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How can you avoid sample bias when sampling for international markets?

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Sampling for international markets is a challenging but essential task for any marketer who wants to understand the needs, preferences, and behaviors of potential customers across different regions and cultures. However, sampling for international markets also involves the risk of sample bias, which is the systematic error that occurs when a sample is not representative of the target population. Sample bias can distort the results of your marketing research and lead to inaccurate or misleading conclusions. How can you avoid sample bias when sampling for international markets? Here are some tips to help you design and execute a reliable and valid sampling strategy.

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Kiran Giradkar

LinkedIn Top Voice ● Group CMO ● Passionate FMCG Marketer ● Storyteller ● Hiker ● 20+ Yrs of few successes & lot…
G?zde Akyol ?ztürk

?Senior Marketing Executive?FMCG?Food&Beverage Luxury Goods?Business Transformation?Brand Strategy?Growth…
Nelson Raju

Team Lead Reference Data at NielsenIQ || Ex Reliance || Ex Casagrand || Ex HDFC.

1 Define your target population

The first step to avoid sample bias is to clearly define your target population, which is the group of people or units that you want to study and generalize your findings to. Your target population should be based on your research objectives and the criteria that are relevant for your marketing decision. For example, if you want to test the demand for a new product in Europe, your target population might be defined by geographic location, age range, income level, and product category. You should also consider the size and diversity of your target population, as this will affect your sampling method and sample size.

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Kiran Giradkar

LinkedIn Top Voice ● Group CMO ● Passionate FMCG Marketer ● Storyteller ● Hiker ● 20+ Yrs of few successes & lot failures breathing India's stellar brands – Parle | Bajaj | Bisleri | Camlin | Storia | Nilon’s | Nutrica
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First thing first, define your TG. For example - let's say F&B brand from India wants to conduct survey for ethnic Indian spices for US market, then look for geographies where Indian diaspora is residing. Next sampling method is very important. If Indians like to cook food by themselves at home then go for In-House Usage test as a sampling method. The sample size for such tests depend on budgets but as long as it's statistically validated then go for it. For instance Sample size for Indian diaspora in US can be managed in 100s while in India it runs into 1000s. While doing all these researches please do not bring personal biases and ensure consistency in data integrity. Post analytics it can also be validated by some KOLs.

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Nelson Raju

Team Lead Reference Data at NielsenIQ || Ex Reliance || Ex Casagrand || Ex HDFC.
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Strategies to avoid sample bias To avoid sample bias when sampling for international markets, it is essential to implement effective strategies tailored to the specific market. Here are some strategies to consider: 1. Clearly define the target population Before conducting any research, clearly define the target population and understand its characteristics. 2. Utilize regional expertise and local partners Partnering with local experts and organizations can provide valuable insights and ensure a more comprehensive representation of the market. 3. Employ random sampling techniques Random sampling involves selecting participants randomly from the target population, ensuring each individual has an equal chance of being included in the sample.

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Jason Ong 王励德 ????

LinkedIn Top Voices in CRM and Customer Service - CRM & Data Insights/Partnerships/Digital Transformation/ Strategist/Speaker
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Ensure all markets and profile segments within each market are identified and targeted to ensure a comprehensive and fair survey coverage for relevant study and comparison.

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2 Choose an appropriate sampling method

The next step to avoid sample bias is to choose an appropriate sampling method, which is the technique that you use to select a subset of your target population for your marketing research. There are two main types of sampling methods: probability and non-probability. Probability sampling methods involve random selection of the sample units, which means that every member of the target population has an equal chance of being included in the sample. Probability sampling methods reduce the risk of sample bias and increase the generalizability of your results. However, they also require more time, resources, and access to the target population, which might not be feasible for some international markets. Non-probability sampling methods involve non-random selection of the sample units, which means that some members of the target population have a higher or lower chance of being included in the sample. Non-probability sampling methods are easier, faster, and cheaper to implement, but they also increase the risk of sample bias and limit the generalizability of your results. You should choose a sampling method that best suits your research objectives, budget, and availability of data.

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Jason Ong 王励德 ????

LinkedIn Top Voices in CRM and Customer Service - CRM & Data Insights/Partnerships/Digital Transformation/ Strategist/Speaker
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Choose sampling methods that are best applicable to all markets to be fair and comparable without bias. Choosing different methods will pollute the results.

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3 Calculate an adequate sample size

The third step to avoid sample bias is to calculate an adequate sample size, which is the number of sample units that you need to collect for your marketing research. Your sample size should be large enough to ensure that your results are statistically significant and representative of your target population, but not too large that it becomes inefficient and costly. To calculate your sample size, you need to consider several factors, such as the level of confidence, the margin of error, the variability of the target population, and the sampling method. You can use online calculators or formulas to estimate your sample size, or consult a statistician or a marketing research expert for guidance.

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Jason Ong 王励德 ????

LinkedIn Top Voices in CRM and Customer Service - CRM & Data Insights/Partnerships/Digital Transformation/ Strategist/Speaker
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Sample size is key to whether the results obtained are accurate. Ideally, the sample size per market should be the same too. Some have to go proportionate as some markets are too small and some are too big.

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Leonardo Werneck

TREINAMENTO E DESENVOLVIMENTO PROFISSIONAL | Como desenvolver seu branding pessoal no Linkedin | Consultoria em Linkedin | Orientador softskills para o Mercado | SENAC-RJ | Cursos Online | Consultor de Negócios
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Quando falamos de coleta e interpreta??o de grandes volumes de dados n?o temos como deixar de citar a enorme revolu??o que a IA está fazendo neste campo. E a maior revolu??o nas técnicas de pesquisa ser?o promovidas pelos algoritmos cada vez mais poderosos e com auto aprendizado. Os algoritmos de IA podem ser treinados para identificar e mitigar viéses implícitos nos dados, como viés de confirma??o ou viés cultural. Isso é feito por meio de técnicas de aprendizado de máquina que ajustam automaticamente os modelos para minimizar o impacto desses viéses.

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4 Ensure data quality and consistency

The final step to avoid sample bias is to ensure data quality and consistency. This means that your data collection and analysis processes should be accurate, reliable, and standardized. Sources of error, such as measurement, non-response, response, and processing errors can affect data quality and consistency. To prevent or minimize these errors, you should design clear and relevant survey or questionnaire questions and scales. Additionally, you should use multiple languages and cultural adaptations for your survey or questionnaire, test and pilot it before launching it, use multiple channels and incentives to reach your respondents, monitor the response rate and distribution, clean your data for errors and outliers, use statistical techniques and software to analyze the data, and interpret and report the results with caution and transparency. Following these steps will help you avoid sample bias when sampling for international markets as well as conducting more effective marketing research.

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Leonardo Werneck

TREINAMENTO E DESENVOLVIMENTO PROFISSIONAL | Como desenvolver seu branding pessoal no Linkedin | Consultoria em Linkedin | Orientador softskills para o Mercado | SENAC-RJ | Cursos Online | Consultor de Negócios
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A inteligência artificial terá papel fundamental para garantir a qualidade dos dados das amostras de pesquisa. Só para citar algumas contribui??es temos: 1) Analisar grandes volumes de dados de feedback do consumidor, como comentários em redes sociais, avalia??es de produtos e opini?es em pesquisas, para identificar padr?es e tendências de sentimentos dos consumidores em rela??o a produtos ou servi?os específicos. 2) PLN (Processamento de Linguagem Natural), a IA pode interpretar e entender a linguagem humana em diferentes idiomas, ajudando a extrair insights para pesquisas de consumidor, e-mails entre outras.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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G?zde Akyol ?ztürk

?Senior Marketing Executive?FMCG?Food&Beverage Luxury Goods?Business Transformation?Brand Strategy?Growth Management?Nestlé and Coca-Cola Alumnus?Currently Head of Strategy&Effectiveness in Pernod Ricard
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All general rules apply here, additionally you can engage with a local partner that already has knowledge and experience in local dynamics; that can carry the operations for gathering, recording and analyzing the data for you.

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Christian Abramson

Fundador cübik e Mind to Mind. Estratégia de marketing, experiência do cliente, trade marketing, pesquisa. Consultor, CMO as a Service, palestrante, advisor. Top Voice Consumer Behavior. Empreteco. Colunista HSM.
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Trabalhei mais de 20 anos em multinacionais e acredito que n?o haja um caso minimamente aceitável de amostra “mundial”. S?o mais de 5 bilh?es de seres humanos. Ainda que avaliando categorias, nichos, grupos, s?o dezenas de milh?es no mundo, provavelmente. Acredito que seja melhor escolher mercados relevantes com go to market, competidores, hábitos, culturas minimamente marcantes e importantes para se considerar e ter amostras que os considere um universo amostral, avaliando ent?o as diferen?as entre cada um, levando às considera??es necessárias. Eu n?o olharia, nunca, uma amostra “internacional”, “global”. Isso n?o existe. Será uma média. E ninguém é uma média, ainda mais se falarmos do Planeta Terra todo.

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Leonardo Werneck

TREINAMENTO E DESENVOLVIMENTO PROFISSIONAL | Como desenvolver seu branding pessoal no Linkedin | Consultoria em Linkedin | Orientador softskills para o Mercado | SENAC-RJ | Cursos Online | Consultor de Negócios
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Administrar negócios globais n?o é tarefa fácil. Economias, políticas e culturas diferentes e entender preferências e comportamentos de compra dos consumidores torna-se indispensável. A Serasa Experian mapeou as 5 áreas que tiveram maior foco das institui??es globais no pós pandemia: inteligência artificial, preven??o à fraude, reconhecimento digital do cliente, novos modelos analíticos e análise de risco de crédito.

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How can you avoid sample bias when sampling for international markets?

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1 Define your target population

2 Choose an appropriate sampling method

3 Calculate an adequate sample size

4 Ensure data quality and consistency

5 Here’s what else to consider

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