The beauty industry has transformed in recent years driven by consumer demands for products that align with their cultural values and personal beliefs. While the top cosmetic brands continue to be L’Oreal and Estee Lauder, they are being challenged by younger, edgier brands like Selena Gomez’s Rare Beauty, Rihanna’s Fenty and e.l.f. Cosmetics. Consumer opinion, however, is not homogeneous. There are significant differences in preferences based on ethnicity, age, income and gender. ThinkNow uncovered some of those differences in our recent Inclusive Beauty Report based on a nationally representative online survey of 2,800 respondents.

Download the full results of the survey here.

The Rise of Conscious Consumerism

The era of conscious consumerism has brought about a major shift in the beauty industry. Increasingly, consumers seek products that align with their values, whether minimizing harm to animals, supporting sustainable practices, or promoting inclusivity. This has led to a growing demand for cosmetics and beauty products that are cruelty-free, meaning they are not tested on animals and that are considered inclusive.

Interestingly, while nearly half of cosmetic consumers want cruelty-free brands, 88% of them are still not cruelty-free. However, the fastest growing brands like e.l.f. and Rare Beauty are both cruelty-free and vegan. Legacy companies that want to compete in today’s market are being pushed to adopt these practices in their formulations and testing processes.

Cultural Insights and Multicultural Consumer Preferences

While the market as-a-whole is trending towards conscious consumerism, there are significant multicultural differences. For example, the demand for all-vegan cosmetics appears to be driven by non-Hispanic White consumers.

Additionally, since non-Hispanic Whites are, on average, ten years older than multicultural Americans, 42% of them choose brands based on how they address age-related needs vs. 30% of Hispanics who value age-related needs. Asians value products that offer solutions for different skin tones (37%) vs products that are endorsed by celebrities (15%) while Black and non-Hispanic White consumers are more likely to value brands that have a variety of price points. Understanding and addressing these specific preferences, as supported by cultural consumer insights, is crucial for building a loyal customer base.

Age and Income Drive Preferences

One might assume that younger consumers would be most interested in conscious consumerism. Gen Z however, is much less likely to seek out vegan cosmetic brands (19%) than Millennials (33%) or Gen X (31%). Gen X is more likely to seek out organic/natural ingredients (41%) than the 36% average for other age groups.

Income, however, is one of the factors that most affect cosmetic product preferences. For example, those earning more than $80K a year are significantly more likely to choose brands that are cruelty-free (53%) and vegan (42%) than those earning less than $40K annually (39%) and 21%), respectively. This insight-driven approach doesn't just enhance product offerings; it also builds trust and loyalty among diverse consumer groups.

The Impact of Inclusive Beauty

The beauty industry's shift towards cruelty-free, vegan, and inclusive beauty products aligns with trends observed in multicultural consumer insights. Younger generations are the most statistically diverse in history and wield the power to affect change. They are communicating their expectations to brands or starting their own and challenging heteronormative stereotypes of “beauty.” Companies willing to adapt to these culture shifts will stay relevant as consumer tastes change and contribute to a more compassionate and diverse world.

Los paneles de investigación en línea en América Latina a menudo subrepresentan a los grupos de bajos ingresos, a pesar de constituir una proporción más grande de la población. Por otro lado, las personas con ingresos más altos a menudo están sobrerrepresentadas en comparación con aquellas de ingresos más bajos. Esta discrepancia puede plantear problemas potenciales, pero los investigadores de mercado pueden mitigar estos riesgos considerando cuidadosamente la composición de sus paneles y tomando medidas para garantizar que obtienen datos precisos y fiables.

Factores que afectan la Representación Socioeconómica

Muchas variables influyen en las disparidades en los paneles de investigación en línea. Principal entre ellas, en América Latina, está el hecho de que las personas de contextos socioeconómicos más bajos podrían no participar tan activamente en encuestas de investigación de mercado por varias razones:

• Acceso limitado a Internet: Las encuestas en línea son un método común para la recopilación de datos en la investigación de mercado, pero las personas de contextos socioeconómicos más bajos podrían tener acceso limitado o nulo a Internet en sus hogares. Esto dificulta su participación en las encuestas en línea.
• Altos costos de Internet: Los servicios de Internet no siempre son asequibles y a menudo se adquieren en paquetes individuales a través de empresas de telecomunicaciones, con datos limitados. El acceso compartido a Internet en el hogar es una rareza, lo que dificulta que todos los miembros de la familia tengan acceso.
• Limitaciones de tiempo: Las personas con recursos limitados a menudo tienen jornadas laborales largas y múltiples responsabilidades, lo que deja poco tiempo libre. Participar en encuestas podría no ser una prioridad cuando están ocupados con el trabajo y el cuidado de la familia.
• Falta de incentivos: Algunas encuestas ofrecen incentivos económicos o regalos como recompensa por la participación. Las personas de fondos socioeconómicos más bajos podrían percibir estos incentivos como insuficientes para justificar el tiempo y el esfuerzo económico requerido.
• Falta de confianza: Algunas personas pueden desconfiar de las encuestas y ser escépticas sobre proporcionar información personal o financiera en línea. Esta desconfianza podría ser más pronunciada en aquellos menos familiarizados con la tecnología y el entorno en línea.
• Falta de identificación: Las preguntas de la encuesta podrían estar formuladas de manera que no se relacionen con las experiencias y preocupaciones de aquellos de fondos socioeconómicos más bajos. En consecuencia, podrían no sentirse representados y no tener interés en participar.
• Barreras culturales y lingüísticas: Las encuestas podrían diseñarse en un idioma inaccesible para todos, y las diferencias culturales pueden influir en la interpretación de las preguntas.

Mejorando la Representación en los Paneles de Investigación en Línea

Para fomentar la participación de personas con antecedentes socioeconómicos más bajos en las encuestas de investigación de mercado, es esencial considerar y abordar las posibles barreras que enfrentan. Esto se puede lograr ofreciendo incentivos relevantes, empleando métodos diversos de recopilación de datos y diseñando encuestas inclusivas y culturalmente sensibles. Tomar estas medidas mejorará con el tiempo la representación socioeconómica en los paneles de investigación en línea de América Latina.

Para obtener más información sobre cómo motivar a los panelistas y adaptar el lenguaje de los cuestionarios, consulta el blog de ThinkNow.

Online research panels in Latin America often underrepresent lower socioeconomic groups, despite being a larger proportion of the population. Individuals with higher incomes, on the other hand, are often overrepresented compared to those with lower incomes. This mismatch can lead to potential challenges, but market researchers can mitigate these risks by carefully considering the composition of their panels and taking steps to ensure that they are getting accurate and reliable data.

Factors Impairing Socioeconomic Representation

Many variables factor into disparities in online research panels. Chief among them in Latin America is the fact that individuals from lower socioeconomic backgrounds might not engage as actively in market research surveys for several reasons:

• Limited Internet Access: Online surveys are a common method for data collection in market research, but people from lower socioeconomic backgrounds might have limited or no internet access at home. This hinders their participation in online surveys.
• High Internet Costs: Internet services are not always affordable and are often bought as individual packages through telecom companies, with limited data. Shared household internet is a rarity, making it challenging for all family members to have access.
• Time Constraints: Individuals with limited resources often juggle long work hours and multiple responsibilities, leaving little free time. Participating in surveys might not be a priority when they are busy with work and family care.
• Lack of Incentives: Some surveys offer economic incentives or gifts as rewards for participation. Individuals from lower socioeconomic backgrounds might perceive these incentives as insufficient to justify the required time and economic effort.
• Lack of Trust: Certain individuals may distrust surveys and be skeptical about providing personal or financial information online. This distrust might be more pronounced in those less familiar with technology and the online environment.
• Lack of Identification: Survey questions might be phrased in a manner unrelated to the experiences and concerns of those from lower socioeconomic backgrounds. Consequently, they might not feel represented so they have no interest in participating.
• Cultural and Linguistic Barriers: Surveys might be designed in a language inaccessible to all, and cultural differences can influence question interpretation.

Improving Representation in Online Research Panels

To encourage participation from people with lower socioeconomic backgrounds in market research surveys, it is essential to consider and address the potential barriers they face. This can be achieved by offering relevant incentives, employing diverse data collection methods, and designing inclusive and culturally sensitive surveys. Taking these measures will, over time, improve socioeconomic representation in Latin American online research panels.

For more insights on motivating panelists and adapting questionnaire language, check out the ThinkNow blog.

Today’s discerning consumers crave personalized marketing experiences in which they feel seen and heard. The paradigm has shifted, and brands looking to stay ahead of the curve are working to foster genuine connections with consumers by committing to inclusivity in products and services and participating in meaningful community engagement. This is particularly important for hard-to-reach demographics, like multicultural consumers, who have endured generations of misrepresentation and underrepresentation in advertising.

While traditional advertising revolves around reaching the masses, often at the expense of the consumer experience, network marketing, on the other hand, leverages person-to-person interactions by independent sales teams to directly engage communities. Popular beauty brands like Avon, Mary Kay and Beautycounter have harnessed the power of this model, often referred to as multi-level marketing, to build global billion-dollar enterprises.

Yet, disparities between corporations and communities persist. There lies a need for adaptive strategies that bridge these gaps, ultimately culminating in enriched consumer experiences.

In this episode of The New Mainstream podcast, Dr. Raymona H. Lawrence, founder of Dr. Raymona H. Lawrence Coaching, LLC, explores the intersection between brands, communities and marketing strategies.

The American ethos of “individualism,” which prioritizes self-reliance, independence and frugality, has tremendously impacted general market advertising strategies. Marketing to Hispanic consumers, however, requires a different approach. The Hispanic ethos embodies collectivism, emphasizing the belief and practice of interdependence and interconnectedness among individuals. Twenty-eight percent of Hispanics live in multigenerational homes where bilingual-bicultural family members typically serve as digital sherpas for Spanish-dominant loved ones who need assistance with online purchasing decisions and online/offline searches.

Interestingly, when Hispanics search online, they prefer to search in English, particularly among the highly acculturated. Marketers may misinterpret this to mean that English-dominate or English-proficient Hispanics are receptive to general market ads when they are not. While advertisers may be reaching Hispanics with these ads, they are not truly connecting with them if they are not brand loyal. And how can they be brand loyal if they do not see themselves reflected in the campaigns? At that point, it becomes a transaction driven by price or availability, not a genuine connection with the brand.

To effectively engage with the bilingual-bicultural Hispanic market, brands must embrace and understand the importance of community, family, and shared experiences. Rather than solely focusing on individual benefits, marketers should emphasize these cultural values in their marketing campaigns. Highlighting how a product or service contributes to the collective well-being and fosters connections can resonate more deeply with Hispanic consumers.

In this episode of The New Mainstream Podcast, Maria (Lopez) Twena, Chief Marketing Officer at Adsmovil and children’s book author of the MariVi the Master Navigator series, discusses the importance of cultural values like collectivism to marketing to bilingual-bicultural Hispanics.

For more Hispanic Consumer insights, get the free report, “The Hispanic Market is not a Monolith but it is Collective,” presented by Publicis Media, Adsmovil and ThinkNow. Download it here.

Meet Our Guest:

Maria (Lopez) Twena, Chief Marketing Officer, Adsmovil

Maria (Lopez) Twena serves as Chief Marketing Officer of Adsmovil, a leading minority-owned and certified mobile advertising and digital media pioneer.

An award-winning marketer with extensive expertise in technology, digital media, and branding, Twena has over thirty years of marketing acumen. Prior to joining Adsmovil, she served as CMO of Entravision Communications and as CMO of Pulpo Media.

Widely recognized for her expertise in branding, positioning, and multicultural consumer segments, Twena’s accolades include receiving the ADCOLOR Award (2009) for her groundbreaking achievement in identifying, segmenting, and targeting bilingual/bicultural Hispanics while at MRM (McCann Worldgroup). There, she founded a discipline that developed Best Practices for advertising to the Hispanic bilingual/bicultural cohort.

She has served as a Board Member of the Association of Hispanic Advertising Agencies and as a faculty member of the Association of National Advertisers (ANA). She is also a ThinkNow Advisory Board Member. Twena is a graduate of Loyola University of the South (B.A. Psychology) and the University of New Orleans (M.A. Mass Communications, with a specialty in Film and Television).

She has also authored a children’s book and TV series: MariVi, the Master Navigator Series, which follows its heroine, MariVi, a bilingual/bicultural character, and her family, the Abascals, as they adapt to life in the U.S. The first of the MariVi television series premiered on Nuestra.TV in April 2023.

En la investigación en línea, la calidad de la muestra es crucial para obtener datos fiables y representativos. Por ello, ThinkNow ha implementado rigurosas medidas de seguridad y un protocolo de gestión de muestras fraudulentas para garantizar la integridad de los datos. En esta guía, exploraremos las medidas de seguridad que empleamos en nuestro panel y cómo abordamos los problemas de calidad en las terminaciones.

Medidas de seguridad para evitar muestras fraudulentas

La integridad de los datos sigue siendo una preocupación constante en el sector de la recolección online. Sin embargo, se pueden tomar algunas medidas para mitigar eficazmente el riesgo de muestras fraudulentas, entre ellas:

• Fingerprinting: Empleamos tecnología de huella digital para identificar si los nuevos registros proceden de dispositivos distintos. Esta medida nos ayuda a salvaguardar eficazmente contra la creación de múltiples cuentas fraudulentas desde el mismo dispositivo.
• Validación telefónica: Validamos aleatoriamente los números de teléfono facilitados por los panelistas durante el proceso de registro. Esto nos permite verificar la autenticidad de los números y evitar registros fraudulentos.
• Verificación del correo electrónico: Para confirmar la autenticidad de las direcciones de correo electrónico facilitadas durante el registro, enviamos un mensaje de verificación a los panelistas. Esta medida nos ayuda a validar la autenticidad de las direcciones de correo electrónico y evita registros generados por bots u otros medios fraudulentos.
• Geolocalización: El uso de la geolocalización de las direcciones IP de los nuevos registros nos permite determinar la ubicación aproximada desde la que se realiza el registro, lo que nos ayuda a detectar posibles registros fraudulentos o geográficamente incoherentes.

Identificación y manejo de panelistas fraudulentos

Además de las medidas de seguridad antes mencionadas, hemos implementado un protocolo para identificar y tratar a los panelistas fraudulentos de nuestra muestra, que incluye lo siguiente:

• Encuestas fantasmas: Los panelistas que intentan modificar los enlaces de seguimiento o realizan actividades fraudulentas son rápidamente identificados y eliminados. Al encriptar la información de los panelistas y la encuesta en curso evitamos la manipulación de los datos y garantizamos la integridad del estado final de los panelistas.
• Múltiples cuentas desde la misma IP: Supervisamos de cerca los registros y generamos informes exhaustivos para identificar a los panelistas que comparten o han compartido la misma dirección IP. Esta medida proactiva nos permite detectar y abordar con prontitud posibles actividades fraudulentas vinculadas a múltiples cuentas originadas desde una misma IP.

Protocolo para problemas de calidad

Si se entregan muestras que presentan problemas de calidad en determinadas encuestas completadas, seguimos un estricto protocolo de conciliación en colaboración con el cliente para resolver el problema. Los pasos que se dan incluyen:

• Identificación de panelistas con bajo rendimiento: Identificamos a los panelistas que presentan un rendimiento deficiente en términos de calidad, como respuestas incoherentes o no válidas. Una vez identificados, se toman las medidas adecuadas para resolver la situación.
• Eliminación de incentivos asociados a respuestas problemáticas: Si una encuesta presenta problemas de rendimiento, retiramos el incentivo concedido al panelista. Con esta medida mantenemos la calidad y fiabilidad de nuestra muestra.
• Comunicación e información: Enviamos un correo electrónico a los panelistas afectados, informándoles de su encuesta y les proporcionamos comentarios constructivos. Esto fomenta un alto nivel de entre los panelistas y promueve la mejora continua y la participación activa en futuras encuestas.

Conclusión

ThinkNow se enorgullece de su compromiso para garantizar la calidad de las muestras que proporciona a sus clientes. Hemos implementado sólidas medidas de seguridad como la toma de huellas digitales, la validación telefónica, la verificación del correo electrónico y geolocalización que infunden confianza en la autenticidad e integridad de nuestros datos. En el raro caso de que se produzca un problema de calidad, nuestro protocolo nos permite abordar los retos con rapidez y eficacia, salvaguardando la calidad de nuestra muestra. Nos comprometemos a proporcionar resultados fiables y representativos a nuestros clientes y seguimos invirtiendo en las herramientas que nos permiten hacerlo.

In online research, sample quality is crucial for obtaining reliable and representative data. So ThinkNow has implemented rigorous security measures and a protocol for handling fraudulent samples to ensure data integrity. In this guide, we will explore the security measures we employ in our panel and how we address quality issues in completions.

Security Measures to Prevent Fraudulent Samples

Data integrity continues to be an ongoing concern within the online sample industry. However, some measures can be taken to effectively mitigate the risk of fraudulent samples, including:

• Fingerprinting: We employ fingerprinting technology to identify whether new registrations originate from distinct devices. This measure helps us effectively safeguard against the creation of multiple fraudulent accounts originating from the same device.
• Phone Validation: We randomly validate the phone numbers provided by panelists during the registration process. This enables us to verify the authenticity of the numbers and prevent fraudulent registrations.
• Email Verification: To confirm the authenticity of the email addresses provided during registration, we send a verification message to panelists. This measure helps us validate the genuineness of the email addresses and prevents registrations generated by bots or other fraudulent means.
• Geolocation: Using the geolocation of the IP addresses of new registrations enables us to determine the approximate location from which the registration is being made, helping us detect possible fraudulent or geographically inconsistent registrations.

Identifying and Handling Fraudulent Panelists

In addition to the aforementioned security measures, we have implemented a protocol for identifying and addressing fraudulent panelists in our sample, including the following:

• Ghost Completes: Panelists who attempt to modify tracking links or engage in fraudulent activities are quickly identified and removed. By encrypting panelist information and the ongoing survey, we prevent data manipulation and ensure the integrity of the panelists’ final status.
• Multiple Accounts from the Same IP: We closely monitor registrations and generate comprehensive reports to identify panelists who share or have shared the same IP address. This proactive measure enables us to promptly detect and address potentially fraudulent activities linked to multiple accounts originating from a single IP.

Protocol for Quality Issues

If samples exhibiting quality issues within certain completed surveys are delivered, we adhere to a strict reconciliation protocol in collaboration with the client to resolve the issue. Steps taken include:

• Identification of panelists with poor performance: We identify panelists exhibiting poor performance in terms of quality, such as providing inconsistent or invalid responses. Once identified, the appropriate actions are taken to address the situation.
• Removal of incentives associated with problematic completions: If a survey has performance issues, we remove the incentive granted to the panelist. By implementing this measure, we uphold the quality and reliability of our sample.
• Communication and feedback: We email the affected panelists, informing them of their survey performance and providing constructive feedback. Doing so encourages a high level of engagement among panelists and promotes continuous improvement and active involvement in future surveys.

Conclusion

ThinkNow takes pride in our commitment to ensuring the quality of the sample we provide our clients. We have implemented robust security measures like fingerprinting, phone validation, email verification, and geolocation which instill confidence in the authenticity and integrity of our data. In the rare event of a quality issue, our protocol enables us to promptly and effectively address challenges, safeguarding the quality of our sample. We are committed to providing reliable and representative results to our clients and continue to invest in the tools that enable us to do that.