Does Advertising Truly Represent the LGBTQ+ Community? An Analysis of Intersectionality and Consumer Responses to LGBTQ+ Advertising
Dublin Core
Title
Does Advertising Truly Represent the LGBTQ+ Community? An Analysis of Intersectionality and Consumer Responses to LGBTQ+ Advertising
Creator
Layton Edgington
Date
September 2021
Description
Depictions of sexual and gender minorities in advertising are becoming increasingly common and diverse. Yet, numerous intersections within these portrayals are still invisible. Previous research has found mixed results regarding consumer responses to LGBTQ+ identities in advertising. The current study aimed to obtain a further understanding into how a diverse range of consumers respond to heteronormative versus LGBTQ+ imagery in ads. This was assessed using semi-structured interviews to examine sexual and gender minority consumer (n = 13) and non-LGBTQ+ consumer (n = 6) reactions to three distinct IKEA ads. In addition to this, LGBTQ+ character depictions in 286 worldwide mainstream ads from 2016-2020 were analysed for measures of intersectionality across the dimensions of race, age and specific LGBTQ+ membership, extending the previous findings of Nölke (2018). Results indicated that non-LGBTQ+ participants showed similar responses and subsequent brand evaluation regardless of ad theme. Sexual and gender minority participants were found to show preference towards the ad featuring LGBTQ+ identities, though were often found to be sceptical of such portrayals. Intersectionality analysis uncovered that 47 out of a possible 96 intersections were completely invisible from 2016-2020, although representation of minorities within the community has increased substantially since the original findings. Results demonstrate the importance of character depictions in advertising, highlighting why intersectionality of such portrayals needs to increase in the future. Findings further denote how and why different consumers react to specific ad imagery, making recommendations to marketers regarding their inclusion of LGBTQ+ identities in advertising.
Subject
LGBTQ+ advertising, prosocial advertising, intersectionality, consumer attitudes
Source
Participants
The sample consisted of 19 participants aged between 18-53 at their time of interview; Mage = 23.5 years, SDage = 7.6. Of this sample, 13 participants stated that they identified as LGBTQ+ (2 White lesbian females, 1 Mixed-Race lesbian female, 2 White gay males, 1 Asian gay male, 2 White bisexual females, 1 Black bisexual female, 1 Asian bisexual male, 1 White transgender female, 1 White transgender male and 1 White transgender non-binary individual). A further 6 participants stated that they did not identify as LGBTQ+ (3 White males and 3 White females). Participants were recruited in a purposive manner through social media sites such as Instagram and WhatsApp and comprised mainly of acquaintances of the researcher. A high proportion of LGBTQ+ participants were utilised in an effort to ensure intersectionality of responses, which has been shown to provide a strong methodological framework within which to investigate underrepresented groups (Rodriguez, 2018).
Design
The study consisted of two distinct elements; semi-structured interviews and a content analysis of existing global advertisements that feature LGBTQ+ characters from 2016-2020. Semi-structured interviews were the chosen method of qualitative data gathering, as the style allows for analysis according to the basis of grounded theory (Glaser & Strauss, 1967) and gives scope for probing questions to supplement the richness of answers given. The combination of quantitative (quantified content analysis) and qualitative research employed in the study through separate investigations was undertaken in attempt to provide a rigorous understanding of LGBTQ+ diversity in advertising and its effects upon observers.
Interviews
All participants individually took part in an in-depth semi-structured interview with the researcher over Microsoft Teams. Due to the inductive nature of the exploration, no independent and dependent variables were implemented. The research broadly assessed the following measures across populations in the sample: the importance of character depictions, prosociality views, representation significance, brand attitudes, and purchasing likelihood succeeding exposure to three IKEA advertisements. The same brand was used for all ads in order to eliminate brand biases. The order in which advertisements were shown to participants was random in an effort to counterbalance order effects. Each interview lasted for approximately 45 minutes.
Ad Intersectionality
This additional component of the study involved conducting a content analysis of all global advertisements that feature LGBTQ+ identities from 2016-2020. This design mirrored that initially used by Nölke (2018), continuing their longitudinal analysis of intersectionality in LGBTQ+ advertising depictions which scoped the years 2009-2015. Identical to the original study, the source for these ads was AdRespect (http://adrespect.org), a website which comprehensively includes any advertisement featuring LGBTQ+ inclusion from around the world. The independent variable was time, as adverts which aired within each individual year were grouped together. Dependent measures included counts of different intersectionality measures, an approach first used by Gopaldas & DeRoy (2015) in their intersectional analysis of Gentlemen’s Quarterly covers, and were further investigated by Nölke (2018). In the present study these measures consisted of age, race and specific LGBTQ+ membership.
Measures
Interviews
The semi-structured interview completed by each participant was devised entirely by the researcher and involved seven different sections which addressed questions surrounding the significance of character portrayals in advertising. The interview primarily consisted of open-ended questions, though some close-ended questions were also asked where definitive answers were required. Questions often had multiple sub-questions within them in order to probe more detailed responses from participants. In total the interview asked 31 unique questions, with nine of these questions repeated three times (in sections four, five and six).
The first section was an overview which told participants what the interview would entail whilst it also asked general ad watching questions to prime the interviewee for more detailed questions to follow. An example question from section one includes “would you say in general that you watch many ads?”.
Section two was focused on the participant’s views towards representation in advertising, particularly focusing on LGBTQ+ representation and its significance to them. Example questions include: “if you are to view an advertisement that openly features LGBTQ+ identities, how would it make you feel?” and “do the character depictions in adverts matter to you? What characteristic(s) are most significant to you? Why is this?”.
The third section addressed identity formation, asking interviewees questions about advertising from when they were growing up in an attempt to investigate the impact of negligible LGBTQ+ depictions in the past. It asked questions including: “Do you ever remember seeing LGBTQ+ identities in advertising when you were younger? How did this make you feel?”. In addition to this, it attempted to gain an understanding of how characters in advertising impact the formation of identity from a retrospective viewpoint.
The subsequent three sections all asked the same set of questions to participants after showing them three different IKEA adverts in a random order (https://bit.ly/2VkBCQs), (https://bit.ly/3yHXouV) and (https://bit.ly/2WVyElD). All ads were published to mainstream audiences on television by IKEA within the past two years and were matched closely in terms of length. The first ad (Ads of Brands, 2020) titled ‘next generation’ featured only heteronormative White characters, within a nuclear family unit. It was selected as it acted as a non-representative example which showcased very little intersectionality and no LGBTQ+ identities. The second ad ‘change a bit for good’ (IKEA UK, 2021) displayed identity neutral robots who attempt to tackle climate change. This ad acted as a control for participants, as it still addresses a prosocial topic whilst portraying no identifying elements of its characters. The final ad ‘be someone’s home’ (IKEA USA, 2020) showed a wide variety of diversity across intersections within the LGBTQ+ community, which functioned as an inclusive example to interviewees.
Questions asked after exposure to each ad included items assessing the participant’s attitude towards the brand, their subsequent purchasing intentions and the believed importance of the identities portrayed. Example items include: “after watching this ad, would you feel more or less inclined to spend money with IKEA? Why is this?” and “do you believe the identities shown in the ad are important to others? Why do you think this?”.
The last component of the interview asked participants about their general spending behaviour, brand evaluation and concluding questions about how LGBTQ+ visibility in advertising makes them feel. Sample items include: “would seeing an ad that positively depicts someone similar to you make you value the brand more? How come? Would this also make you more likely to buy?” and “is there anything that you would like to change in modern advertising? Less of something? More of something? Why?”.
Ad Intersectionality
Coding Scheme. The present study followed the coding scheme of Nölke (2018), but chose to exclude class as a coding dimension, due to an absence of representation in this area. The coding dimensions analysed within the study were LGBTQ+ membership, age and race. Each portrayal was coded across all three dimensions.
LGBTQ+ Membership. Items within this dimension were coded accordingly: ‘lesbian female’, ‘gay male’, ‘bisexual’, ‘trans-female’ (MtF) which included drag queens, ‘trans-male’ (FtM) and ‘gender neutral/non-binary’. Nölke (2018) did not code gender neutral or non-binary identities due to the absence of such portrayals. The current study implemented this additional measure as it saw the need to recognise the additional membership which is becoming increasingly prevalent in modern depictions. Transgender depictions were either explicitly labelled as such within the ad, overtly presented (for example, in terms of top-surgery scarring) or for celebrity depictions, publicly accessible data on their identity was used. Gender neutral/non-binary coded characters were either stated as such within the ad, their gender was indiscernible, or in celebrity cases, publicly available information on their identity was again utilised.
Age. Based upon Gopaldas & DeRoy’s (2015) scheme, age was determined by estimations to the nearest multiple of five based upon observation. The following codes were used: “teen” (aged 13+), “young adult” (20+), “middle-aged” (35+) and “mature” (50+).
Race. The race of characters was coded according to visual appearance, language and ad text. Codes included “White”, “Black”, “Asian” and “Latinx”. It is important to note that these terms differ from those used by Nölke (2018), in accordance to APA’s guidance on inclusive language regarding racial and ethnic identity (American Psychological Association, 2019).
Procedure
Ethical approval for this study was acquired through the project supervisor and ethics partner at Lancaster University, as the proposed research was deemed low risk.
Interviews
Participants were each given an electronic information sheet, consent form and short demographic questionnaire which included LGBTQ+ membership status questions to complete through Qualtrics (https://www.qualtrics.com). To ensure participants were comfortable, all questions in this form were optional to answer. After consent was obtained, participants were contacted to arrange a suitable interview date and time, which was conducted via Microsoft Teams. During each interview, the researcher asked questions according to the interview schedule in a semi-structured manner. These interviews were recorded and transcribed for analysis. Throughout the interviews, participants were reminded that they did not need to answer any questions that they did not want to and that they were free to leave at any point should they wish. Any identifying data was removed during transcription to maintain participant confidentiality. After interviews had finished, all participants were sent a debriefing form via email.
Ad Intersectionality
Ad Selection. Ads published between 2016-2020 on AdRespect were selected according to the same principles utilised by Nölke (2018). To begin, the 531 ads submitted to AdRespect during the years 2016-2020 were evaluated. AdRespect states the audience in which each ad was published to and those that were exclusively published to LGBTQ+ audiences were excluded from analysis. Additionally rejected from analysis were ads where the character’s LGBTQ+ status was not evident, ads that showed no explicit depiction of people and ads for non-profit organisations. This exclusion criteria left 284 ads. As AdRespect is a crowdsourced platform, a further search for ads that met the inclusion criteria was conducted across the internet in case any were left out by the online database. This search found a further two ads, producing a total of 286 ads within the final dataset. These ads were then coded according to the dimensions of age, race and LGBTQ+ membership. Ads were coded for every LGBTQ+ portrayal shown, thus often multiple characters were displayed within each ad and were analysed per individual depiction.
Analysis
Qualitative Analysis of Interviews
After transcription, all interviews were analysed through inductive thematic analysis due to the exploratory nature of the research (Braun & Clarke, 2006). This process adhered to their six phases of analysis: familiarization of the data, initial code generation, theme search, theme review, defining and naming themes and report production, which allowed the researcher to identify the themes that underpin consumer responses and attitudes towards LGBTQ+ portrayals. This analysis was conducted through NVivo 12 qualitative data analysis software.
Quantitative Analysis of ad Intersectionality
Quantitative analyses of the dataset were conducted through collation of codes ascribed to portrayals across time. The depictions were summarised across intersectional and unidimensional measures according to which year they belonged to. This was analysed as a singular project as well as comparatively against the original findings from Nölke (2018), which allowed to researcher to demonstrate how portrayals of the LGBTQ+ community in advertising have transformed from 2009-2020. In addition to the researcher, a secondary coder was randomly assigned 25 ads from the dataset in order to test inter-rater reliability, which stood at 100% across all coding dimensions.
The sample consisted of 19 participants aged between 18-53 at their time of interview; Mage = 23.5 years, SDage = 7.6. Of this sample, 13 participants stated that they identified as LGBTQ+ (2 White lesbian females, 1 Mixed-Race lesbian female, 2 White gay males, 1 Asian gay male, 2 White bisexual females, 1 Black bisexual female, 1 Asian bisexual male, 1 White transgender female, 1 White transgender male and 1 White transgender non-binary individual). A further 6 participants stated that they did not identify as LGBTQ+ (3 White males and 3 White females). Participants were recruited in a purposive manner through social media sites such as Instagram and WhatsApp and comprised mainly of acquaintances of the researcher. A high proportion of LGBTQ+ participants were utilised in an effort to ensure intersectionality of responses, which has been shown to provide a strong methodological framework within which to investigate underrepresented groups (Rodriguez, 2018).
Design
The study consisted of two distinct elements; semi-structured interviews and a content analysis of existing global advertisements that feature LGBTQ+ characters from 2016-2020. Semi-structured interviews were the chosen method of qualitative data gathering, as the style allows for analysis according to the basis of grounded theory (Glaser & Strauss, 1967) and gives scope for probing questions to supplement the richness of answers given. The combination of quantitative (quantified content analysis) and qualitative research employed in the study through separate investigations was undertaken in attempt to provide a rigorous understanding of LGBTQ+ diversity in advertising and its effects upon observers.
Interviews
All participants individually took part in an in-depth semi-structured interview with the researcher over Microsoft Teams. Due to the inductive nature of the exploration, no independent and dependent variables were implemented. The research broadly assessed the following measures across populations in the sample: the importance of character depictions, prosociality views, representation significance, brand attitudes, and purchasing likelihood succeeding exposure to three IKEA advertisements. The same brand was used for all ads in order to eliminate brand biases. The order in which advertisements were shown to participants was random in an effort to counterbalance order effects. Each interview lasted for approximately 45 minutes.
Ad Intersectionality
This additional component of the study involved conducting a content analysis of all global advertisements that feature LGBTQ+ identities from 2016-2020. This design mirrored that initially used by Nölke (2018), continuing their longitudinal analysis of intersectionality in LGBTQ+ advertising depictions which scoped the years 2009-2015. Identical to the original study, the source for these ads was AdRespect (http://adrespect.org), a website which comprehensively includes any advertisement featuring LGBTQ+ inclusion from around the world. The independent variable was time, as adverts which aired within each individual year were grouped together. Dependent measures included counts of different intersectionality measures, an approach first used by Gopaldas & DeRoy (2015) in their intersectional analysis of Gentlemen’s Quarterly covers, and were further investigated by Nölke (2018). In the present study these measures consisted of age, race and specific LGBTQ+ membership.
Measures
Interviews
The semi-structured interview completed by each participant was devised entirely by the researcher and involved seven different sections which addressed questions surrounding the significance of character portrayals in advertising. The interview primarily consisted of open-ended questions, though some close-ended questions were also asked where definitive answers were required. Questions often had multiple sub-questions within them in order to probe more detailed responses from participants. In total the interview asked 31 unique questions, with nine of these questions repeated three times (in sections four, five and six).
The first section was an overview which told participants what the interview would entail whilst it also asked general ad watching questions to prime the interviewee for more detailed questions to follow. An example question from section one includes “would you say in general that you watch many ads?”.
Section two was focused on the participant’s views towards representation in advertising, particularly focusing on LGBTQ+ representation and its significance to them. Example questions include: “if you are to view an advertisement that openly features LGBTQ+ identities, how would it make you feel?” and “do the character depictions in adverts matter to you? What characteristic(s) are most significant to you? Why is this?”.
The third section addressed identity formation, asking interviewees questions about advertising from when they were growing up in an attempt to investigate the impact of negligible LGBTQ+ depictions in the past. It asked questions including: “Do you ever remember seeing LGBTQ+ identities in advertising when you were younger? How did this make you feel?”. In addition to this, it attempted to gain an understanding of how characters in advertising impact the formation of identity from a retrospective viewpoint.
The subsequent three sections all asked the same set of questions to participants after showing them three different IKEA adverts in a random order (https://bit.ly/2VkBCQs), (https://bit.ly/3yHXouV) and (https://bit.ly/2WVyElD). All ads were published to mainstream audiences on television by IKEA within the past two years and were matched closely in terms of length. The first ad (Ads of Brands, 2020) titled ‘next generation’ featured only heteronormative White characters, within a nuclear family unit. It was selected as it acted as a non-representative example which showcased very little intersectionality and no LGBTQ+ identities. The second ad ‘change a bit for good’ (IKEA UK, 2021) displayed identity neutral robots who attempt to tackle climate change. This ad acted as a control for participants, as it still addresses a prosocial topic whilst portraying no identifying elements of its characters. The final ad ‘be someone’s home’ (IKEA USA, 2020) showed a wide variety of diversity across intersections within the LGBTQ+ community, which functioned as an inclusive example to interviewees.
Questions asked after exposure to each ad included items assessing the participant’s attitude towards the brand, their subsequent purchasing intentions and the believed importance of the identities portrayed. Example items include: “after watching this ad, would you feel more or less inclined to spend money with IKEA? Why is this?” and “do you believe the identities shown in the ad are important to others? Why do you think this?”.
The last component of the interview asked participants about their general spending behaviour, brand evaluation and concluding questions about how LGBTQ+ visibility in advertising makes them feel. Sample items include: “would seeing an ad that positively depicts someone similar to you make you value the brand more? How come? Would this also make you more likely to buy?” and “is there anything that you would like to change in modern advertising? Less of something? More of something? Why?”.
Ad Intersectionality
Coding Scheme. The present study followed the coding scheme of Nölke (2018), but chose to exclude class as a coding dimension, due to an absence of representation in this area. The coding dimensions analysed within the study were LGBTQ+ membership, age and race. Each portrayal was coded across all three dimensions.
LGBTQ+ Membership. Items within this dimension were coded accordingly: ‘lesbian female’, ‘gay male’, ‘bisexual’, ‘trans-female’ (MtF) which included drag queens, ‘trans-male’ (FtM) and ‘gender neutral/non-binary’. Nölke (2018) did not code gender neutral or non-binary identities due to the absence of such portrayals. The current study implemented this additional measure as it saw the need to recognise the additional membership which is becoming increasingly prevalent in modern depictions. Transgender depictions were either explicitly labelled as such within the ad, overtly presented (for example, in terms of top-surgery scarring) or for celebrity depictions, publicly accessible data on their identity was used. Gender neutral/non-binary coded characters were either stated as such within the ad, their gender was indiscernible, or in celebrity cases, publicly available information on their identity was again utilised.
Age. Based upon Gopaldas & DeRoy’s (2015) scheme, age was determined by estimations to the nearest multiple of five based upon observation. The following codes were used: “teen” (aged 13+), “young adult” (20+), “middle-aged” (35+) and “mature” (50+).
Race. The race of characters was coded according to visual appearance, language and ad text. Codes included “White”, “Black”, “Asian” and “Latinx”. It is important to note that these terms differ from those used by Nölke (2018), in accordance to APA’s guidance on inclusive language regarding racial and ethnic identity (American Psychological Association, 2019).
Procedure
Ethical approval for this study was acquired through the project supervisor and ethics partner at Lancaster University, as the proposed research was deemed low risk.
Interviews
Participants were each given an electronic information sheet, consent form and short demographic questionnaire which included LGBTQ+ membership status questions to complete through Qualtrics (https://www.qualtrics.com). To ensure participants were comfortable, all questions in this form were optional to answer. After consent was obtained, participants were contacted to arrange a suitable interview date and time, which was conducted via Microsoft Teams. During each interview, the researcher asked questions according to the interview schedule in a semi-structured manner. These interviews were recorded and transcribed for analysis. Throughout the interviews, participants were reminded that they did not need to answer any questions that they did not want to and that they were free to leave at any point should they wish. Any identifying data was removed during transcription to maintain participant confidentiality. After interviews had finished, all participants were sent a debriefing form via email.
Ad Intersectionality
Ad Selection. Ads published between 2016-2020 on AdRespect were selected according to the same principles utilised by Nölke (2018). To begin, the 531 ads submitted to AdRespect during the years 2016-2020 were evaluated. AdRespect states the audience in which each ad was published to and those that were exclusively published to LGBTQ+ audiences were excluded from analysis. Additionally rejected from analysis were ads where the character’s LGBTQ+ status was not evident, ads that showed no explicit depiction of people and ads for non-profit organisations. This exclusion criteria left 284 ads. As AdRespect is a crowdsourced platform, a further search for ads that met the inclusion criteria was conducted across the internet in case any were left out by the online database. This search found a further two ads, producing a total of 286 ads within the final dataset. These ads were then coded according to the dimensions of age, race and LGBTQ+ membership. Ads were coded for every LGBTQ+ portrayal shown, thus often multiple characters were displayed within each ad and were analysed per individual depiction.
Analysis
Qualitative Analysis of Interviews
After transcription, all interviews were analysed through inductive thematic analysis due to the exploratory nature of the research (Braun & Clarke, 2006). This process adhered to their six phases of analysis: familiarization of the data, initial code generation, theme search, theme review, defining and naming themes and report production, which allowed the researcher to identify the themes that underpin consumer responses and attitudes towards LGBTQ+ portrayals. This analysis was conducted through NVivo 12 qualitative data analysis software.
Quantitative Analysis of ad Intersectionality
Quantitative analyses of the dataset were conducted through collation of codes ascribed to portrayals across time. The depictions were summarised across intersectional and unidimensional measures according to which year they belonged to. This was analysed as a singular project as well as comparatively against the original findings from Nölke (2018), which allowed to researcher to demonstrate how portrayals of the LGBTQ+ community in advertising have transformed from 2009-2020. In addition to the researcher, a secondary coder was randomly assigned 25 ads from the dataset in order to test inter-rater reliability, which stood at 100% across all coding dimensions.
Publisher
Lancaster University
Format
Data/Excel.csv
Text/Nvivo
Text/Nvivo
Identifier
Edgington2021
Contributor
Laura Meek
Rights
Open (Unless stated otherwise)
Relation
None (Unless stated otherwise)
Language
English
Type
Data
Coverage
LA1 4YF
LUSTRE
Supervisor
Leslie Hallam
Project Level
MSc
Topic
Social, Marketing
Sample Size
The sample consisted of 19 participants aged; Mage = 23.5 years, SDage = 7.6. Of this sample, 13 participants stated that they identified as LGBTQ+ (2 White lesbian females, 1 Mixed-Race lesbian female, 2 White gay males, 1 Asian gay male, 2 White bisexual females, 1 Black bisexual female, 1 Asian bisexual male, 1 White transgender female, 1 White transgender male and 1 White transgender non-binary individual). A further 6 participants stated that they did not identify as LGBTQ+ (3 White males and 3 White females).
Statistical Analysis Type
Qualitative
ANOVA
ANOVA
Files
Collection
Citation
Layton Edgington, “Does Advertising Truly Represent the LGBTQ+ Community? An Analysis of Intersectionality and Consumer Responses to LGBTQ+ Advertising ,” LUSTRE, accessed April 28, 2024, https://www.johnntowse.com/LUSTRE/items/show/131.