How can you collect accurate consumer perceptions and attitudes data?

- Design concise and clear surveys to gather quantitative data on consumer perceptions and attitudes. - Use a mix of closed-ended and open-ended questions to capture both specific responses and qualitative insights. - Distribute surveys through various channels like email, social media, or through your website to reach a broad audience.

I have seen excellent surveys fail because the team who will need to respond to the results says the attributes are not actionable. Combine your quantitative surveys with focus groups or in-depth interviews. Do not depend on open-ended follow up questions. Have the team that will apply the research present for qualitative interviews. Use the customers’ own language to finalize the attribute wording. Rewrite any attribute that evaluates multiple qualities…what do you do with “fast and friendly?” When customers in your qualitative research point out issues ask them for their solutions to the problems. Weave the customers’ solutions into an action plan playbook so there is no debate about the actionability of the survey attributes.

Obviously any research has to start with objective. When you are clear on that, your questionnaire will be sharp & avoid unnecessary sections. There has to be discipline here as many a times, I see questionnaires that have questions that are never used in later decision making. The length of the questionnaire itself depends on what kind of methodology are you using - is it at home where you have a lot of time? Is it outdoors, at a shop where you have to be quick? Is it online... better be short to get accuracy and not clicks to just finish survey.

Nail down your research goals before diving into data collection. Clearly defined objectives and questions will steer your methodology, sample size, and analysis, ensuring you gather the right insights to address your research aims. For instance, measuring customer satisfaction calls for a survey or rating scale, while exploring customer motivations demands interviews or focus groups.

To collect consumer perceptions and attitudes data, you need to select a method that aligns with your research objectives, questions, budget, and time. There are various methods available, such as surveys, interviews, focus groups, observations, experiments, or online reviews. Each method has its strengths and limitations in terms of cost, speed, ease, depth, and validity of data. For example, surveys can be cheap, fast, and easy, but they may not capture the complexity and nuance of customer insights. Interviews and focus groups can be more qualitative and interactive, but they may be expensive, time-consuming, and biased. After collecting your data, you need to analyze and interpret it in a way that addresses your research goals.

In my capacity as a Marketing Manager for a food delivery app, selecting the right data collection methods is critical for accurate consumer insights. We use a mix of online surveys for quick feedback, in-depth interviews for detailed insights, and app analytics for real-time user behavior. Each method serves a specific purpose: surveys for broad trends, interviews for deeper understanding, and analytics for actual usage patterns. This multi-method approach ensures we gather comprehensive data, essential for making informed decisions that truly resonate with our customers.

Conduct focus group discussions with a diverse mix of consumers. For successful data collection use skilled moderators to facilitate the discussion and probe deeper into consumer attitudes and perceptions.

In my experience based on an objective you have in mind, you need to ensure your sample is diverse and representative of your target audience, then you need to employ mix of qualitative and quantitative research methods, surveys, interviews, focus groups, etc. in addition monitoring social media to receive real-time feedback and SOV on special subject can give you more insight to finalize your research method, although for quick surveys using online version both by email or SNS have been really useful in my field of work.

The most powerful source of customer data are direct interviews, yet this part of research often gets missed. There is no research quite like the voice of your past customers. They will tell you everything you need to know about your offering if you ask them the right questions. When I conduct interviews, I follow this cadence: what was going on in your life before "x", what triggered you to buy "x"; what objctions did you have to buying "x" and what does your life look like after "x". This will give you the messaging map for your offer and most of your marketing. Good luck!

One thing that helps choose an adequate sample is considering the target audience/market as consisting of smaller segments. Choosing separate samples from these smaller audiences/segments will help to get a representative sample. This is called stratified sampling and criteria such as age, gender, or location can be used for dividing the larger population into smaller groups. Assuming that every member of a moderately sized target population shares similar attitudes, perceptions, or behavior isn't realistic. Acknowledging the differences (i.e., heterogeneity) within the population before conducting the research significantly influences arriving at more dependable and generalizable findings.

In my role overseeing marketing for a food delivery app, choosing a representative sample is key for genuine consumer insights. We focus on diversity, ensuring our sample mirrors our varied customer base—age groups, geographic locations, and user frequency. This approach isn't just about numbers; it's about inclusivity. We strive for a balance between regular and occasional users, and urban and rural customers, to get a well-rounded view. This method helps us avoid biases and truly understand the diverse needs and preferences of our entire user spectrum.

There's no single way of doing so, perhaps the reason why its important to take a multi-pronged approach and triangulate. If we are to consider the era we in, digital ways of collecting consumer perceptions and attitudes is much easier and quicker than traditional methods. However, at business level, this requires substantial investment in ICT infrastructure, especially big data analytics.

Some important steps here… 1 - understand your audience. Do some desk research. Try to understand the incidence of your audience before you reach out to suppliers. Don’t be blind sided by requesting costs for a method that can’t support your needs. 2 - understand the demographic breakdown of your audience. Don’t just ask for Nat rep quotas because “thats what we always get”. Some audiences will be heavily weighted towards different demographics, so WHO you need and target/quota accordingly. 3 - Plan the amount of completes you need, based on the data collection method and audience you are going after. An online survey may need 100, 500 or 1,000 completes. Yes a traditional qual survey may need two or three groups of 30/50 completes.

Seleccionar una muestra representativa es fundamental; es como asegurarte de que todas las voces sean escuchadas en una reunión importante. Si te enfocas solo en un tipo de cliente, digamos los millennials, te pierdes de la visión completa. Es como armar un rompecabezas pero solo con piezas del cielo; te falta el resto del paisaje. Y claro, hay que tener cuidado con el tama?o de la muestra. Demasiado peque?a y tus conclusiones pueden ser tan inestables como una mesa coja. Demasiado grande y quizás estés gastando recursos que podrías invertir en otra parte. La clave está en encontrar ese punto dulce donde tienes suficiente variedad y cantidad para que los resultados sean sólidos y se puedan aplicar bien a lo que necesitas.

Analyze online reviews too cos while some complain, others explain what really drives value. Eyes on the positives helps win over more fans.

It is important to ensure the view of a minority is not assumed to be the view of the majority. Those with something negative to say are always more vocal. I also recommend using multiple sources to back up and support any findings.

In analyzing survey data, going over descriptives then running factor analysis, correlation analysis or regression using specialized software is common in understanding the data and the interaction between variables/questions. Getting rid of outliers is a good way to overcome certain problems. A potential issue in interpretation is not knowing the limits of the method used. For instance, insights from interviews and focus groups should not be used to arrive at larger decisions as they may not reflect the target market's/audience's point of view well. Conversely, survey data may be biased as it is not straightforward to prepare neutral, easy-to-understand questions and respondents may not be totally honest with their answers.

After collecting data, analyzing and interpreting it is crucial to derive meaningful insights. Start by aligning your analysis with research objectives and questions. Depending on the data collection method, employ suitable analysis techniques like descriptive statistics, inferential statistics, content analysis, or thematic analysis. Utilize tools and software to organize, visualize, and summarize your data effectively. However, it's essential to exercise caution and avoid making false or misleading claims or conclusions from your analysis. Acknowledge the limitations and assumptions of your data, ensuring transparency and credibility in your findings. By approaching analysis with diligence and integrity, you can extract valuable insights.

Two things I would add here to consider. 1 - ask for the screening data and see incompletes, as well as the completes. It’s not unusual to find data from respondents who have answered 80/90/95% of a survey, which isn’t included as a complete but this may come with some valuable open ended responses. 2 - be aware of the current market trends in whatever product/brand you are doing research on. It is possible that changes in consumer habits or consumer trends will effect your data and the normal reaction is to question the data collection method, but it’s equally possible that the data is a true reflection of the market.

This comes down to choosing the right supplier. Any reputable MRA will do all the data validation for reliability and accuracy on their assets on a regular basis. Data quality is the life blood of data suppliers and lots of time and money is spent on ensuring a high quality product, but don’t be tempted to cut corners and just go for the cheapest option. There are many different options within quant and qual, online and offline. Know who you are speaking to and what they offer. Don’t be blind sided by cost and/or speed if your priority is on a different attribute.

Community Forums and Discussion Boards: Monitor and participate in relevant community forums and discussion boards to gather insights about consumer perceptions.

Validar y verificar datos es como hacer una inspección final de un producto; te aseguras de que todo esté en perfecto estado antes de sacarlo al mercado. Es un paso que no puedes saltarte. La validación es asegurarte de que lo que mides es realmente lo que buscabas medir. La verificación es como un control de calidad, para tener confianza en que si repites el proceso, los resultados serán los mismos. Herramientas como la comprobación cruzada y la triangulación son como tener una segunda y tercera opinión. Dedicar tiempo a estos pasos es esencial para que al final, los datos que tienes sean robustos y puedas tomar decisiones empresariales con confianza.

Interpret the data without any bias. Read the feedback as it is, sometimes it may be not conclusive Have one or two more team members also interpret the information

To gather precise perceptions and attitudes data, drafting clear objectives, blending qualitative and quantitative methods, and ensuring a representative sample. Use random sampling, unbiased questioning, use of technology, and rigorous data checks to generate dependable and true insights. On top of that, you can leverage longitudinal studies to enhance the accuracy of the collected data.

Social Media Monitoring and Analysis: Utilize social media listening tools to monitor consumer conversations about your brand, products, or industry. Analyze sentiments, trends, and common themes in social media discussions.

Analyze online reviews on platforms such as Google, Yelp, and Amazon to understand customer perceptions and attitudes towards your products or services.

Las agencias de investigación de mercados tienen dise?ados algunos modelos y baterías de preguntas estandarizados para medir las percepciones de los consumidores. Auditorias de Mercado para conocer la participación, inventario en punto de venta, agotados. Prueba Ciega de Producto para conocer las percepciones sobre la calidad del producto. Personalidad de la marca. Para conocer qué piensan los usuarios sobre la marca. Y muchos estudios más. Tomar decisiones y acciones con la información obtenida de un estudio de grupos focales implica tomar riesgos muy altos ya que es el resultado de grupos de personas. Con los resultados del grupo focal, se deben validar con otro estudio de encuestas a una muestra representativa de la población.

Collecting accurate consumer perceptions and attitudes data is crucial to understand the target audience and make informed decisions. While there is no one correct way and one size does not fit all, deploying some of these methods help to gather accurate data on consumer perceptions and attitudes. Well crafted surveys, In depth interviews, Focus groups, Social Media listening, Online reviews and feedback, Observational research, purchase data analysis, psychographic Segmentation, ethnographic research. Combine multiple methods to triangulate data and gain a comprehensive understanding of consumer perceptions and attitudes. Regularly update your research approaches (IMP) to stay attuned to evolving consumer sentiments in a dynamic market.