (M = 3.89, SD = 0.84, p < .10; see Table 3). Additionally, data were coded into a top-2-box score to represent the proportion of the group selecting either 4 or 5 with regards to their level of enjoyment while shopping. A z-test of two population proportions demonstrated that this top-2-box value was significantly higher for those who received a flower (91%) vs. those who did not (75%, p < .05). Thus, flower receipt was linked to an increase in self-reported enjoyment of the overall shopping experience.

Finally, voice characteristics were analyzed as participants responded to questions about their shopping trip in order to assess the types of emotions experienced. Emotions AnalyticsTM software analyzed a speaker’s vocal arousal or “excitement” and level of “embraciveness” on a continuous scale of 0 (low arousal and embracive emotion) to 100 (high arousal and embracive emotion). An independent-samples t-test compared vocal arousal for the groups, and results demonstrated a highly significant difference in the extent of arousal verbally expressed by participants in the experimental and control groups. Those who received a flower while shopping expressed higher average levels of excitement and enthusiasm in their voice (M = 47, SD = 16.6) compared to those who received no flower (M = 33, SD = 14.7, p < .01).

An independent-samples t-test was also used to compare the extent of embraciveness expressed by each group when describing their shopping experience. Those who received a flower expressed a higher extent of embracive emotion (M = 52, SD = 20.2) compared to those in the control group (M = 36, SD = 17.19, p < .01). These results suggest that participants who received the flower gift had a more positive demeanor compared to those in the control group (see Figure 5).

GENERAL DISCUSSION AND IMPLICATIONSUsing a multi-method experimental protocol, the current research evaluates a new approach for influencing shopper perceptions and behavior at the point of purchase. The study reveals that giving the gift of a flower early in the shopping experience significantly boosts the shopper’s emotional arousal, reduces visual attention to price, improves shopping enjoyment, and increases touch-to-purchase conversion rates, compared to the no-gift control condition.

These findings should encourage retailers and manufacturers to consider creative ways to improve emotion through possible “on the spot” emotional triggers

Note: Heart rate while shopping the carbonated beverages aisle (where flower was distributed) had a significantly larger percent increase from baseline for the experimental group compared to the control group. Specifically, flower receivers showed a 7.7 percentage point larger increase from baseline than the control group. Note: Baseline was calculated as the bottom 10% of the data. *indicates signficance at 90% CI

Figure 4Heart Rate (BPM) While Shopping in the Carbonated Beverages Aisle

Per

cent

Cha

nge

from

Bas

elin

e

0%

5%

10%

15%

20%

25%

30%

Control Group Experimental Group(Flower)

17%25%*



related to promotions, product trial, or sensory experience. Given that the gift of a flower reduced price fixations, there may be an opportunity to leverage emotion to combat price sensitivity and help support premium brands. Improving the emotional experience at the point of purchase is a potentially cost-effective method for raising shopper satisfaction and increasing overall spending.

Retailers have long practiced various approaches for showing hospitality and providing emotional uplift for customers. Some stores offer small gifts to shoppers, including product samples, free products, or edible treats (see Chandukala, Dotson and Liu 2017). For example, Macy’s often provides unannounced in-store rewards to consumers, and has given both chocolates and even gift cards to shoppers during holiday seasons. Marketers know that these uplifting experiences have the potential to enhance shopper satisfaction and customer loyalty, and yet little has been done to scientifically isolate the physiological and emotional responses of shoppers to such practices.

The present research demonstrates that the tactic of giving a simple, inexpensive gift at retail can have positive effects on shopper behavior. This is important, as traditional brick-and-mortar retailers have begun to embrace various expensive, high-tech innovations to engage customers, such as digital signage and mobile apps (Grewal, Roggeveen and Nordfält 2016). Indeed, recent research on the effects of digital factors in retail suggests that more complicated, costly digital display technologies can sometimes interfere with customers’ focused shopping in smaller stores, resulting in a reduction in sales (Roggeveen, Nordfält and Grewal 2016).

And yet, opportunity abounds to easily and efficiently alter the retail experience in order to heighten consumer emotions, boost shopper enjoyment, and improve sales.

LIMITATIONS AND FUTURE RESEARCH AVENUESWhile we tried to create as natural a shopping environment as possible for this field experiment, aspects of the research design may have detracted from participants experiencing a true natural shopping experience, such as being outfitted with eye-tracking and biometric devices. Additionally, although only one experimental participant was outfitted with biometrics at a time, we did not control for whether experimental participants interacted with other shoppers in the store. Future research using similar methods to assess shopping behavior could address these confounds by considering use of virtual reality settings (Meißner et al. 2017), which could allow for more control of interfering variables.

Additionally, the sample size used in the current experiment was relatively small, and may have limited our ability to identify significant differences between conditions (particularly those relating to purchase behavior). Future research should aim to replicate this study with a larger sample to test whether receipt of an unexpected flower gift, or other emotionally uplifting stimuli, can significantly influence sales.

With the current research design, we are unable to confirm a change in consumers’ emotional valence in direct response to flower receipt. Biometric measures such as GSR and HR can measure emotional arousal, a critical component of affect (e.g., DiMuro and Murry 2012), but cannot confirm whether the valence is positive or negative, or neutral. Although prior research suggests that cultivated flowers are effective at inducing positively valenced emotion (Haviland-Jones et al. 2005), future research might consider surveying consumers immediately after receipt of the flower in order to assess the type of valence experienced.

Follow-up research is needed to explore and identify the potential underlying mechanisms responsible for the present findings. Multiple psychological processes may potentially contribute to the observed effect of the flower gift on shopper behavior, including the possible roles of gratitude and reciprocal obligation associated with gifts and favors (Kolyesnikova et al. 2009), or the feeling of surprise associated with receipt of an unexpected reward (Vanhamme and Bont 2008; Heilman, Nakamoto and Rao 2012). Positive social interactions with in-store personnel have also been linked with positive consumer attitudes (Yoon et al. 1998), and this is another promising candidate. Each of these potential mechanisms would have different implications for the application of the current findings in real consumer settings.

Figure 5Group and Individual Shoppers in the Experimental Condition Exhibiting Positive Affect

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Further, the well-established aesthetic and symbolic value of the flower itself may have uniquely influenced consumers’ emotional responses and purchase behavior. Research in evolutionary psychology shows that flowers are particularly effective in promoting positive emotion (Haviland-Jones et al. 2005). Further work is needed to establish what exact meaning the flower gift has in the context of shopping in comparison to other gifts that retailers might use, such as product samples. This line of work could be further extended to explore customized gifting strategies for improving customer well-being linked to the context of individual categories and brands.

CONCLUSIONSEstablishing the impact of positive emotion-inducing stimuli on complex consumer affective response has remained a challenge for past experimental research. Technological innovation may be particularly useful in overcoming this specific challenge, as new methods of analysis, such as biometrics, can be used to explore the interactions between emotional arousal, attitudes, and behavior, which drive complex consumer behavior and perceptions. The configuration of the current experiment enhances our understanding of how the retail environment can influence shopper cognitions and emotions in facilitating purchasing behavior. The current findings have broad implications for both retailers and manufacturers, leading to compelling questions to consider for future experimental studies.

Influencing emotion at retail has the potential for achieving a number of desired effects, including greater store satisfaction and lower price sensitivity. These results suggest that marketers should think creatively beyond conventional P-O-P communications, merchandising and promotions to experiment with contextual sensory stimuli and positive experiential associations. The more retailers can engage consumers at the point of purchase with positive associations and sensory experiences, the greater their chances of improving the customer experience and driving purchases.

Elissa Moses, CEO, Ipsos Neuro and Behavioral Science

Center is a pioneer in applied neuroscience. At Ipsos, she has

expanded the portfolio of nonconsious measurement to include

EEG, biometrics, facial coding, eye tracking, implicit reaction

time testing and voice analytics to be accessible throughout

the world. Prior she was Chief Analytics Officer at EmSense,

Managing Partner at Grey Advertising, Founder and

Managing Director of the Brainwaves Group and SVP,

Head of Global Consumer Intelligence and Strategy at

Philips. She is a frequently published thought leader, author

of the $100 Billion Allowance: Accessing the Global Teen

Market and a speaker throughout the globe. She can be

reached at [email protected].

Dr. Laura E. Beavin is a research consultant in the space

of consumer and behavioral neuroscience and an adjunct

professor of psychology. Dr. Beavin has served as Manager

of R&D for the Ipsos Neuro and Behavioral Science Center

and as the Senior Research Manager for Coherency. She can

be reached at [email protected].

Dr. Lisa Zaval, is a behavioral scientist with broad

expertise in decision science, social psychology and

behavioral economics, and serves as Director of Scientific

Research at the Ipsos Neuro and Behavioral Science Center.

She can be reached at [email protected].

Kirk Hendrickson, CEO, Eye Faster, a leading provider

of shopper research using eye tracking, developed his

expertise in eye tracking and shopper research while leading

worldwide field operations for EmSense Corporation and

product management for MarketTools, Inc. Kirk holds a

patent for conducting surveys on mobile phones and was

twice a finalist for the EXPLOR Awards. He can be

reached at [email protected].

Acknowledgments

This research was conducted by Ipsos with support from Eye Faster for Eye-tracking and Beyond Verbal for Voice Analytics. It was also made possible by Schnucks Market in St. Louis in providing their large grocery as an in-store field site. We also want to thank the additional project team members from the Ipsos Neuro and Behavioral Science Center who helped make this study possible Kelley Hargus, Dr. Patrick B. Williams, Jessica Reiter, and Marc Korczykowski and from Ipsos Marketing, Mark Berry; from Eye Faster: Scott McEachen, Jordan Morgen-Barnes and Mitch Cartwright; and from Beyond Verbal: Alon Goldstein, Bianca Meger, Dan Emodi and Zohar Ben-Har.



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Appendix A

Appendix AShopper Study - Intercept Screener

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Appendix AShopper Study - Intercept Screener

Appendix A



Appendix B

Appendix BShopper Study - Post-Shopping Survey

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Appendix BShopper Study - Post-Shopping Survey

Appendix B



Appendix B (Continued)Shopper Study - Post-Shopping Survey

Appendix B

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