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Conjoint Analysis is a market research technique used to understand how consumers value different product or service features. It involves presenting participants with a series of product profiles that vary in their features and asking them to rate or choose the profiles they prefer. By analyzing the data collected, researchers can determine each feature’s relative importance and how consumers trade off one feature for another. Conjoint Analysis helps companies make informed decisions about product design, pricing, and positioning.

Conjoint Analysis and Trade-off Analysis are essentially the same. Conjoint Analysis is a more commonly used term, but Trade-off Analysis is also widely used in market research. Conjoint Analysis and Trade-off Analysis are also known by other names, such as:

Conjoint Study
Multi-attribute Trade-off Study
Conjoint Measurement
Conjoint Analysis Method
Conjoint Analysis Technique
Conjoint Methodology
Conjoint Analysis Experiment

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Conjoint Analysis has its roots in mathematical psychology in the 1960s. It was first used in market research in the 1970s and has since become one of the most widely used methods for understanding consumer preferences for product features. Sawtooth Software founder Dr. Fred McCollum conducted the first Conjoint Analysis study in the 1970s. He used the technique to study the features customers valued in different types of products. McCollum’s work laid the foundation for developing Conjoint Analysis as a widely used market research tool. Since then, Conjoint Analysis has been adapted and refined to meet the changing needs of market research and is now used in a wide range of industries to help companies make informed decisions about product design, pricing, and positioning.

Conjoint Analysis is a type of quantitative market research. It uses statistical methods to quantify consumer preferences and trade-offs, making it a numerical and data-driven approach to market research. The results of Conjoint Analysis are typically presented in graphs, tables, and statistical models.

The market research formulas typically used when analyzing data from a Conjoint Analysis study include:

Part-Worth Utilities: Part-Worth Utilities are the most commonly used metric in Conjoint Analysis. They quantify the relative importance of each product feature and the trade-off between different features.
Regression Analysis: Regression analysis examines the relationship between product features and consumer preferences and identifies which features are most influential in driving consumer behaviour.
Multivariate Analysis of Variance (MANOVA): MANOVA is used to analyze the differences in consumer preferences across demographic groups and to identify differences in product preferences between sub-groups.
Logit Regression: Logit Regression analyzes binary choices, such as the choice between two product options. It is used to model consumer choice behaviour and to predict which product features are most likely to influence consumer choices.
Conjoint Simulation: Conjoint Simulation is used to forecast consumer behaviour based on the results of the Conjoint Analysis. It predicts how consumers will respond to different product profiles and identifies the most appealing product configurations.

Like everything in life, Conjoint Analysis has both pros and cons.

The pros of conducting Conjoint Analysis:

Insights into Consumer Preferences: Conjoint Analysis provides valuable insights into what consumers value in a product or service and how they trade off one feature for another. This information can inform product design, pricing, and positioning decisions.
Realistic Scenarios: Conjoint Analysis presents participants with real product scenarios, making it a more accurate reflection of real-world purchasing behaviour.
Large Sample Size: Conjoint Analysis is a scalable research technique and can be used to gather data from large sample sizes, providing more robust and representative results.
Cost-effective: Conjoint Analysis is relatively cost-effective compared to other market research techniques, such as focus groups and individual interviews, making it an attractive option for many companies.

Conversely, some of the disadvantages or cons of Conjoint Analysis include:

Limited Feature Options: Conjoint Analysis may only be able to capture consumer preferences for a limited set of product features and may not be suitable for studying the impact of unusual or unique features.
Response Bias: There is the potential for participants to exhibit response bias, where they may choose product profiles based on factors other than the features presented, such as brand or price.
Complex Analysis: Conjoint Analysis requires complex data analysis to extract meaningful insights and may be challenging for researchers without specialised training.
Limited Context: Conjoint Analysis presents product profiles in a laboratory setting, which may not accurately reflect real-world purchasing behaviour in different contexts, such as in-store or online.

Minimizing respondent bias is essential in any market research study, including Conjoint Analysis. Here are some steps that you can take to mitigate respondent bias in a Conjoint Analysis study:

Use a representative sample: Using a representative sample of the target population can help to minimise the impact of respondent bias, as the results will be more representative of the broader population.
Use blind or randomised presentation: To minimise the impact of order effects or other biases, it can be helpful to present the product configurations randomly or to use a blind presentation, where the respondents do not know the identity of the product or brand being evaluated.
Avoid leading questions: Care should be taken to avoid asking leading questions or using language that could influence the respondents’ responses.
Provide clear instructions: Providing clear and detailed instructions to the respondents can help to minimise misunderstandings and ensure that the responses are accurate and meaningful.
Use incentives to increase response quality: Providing incentives to the respondents can help to improve the quality of the responses and to encourage respondents to take the time to evaluate the product configurations thoughtfully.
Pre-test the survey questionnaire: Conducting a pre-test of the survey can help identify and address any potential biases or problems with the questions and improve the quality of responses.
Consider using multiple methods: Conjoint Analysis can be combined with other forms of market research, such as in-depth interviews or focus groups, to help validate the results and minimise the impact of respondent bias.

In addition, Conjoint Analysis may be best suited to specific industries than others. Industries that typically use Conjoint Analysis:

Consumer Goods: Conjoint Analysis is widely used in the consumer goods industry to understand consumer preferences for product features in categories such as packaged goods, electronics, and appliances.
Healthcare: Conjoint Analysis is used in the healthcare industry to understand patient preferences for medical treatments, procedures, and healthcare services.
Financial Services: Conjoint Analysis is used in the financial services industry to understand consumer preferences for financial products and services, such as credit cards, loans, and insurance products.
Automotive: Conjoint Analysis is used in the automotive industry to understand consumer preferences for vehicle features, such as safety, performance, and design.
Telecommunications: Conjoint Analysis is used in the telecommunications industry to understand consumer preferences for mobile phone features, such as camera quality, battery life, and screen size.

However, if Conjoint Analysis is suitable for your brand, product, or service, you can expect the following strategic outcomes from conducting a Conjoint Analysis research study:

Improved Product Design: Conjoint Analysis provides insights into the relative importance of different product features and the trade-off between various features. This research can be used to design products that better meet the needs and preferences of consumers.
Better Understanding of Consumer Preferences: Conjoint Analysis provides a detailed understanding of consumer preferences and behaviours, which can be used to inform product design, pricing, and marketing decisions.
Improved Pricing Strategy: Conjoint Analysis can help determine the price sensitivity of consumers for different product features, allowing a company to set prices that are competitive and in line with consumer preferences.
Increased Market Share: By designing products that better meet the needs and preferences of consumers and by pricing products in a way that is competitive and in line with consumer preferences, a company can increase its market share and improve its competitiveness.
Better Segmentation: Conjoint Analysis can help identify differences in consumer preferences across demographic groups and can be used to inform targeted marketing and product design strategies for different segments of the market.
Improved Product Development: Conjoint Analysis can be used to test new product concepts and to identify which ideas are most likely to be successful in the market. These insights can be used to improve the success rate of product development efforts.
Better Decision Making: Conjoint Analysis provides objective and data-driven insights into consumer preferences and behaviours, which can be used to support informed decision-making in product design, pricing, and marketing.

Another important consideration before embarking on a Conjoint Analysis research study is that they typically analyze between 4 to 10 features or attributes.

For example, a Conjoint Analysis study of a smartphone product may analyze 4 to 6 features, such as screen size, camera quality, battery life, and storage capacity. A Conjoint Analysis study of a car may analyze 8 to 10 features, such as fuel efficiency, safety features, interior design, and entertainment systems.

A maximum number of features is critical because Conjoint Analysis presents participants with trade-off scenarios between different product features. Too many attributes or features can make the trade-off decisions overwhelming and unrealistic. Additionally, analyzing too many features can increase the complexity of the Conjoint Analysis design, making it more challenging to interpret the results.

Because there are limitations with the number of features to include in a Conjoint Analysis research study, researchers and product managers can determine which trade-offs to include in the study by:

Identifying the most important product attributes: Researchers should identify the product characteristics that are most important to consumers and have the most significant impact on their purchasing decision. This information can be obtained through market research techniques such as focus groups, surveys, and competitor analysis.
Determining the level of variability for each attribute: Researchers should assess the level of variability for each product attribute, such as low, medium, or high. This will help determine the number of levels for each feature included in the Conjoint Analysis study.
Determining the feasibility of including all attributes: Researchers should evaluate the feasibility of having all attributes in the Conjoint Analysis study. Some attributes may be too complex or difficult to measure or need more variability to make meaningful trade-off decisions.
Considering the trade-off between complexity and accuracy: Researchers should consider the trade-off between complexity and accuracy when determining which attributes to include in the Conjoint Analysis study. A study with too many features may be too complex for consumers to understand and respond to, while a study with too few attributes may not provide enough information to predict consumer behaviour accurately.
Testing the attributes in a pilot study: Researchers should conduct a pilot study with a small sample of participants to test the attributes or features and make any necessary adjustments before running a full Conjoint Analysis study.

These points will help determine which product feature trade-offs to include in a Conjoint Analysis study that provides meaningful and statistically significant results.

Once the trade-offs are determined for the study, typical steps taken when conducting a Conjoint Analysis Market Research Project include:

Step 1 – Design and Development: The first step is to design the Conjoint Study, including developing product profiles, feature sets, and questions for participants. This stage usually takes several weeks to a few months, depending on the complexity of the study.

Step 2 – Recruitment: Participants are recruited for the study, which may involve online surveys, telephone interviews, or in-person focus groups. Recruitment can take weeks to months, depending on the sample size.

Step 3 – Data Collection: Once participants are recruited, data is collected. Again, this stage can take several weeks, depending on the sample size and complexity of the study.

Step 4 – Data Analysis: The collected data is then analyzed to determine the relative importance of different features and how consumers trade off one feature for another.

Step 5 – Report Preparation: The final stage is to prepare a report that summarises the findings of the Conjoint Study and provides actionable insights for the client.

Once the decision is made to run a Conjoint Analysis research study, brands should find a reputable market research agency to run the study.

The benefits of hiring an external market research agency like Kadence International to conduct a Conjoint Analysis study are:

Expertise: Market research agencies have the knowledge and experience necessary to design and conduct high-quality Conjoint Analysis studies, ensuring the results are accurate and meaningful.
Objectivity: An external market research agency can provide an objective perspective on the findings of the Conjoint Analysis, free from any internal biases or conflicts of interest.
Access to Resources: Reputable market research agencies have access to a range of resources, including data collection and analysis tools, that can significantly improve the quality and efficiency of the Conjoint Analysis study.
Time and Cost Savings: Hiring an external market research agency can save time and reduce the cost of conducting a Conjoint Analysis study, as the agency can manage all aspects of the study, from design and development to data collection and Analysis.
Increased Credibility: An external market research agency provides credibility to the results of the Conjoint Analysis study, as the agency is independent and impartial and has a reputation to uphold.
Expert Interpretation: Market research agencies have the expertise to interpret the results of the Conjoint Analysis study and provide actionable insights and recommendations to the client. This can help you make informed decisions and drive growth.

Big data and advanced analytics are hot. Voluminous sets of data can be processed automatically using technology. But the data becomes useful only when it is converted into meaningful information. While Big Data has become the buzzword today, it is of little use if it’s not profitably analysed.

The global Big Data and Analytics market is worth USD 274 billion. Around 2.5 quintillion bytes worth of data is generated each day. There are currently over 44 zettabytes of data in the entire digital universe.

So what is big data exactly, and how does it impact companies?

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Big data refers to large sets of data obtained from multiple sources, like medical records, government records, customer databases, mobile applications, search engines, business transactions, social networks, and other massive data sources. Big data may be structured or unstructured, allowing brands to manage large amounts of data more efficiently. Many organizations are moving away from legacy systems and consolidating data to make the research process seamless, cost-effective, and efficient.

Technologies like text analytics help market researchers examine large amounts of information and data in real-time to track consumers’ sentiments and detect potential brand reputation issues before they become serious.

Big data market research is invaluable for brands as it combines consumer and behavioural data with advanced analytics to enable faster decision-making that yields improved business outcomes. When big data and market research converge, everyone wins because it results in better, more relevant products and services for the consumer and a competitive advantage for the brand.

Big data and market research convergence allow brands to dig into data to uncover the “why” behind the numbers. Let’s say, for instance, a brand uses data mining to discover a sudden decline in the market share for a high-end product in a specific market. Using market research methodologies, it studies a sample of consumers that have exhibited a change in buying behaviour to unearth what led to the change. Was it a new product that entered the market, or did they reduce spending due to the economic climate?

These reasons are not presented in the data, and market research can help uncover the “why” behind a data set.

Today, the digital consumption of information, products, and media makes everything measurable on a large scale. Social media analytics is an example of big data used on a massive scale globally.

How does big data impact business?

A 2020 study showed that around 94 percent of organizations believe data and analytics are essential to growing their brand and supporting digital transformation. The study also found that the financial, hospitality, telecoms, and retail industries invest the most in big data and analytics.

Big data in the Banking and Financial Services sector

The application of big data analytics has allowed financial services companies and banks to become more efficient, customer-centric, and competitive. This industry utilises big data to make transactions, trading, and financial activities seamless for their employees and customers.

Retail and eCommerce

The eCommerce and retail industries collect data through their Point of Sale (POS) systems, loyalty programs, and website browsing behaviour. It also helps with inventory replenishments.

In the eCommerce industry, knowing your customers can unlock conversions and profits. Big data on real-time consumer behaviour, purchase history, and consumer preferences can help online stores recommend the most relevant products and offer them to consumers at the right time. Big data enables e-stores to conduct competitive analyses and pricing to lure consumers. Above all, technology allows online retailers to offer personalization, superior customer service, and experience.

While these industries invest heavily in big data, they are not the only ones. Many sectors like manufacturing, logistics, media, oil and gas, and healthcare are investing large sums of money in adopting this technology to manage their data efficiently.

Big Data analytics for the healthcare industry is expected to reach USD79.23 billion by 2028.

For most companies, data is fragmented, and brands are looking for people who can analyze and use data to optimise all business processes and functions.

Big data impacts not only the private sector but also the public sector. For governments, big data has many applications, including health-related research, financial markets research, fraud detection, public safety, transportation, and environmental protection, to name a few.

Advantages of Big Data

Massive organizations like Google, Facebook, and Amazon have proved how big data can build big brands. These organizations have capitalised on big data mining and analytics to grow their brands and boost market valuations.

One of the most significant advantages of big data is the ability to make informed decisions based on hard data and facts.

Big data is valuable for consumers too. In the information age, the consumer can access ratings, product reviews, and an easier means of providing instant real-time feedback. This allows consumers to make informed choices.

What are the challenges with big data and analytics?

As recently as last year, Facebook’s Mark Zuckerberg, Google’s Sundar Pichai, and Jack Dorsey of Twitter had to testify before Congress about the steps they have taken to deal with data privacy.

Consumers have become more data savvy and are concerned with privacy issues and breaches. <add stats on #s ready to share data for more relevant messaging)

Business outcomes are only as good as the data; high-quality data (link) is of utmost importance. Researchers and brands must be cautious about the data sources and methodologies to obtain the most accurate, reliable, and relevant data.

The big data market is poised for phenomenal growth in the coming years. With the development of technology penetration across all areas of life, digitization, and the widespread use of smartphones globally, large amounts of data are produced every second. This has led to the need for data analysis and big data.

As brands apply big data, they make data-driven decisions faster and can respond quickly to market changes. This has a direct impact on their bottom line. But data is not enough; there has to be a fusion of data science with marketing science to help market research become more effective.

Kadence International helps leading brands make game-changing decisions. If you are looking for a research partner to help better understand your customers, we would love to help. Fill out our Request for a Proposal here.

According to the Global Research Business Network (GRBN), confidence in the market research industry has remained stable, and trust in data analytics has increased in 2022 compared with 2020.

Still, market research as an industry needs to constantly work to improve the perceived value of research. The way to ensure this happens is by addressing the main challenges of obtaining high-quality data.

The importance of data collection in market research cannot be emphasised enough. This blog post will analyze the main obstacles brands face in this area and provide guidance on how market researchers can tackle these challenges with the help of technology.

The methods you use to collect and analyze data will significantly impact the quality of your market research report and its value in decision-making. The five best data collection tools for market research are surveys, interviews, focus groups, observation, and secondary sources.

Understanding the best methodology to get the most accurate, error-free, and reliable data is essential.

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What is data quality?

Data quality is a complex, multi-faceted construct. Quality data is data that is fit for its purpose and closely relates to the construct they are intended to measure.

Let’s take the example of a brand like Amazon’s Audible and try to predict what type of books a person would be interested in based on his previous listening history. The data is likely high quality because the books subscribers have listened to in the past are a good predictor of what they would like to consume in the future. The books they have listened to in the past also have a close relationship with what you are trying to measure, in this case, book preferences, which makes the data high quality.

Reliable data requires a high-quality sample with enough information to make conclusions that inform business decisions. For instance, in the same example of Audible, if a subscriber uses it only once in a while and has only listened to one book in six months, it fails to present a complete picture of the user’s preferences due to limited data or information available.

In the example used above, the data is available in the app and is much easier to collect. However, this is not always the case. Many instances of market research involve collecting data from people taking surveys, user testing, or recollecting past experiences and feedback, which are much more challenging to measure.

So how do you ensure you collect high-quality data that informs decision-making at every step of the organization?

Utilise technology

As the world has moved online, so have many market research methodologies. Many companies have been forced to move online quickly, which has been a blessing in disguise for them. Technologies like automation and Artificial Intelligence (A.I.) have allowed brands to obtain transparent, reliable, and accurate data more efficiently.

Technology can also be beneficial in identifying bad data. Automation helps select the best pool of candidates for a study and helps achieve a more balanced view of the respondents. It can help reduce subjectivity and bias, scale costs, and improve project speed and efficiency.

Advanced profiling

To yield high-quality data, you must obtain a 360-degree view of the user or consumer. A good data scientist will study the consumer using all critical data points, like browsing history, purchase history, online behaviour, cart abandonment, geolocation, and other relevant data.

Proper Planning

Excellent outcomes need proper planning, which is valid for everything, including market research. The entire team must understand the research study’s objectives before doing anything else, including all the early actions, like identifying the right participants for the study. Researchers can then create a sample plan based on key objectives and participants. This will become the basis of the methodologies used and the survey designs. A good market research study also employs a screener to ensure they only include participants relevant to the study.

Recruit the right people

At Kadence, we firmly believe your research is only as good as the people participating in your study. When carrying out a virtual study or focus group, it is vital to make sure people doing the testing or surveys are genuine and suitable for the particular study. Researchers must hunt down even the most difficult-to-reach audiences, as you need the right people for the research to yield unvarnished results.

Ensure complete and active participation

Making surveys more engaging will always lead to higher participation in online surveys. A well-designed survey with clear instructions will ensure higher participation and more honest responses.

Throughout the survey, researchers can include questions to ensure participants are paying attention and potentially weed out those who are off-track and disengaged.

Screening dishonest participants

Researchers can go a step ahead to eliminate dishonest survey participants. Online surveys can identify potential red flags where people provide false demographic information so they can qualify for studies with high rewards.

Researchers can selectively target participants who have been profiled in the past to avoid participants with false demographic information.

Develop a system of efficient, consistent data quality checks throughout the process

Market researchers should always have an effective and efficient plan for weeding out bad data throughout the study. Automating and utilizing suitable technology can ensure you safely streamline the quality check process in real time.

A critical challenge with market research is the ethical collection and use of data. Discover why ethics are vital in data collection and how to ensure your data collection is always on the right side of law and ethics here:

The ultimate goal of market research is to obtain high-quality data that is accurate, relevant, and reliable. While well-planned and thoughtfully designed studies can yield effective results to inform decision-making, poorly planned and designed ones can lead to poor business outcomes.

The stakes are always high, so it is crucial for brands and researchers to constantly improve data quality and reliability to save time, money, effort, and resources and lead to better, more informed business decisions.

India is a diverse country having 29 States and seven Union Territories covering more than 600 districts, roughly 8,000 towns, and more than 0.6 million villages. The villages are spread over 3.2 million square kilometres supporting 65% of India’s total population. There is vast heterogeneity in population characteristics due to socio-cultural factors, caste-based divisions, and religious and linguistic diversity.

Specifically, in the Indian context, ensuring data capturing, and research methodologies are amenable to different languages, literacy levels, and differentiated access/familiarity with the internet is critical.

For the above reasons, research and data collection become a challenging task and calls for a robust and representative methodology to mirror India’s diversity.

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Key Challenges in Research & Data Collection

Given India’s cultural and geographical diversity, some of the critical challenges for marketers and researchers in designing a survey for rural India are listed below:

1. Reach: As per Census 2011, nearly 58 percent of India’s rural population resides in 115,080 villages having a population of 2000+. This effectively means that roughly 80% of the total villages in India are small or very small in size, inhabiting less than 2000 people. Looking at tapping rural markets, last mile connectivity with end consumers is a big challenge for FMCG players. Similarly, reaching the vast network of 33 million retail outlets in rural India is a challenge for companies, given the high distribution cost. Therefore, focused, and targeted reach is a priority in accessing rural markets. The survey design needs to factor in this critical consideration when designing the scope of research and sampling methodology.

2. Commercial Viability: It is estimated that 85,000 large villages in India account for 40% of the total population and 60 percent of the total consumption of FMCG categories. The skewness in demographic profile and purchasing power further limits the scope to cover the whole of Rural India for reasons of commercial viability.

3. High degree of heterogeneity: “A one size fits all approach” does not work well when designing a survey or methodology for rural India. For example, poor and backward States like Bihar, Uttar Pradesh, West Bengal, and Madhya Pradesh have more than 75-80% of their total population living in rural areas, whereas urbanized States like Tamil Nadu, Maharashtra, and Telangana and more equitable in terms of distribution. Therefore, each State has its unique demographic and socio-cultural profile, which must be kept in mind while designing the sampling methodology in any primary research survey.

4. Gender Inclusivity: Females are vital consumers and influencers of product categories in Rural India, but men are likely to be key purchasers. Therefore, “whom to interview” becomes a pivotal question to answer while designing a survey.

5. Linguistic Diversity: India has 22 official languages besides numerous local languages, dialects, and colloquial words. Therefore, linguistic compatibility becomes essential for survey administration in Rural India.

Methodologies for Rural Research

Some factors merit consideration while designing a methodology representative of the diversity of Rural India and are listed below:

Regional Representation
Adequacy of Sample Size
Defining “Rural” and therefore a selection of villages
Other Imperatives

1. Regional Representation

In a vast and diverse country like India, robustly researching rural consumers requires reflecting heterogeneity and ensuring representativeness. For example, people in the North have attitudes and behaviours that are distinctly different from the population in the South. Similarly, other regions also have socio-cultural nuances that often colour their opinions and attitudes, especially on sensitive issues.

Therefore, selecting Socio-Cultural Regions or SCR-s is often the starting point to decoding rural consumer behaviour. The regions make it easier to contextualize people and their behaviour for prevalent agrarian practices, social and cultural nuances, and crop-season-driven income and consumption patterns.

2. Adequacy of Sample

The population spread for different States in India varies a lot. For example, the most populous State, Uttar Pradesh, accounts for almost 15% of India’s population. On the other hand, the tiny State of Goa accounts for less than 0.5% of India’s population. Therefore, in a pan-India or multi-State survey, stratification of a sample by State becomes essential. Generally, States are categorized into different population bands such as high population states, medium population states, and low population states. The sample is then fixed for each band in terms of their population size to ensure adequate representativeness.

The sample size would also depend on other factors such as the granularity of data required within a State, and heterogeneity of population characteristics within a State et al.

3. Defining Rural

The Census of India defines a rural village as a settlement that has the following three characteristics:

A population of fewer than 5,000 people
<75 percent of the male population employed in non-agricultural activities and
Population density of fewer than 400 people per square kilometre

However, for commercial purposes, this vast and huge area coverage is logistically challenging to cover for any marketing company. Therefore, for practicality and feasibility, different definitions of rural are followed. For most companies, the “hub and spoke model” defines rural coverage as mapped to their distribution channels. They consider villages in the immediate vicinity or within a defined radius of the feeder towns. Last mile connectivity is a challenge for most companies in Rural India. Covering interior or remote parts of rural is not considered to be a viable option. Villages at the periphery of small towns/feeder towns that can be accessed easily become the “immediate” potential for targeting Rural India. This is also called the “Ringing Method” of village selection.

The above has a profound implication for researchers in terms of designing a suitable methodology and, more importantly, for deciding on an appropriate sampling methodology for the research.

4. Other Imperatives: There are a few other imperatives that one must be cognizant of while designing rural research methodologies:

o Permissions: Before any fieldwork in villages starts, it is crucial to approach the village head called the “Sarpanch” to apprise them of the survey and its objectives and take approval to conduct fieldwork. This is a formal authorization from the village head that they have been informed about the study and grant their formal permission.

o Village Map: You are required to draw a rough map of the village before the start of fieldwork to understand the village’s layout and the critical physical structures —like the hospital, school, panchayat office, temple, or any other place of worship. The team supervisor generally does this exercise with the help of a local person from the village, such as the sarpanch/ schoolteacher or any other elderly person. As the rural dwellings/ households in a village are not structured or follow a pattern (unlike the urban dwellings), the maps also help sample and select clusters/households in that village.

o Use of colloquial terms: Given the linguistic diversity of Indian States, specific phrases or words have colloquial interpretations. Therefore, for ease of understanding and comprehension of questions by the respondents, it is generally recommended that local phraseology is inserted into the instrument basis inputs from an informed local person such as the schoolteacher.

With the focus of multinational companies and marketers now shifting to rural consumers, rural market research in India will likely increase spending in the near future. It augurs well for market research companies to actualize this opportunity to sharpen their research methodologies with rural consumers in mind. At the same time, researchers should be mindful of some of the challenges of rural research, such as low literacy levels, low tech savviness, poor connectivity, and a heterogeneous population, while designing research methodologies for this group.

Kadence International helps leading brands make game-changing decisions. If you are looking for a research partner to help better understand your customers, we would love to help. Simply fill out our Request for a Proposal here.

World economists are starting to speculate or predict a pending recession, which often leads to a flow-on effect on company forecasts and budgets.

In economics, a recession is a contraction in an economy for two consecutive quarters when there is a decline in economic activity.

During a recession, consumers generally spend less. Recession-challenged consumers become more discerning in where they spend – looking for deals or switching brands. Some buyers even change long-held behaviours and attitudes toward consumption.

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At the same time, brands, like their consumers, seek to conserve cash and reduce spending, including their market research budgets, during economic downturns.

One of the many benefits of market research is that it helps mitigate uncertainty and can often reveal opportunities in price, competitor intelligence gathering, new markets, customer satisfaction, product development, target groups, and overall demand.

Price

In market research, understanding consumer price preferences are often revealing no matter the economic condition. Knowing what price a consumer will deter a purchase is essential during a market downturn.

The Price Sensitivity Meter or PSM is a technique in market research to determine the optimal price for goods and services. PSM asks four price-related questions. These standard questions can vary but generally take the following form:

At what price point would you consider the product to be so expensive that you would not consider buying it? (Too expensive)
At what price point would you consider the product to be priced so low that you would feel there must be a compromise in quality? (Too cheap)
At what price point would you consider the product is starting to get expensive, so that it is not out of the question, but you would have to give some thought to buying it? (Expensive/High Side)
At what price point would you consider the product to be a bargain— a great buy for the money? (Cheap/Good Value)

The image is taken from a Forbes article, titled “How To Price Your Product: A Guide To The Van Westendorp Pricing Model” by Rebecca Sadwick.

The results are then plotted, and an optimal price range is determined. Depending on the brand strategy, an additional or phase two research study can determine demand by asking:

At the <expensive price> how likely are you to purchase the product in the next six months? Scale 1 (unlikely) to 5 (very likely).
At the <cheap price> how likely are you to purchase the product in the next six months? Scale 1 (unlikely) to 5 (very likely).

In many categories, price is the most crucial determinant that affects buying decisions. Understanding an upper and lower price point is essential as it can help Product Marketing Managers determine where to price their product based on current economic conditions.

Competitor Intelligence Gathering

When consumers feel the pinch from economic pressures like inflation, high unemployment, or a recession, they start to shop more discriminately.

Understanding why a customer buys from you is important for any brand to know and understand. Having a deep understanding of why your target audience chooses a competitor brand over yours is equally as important.

Competitive Intelligence or CI research gathers information about your competitors so that brands can improve and make smarter strategic decisions.

When demand is affected by economic conditions outside of your control, having a strategic advantage over your competitors could mean the difference between product success or failure.

The goals of CI research include knowing who your direct and indirect competitors are and discovering where your competitors are doing well (and not so well). It can also gather insights into market share, brand or product recall, and price points.

Brands may have hundreds or even thousands of competitors during a burgeoning economy. When the economy shrinks, so does demand, making the market smaller. Brands that understand how to differentiate themselves from their competitors will be able to withstand economic ups and downs.

New Markets

The Global Financial Crisis (GFC) in 2007 saw many countries emerging quicker from the impact of this recession than others. As a result, some currencies bounced back faster and stronger.

One way to offset the impact of a contraction in the economy is to develop additional revenue streams and customers in new markets.

When your product or service is available in multiple markets, it can sometimes lessen risk as some countries and currencies emerge quicker or are not affected as your local market.

Knowing when and where is the first question when commissioning a new market entry study. Learn more from our Ultimate Guide to Market Entry here.

Customer Satisfaction

When money is tight, any marketer knows customers become more selective and demanding. There are many measurements available in market research to measure customer satisfaction. This article explores our top five.

Benchmarking your current customer satisfaction levels, and measuring them each year, especially during times of uncertainty, allows brands to see if sentiment is changing and address those reasons for dissatisfaction. Finding new customers always costs more than keeping existing ones, so an in-depth understanding of customer satisfaction is important regardless of economic factors.

Product Development

Even during a recession, new products have an essential place. With their undiminished appetite for goods and experiences, live-for-today customers often appreciate the novelty.

Other audience segments will embrace new products that offer clear value compared with alternatives. While new product development slows in recessions overall, new product launches during economic downturns can gain greater visibility. Procter & Gamble’s successful introduction of the Swiffer WetJet in 2001 during the Y2K recession established a new product category that eased the chore of mopping floors and weaned consumers away from cheaper alternatives.

Target Groups

Understanding different buyer personas in your target audience can help marketers use their budgets wisely. New audiences may emerge, such as Gen Z, or an existing persona that is more fickle than others during uncertain times or inflation.

When company CFOs ask their marketing and product development teams to do more with lower budgets, research can help you prioritise target audiences and allow your marketing dollars to go further and have a greater return on investment.

Demand

Lower demand is the visible result of a recession or periods of high inflation. According to the Harvard Business Review, “In frothy periods of national prosperity, marketers may forget that rising sales aren’t caused by clever advertising and appealing products alone. Purchases depend on consumers’ having disposable income, feeling confident about their future, trusting in business and the economy, and embracing lifestyles and values that encourage consumption”.

Whether changing your advertising campaign to reflect consumer sentiment or offering new and relevant product features, knowing what will sway a customer to buy is important to understand.

Market research is about making strategic decisions with confidence backed by data and insight. Whether or not a recession is in our immediate future, having a crystal clear view of the future is essential no matter the economic conditions.

Data is at the heart of all research, and marketing research is no exception. It is the eyes and ears for a brand’s marketing initiatives. The data you gather — and its quality — will make a massive difference to how successful your research is, how accurate your findings are, and the impact on your business goals and strategies.

As a result, data collection is arguably the most critical market research stage. It can make or break the rest of the process, so it’s vital to do everything you can to make this stage run smoothly and successfully.

In this article, we’ll take a deep dive into why data collection matters in marketing research, the different types of data you should focus on, and all the options available to you when it comes to collecting that data. Let’s start by defining what data collection means.

What is data collection in market research?

Data collection entails gathering all the necessary raw information for your market research. Some people also extend the definition to include analysing that data to extract valuable insights for your research objectives.

It is a detailed, planned search process for all relevant data made by a researcher for a hypothesis.

The most critical purpose of data collection in market research is to ensure that reliable data is collected for statistical analysis so brands can make decisions backed by rich data. Therefore, your data must be high-quality, relevant, and plentiful enough to draw meaningful insights.

Why data collection is so important?

Data collection is a critical step in the research process, often the primary step. You can analyse and store essential information about your existing and potential customers when you collect data. This process saves your organisation money and resources, as you can make data-driven decisions. Data collection also allows you to create a library or database of customers (and their information) for marketing to them in the future or retargeting them.

Three main uses of data collection in market research:

Data collection helps you make informed decisions and analyses, building complete and insightful market research reports that can drive future product launches, market-entry campaigns, marketing strategies, and more. Data collection is the foundational step for various activities that can lead to business growth.
Data collection allows you to build a database of information about your market for future use. While your primary goal might be to create a research report with a specific objective, the data can still be helpful for future activities.
Data collection allows you to target marketing and outreach more efficiently, thereby allowing your organisation to save money and do more with its resources.

The different types of data collection in marketing research

There are several different types of data to consider at this stage — let’s examine them more closely.

We can break down data into two main categories, which makes it easier to understand the types of data we want to focus on and helps us hone in on the research methods and channels that will be most useful.

Primary data

Primary data is collected directly by your researchers, specifically for your research purposes. This data is primarily collected from interviews, surveys, focus groups, and experiments. In other words, this data did not exist before your team collected it.

Secondary data

Secondary data refers to data that already existed before you started your research. Other researchers have already collected and compiled this data before. You can find this type of data in places like government reports, the analysis of other businesses, polls and surveys, and the work of NGOs. It’s typically cheaper and easier to obtain than your primary data, but it won’t be as relevant to your project.

Qualitative research

Qualitative research is usually the first step in data collection. It’s more textual than statistical and involves collecting non-numerical data like interview transcripts, video recordings, and survey responses.

Qualitative data is typically collected via first-hand observation through focus groups, interviews, and ethnography. It is a way of diving deep into ideas and concepts, allowing researchers to learn more about specific topics that may not be well understood.

Quantitative Research

Where qualitative research is relatively more text-based, quantitative research focuses on numbers and statistics. This data is expressed in charts, graphs, and tables and is typically used to test initial findings.

Methods used to collect quantitative data include more closed-ended survey questions, mobile surveys, and Likert scales. The main benefit of this type of data is that it allows researchers to make more broad generalisations and predictions, but it’s not well-suited for diving deep into particular questions.

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How data collection in marketing research works

There are many steps involved in the data collection process. Some of these steps begin even before you start collecting data.

Prior steps

There are several steps you should take before your data collection begins, such as:

・ Make sure you have all the necessary permission to collect your data. Today, data privacy laws are stronger than ever, so researchers need to take extra care to comply with regulations and have the full consent of their subjects and participants. It’s best to work with a legal compliance team to draft all the required documents, forms, and contracts to share with your research participants from the very beginning.

・ Make sure you have the support of any company decision-makers and stakeholders. It may be helpful at this stage to prepare a preliminary report informing any higher-ups of your plans, goals, sources, and any methods you plan to use.

・ Try to predict and pre-empt any possible challenges or problems, such as privacy regulations, collection methods, infrastructure, or budget. Anticipating any issues now will help you avoid costly problems and make the whole process run more smoothly.

・ Put together a team of skilled and qualified researchers and analysts. Data collection can be a difficult task, and you need to have the right experience and skillsets on your team.

Decide on your data collection methods.

The next stage is to decide which data collection methods you will use to collect data for your marketing research report. You will likely employ various methods here, as each has unique pros and cons. Here are the main methods you should consider:

・ Surveys

There are many ways to conduct surveys — in-person, online, post, email, mobile message, others. Surveys differ in content and structure — from simple Likert scales with just five possible numerical responses to more qualitative open-ended questions.

・ Focus groups

Focus groups allow you to bring multiple participants together to discuss the subject of your research and share their opinions. This format can be a great way to brainstorm ideas, and people can often bring good ideas out of each other. To get the best results, everyone should get a chance to speak, and no one person should dominate the group.

・ Interviews

One-to-one interviews are the best ways to dive deep into a person’s opinions about your brand or a specific product. However, they can be time-consuming and may require much planning.

・Observation and experimental research

This type of data collection involves observing individuals as they interact with specific products or services. It helps get around certain biases that people might have in interviews and surveys and cut right through to their true thoughts. However, it isn’t easy and requires an expert touch to get it right.

Identify and prepare for common challenges with data collection.

During the data collection process, you’re likely to encounter several challenges. The good news is that you can avoid these challenges and mitigate any impacts on your research report with proper preparation.

Here’s what to look out for:

・Bad methodology results in poor quality data

A lot can go wrong with your data collection methods — badly identified participants, poorly designed questions, and choosing the wrong methods are just a few examples. This can result in poor quality data, leading to erroneous conclusions and an unsuccessful research report. Take the time to work with experienced researchers and build the right data collection strategy for your needs.

・Logistical challenges

You will also come across many logistical challenges. For instance, you’ll need a big venue to hold everyone if you’re running a focus group. If you want to conduct a stream of interviews, you’ll need to hire a space for a particular time. You may need to arrange transport, refreshments, and a wide range of other logistical demands. If you fail to plan this properly in advance, your team could find itself in a highly stressful situation.

・Using the proper channels

The channels you use to connect with your audience are consequential — what works well for one demographic might completely fail for another. If you choose the wrong media (like Twitter to send surveys to an older demographic), you could have a poor response rate and lack usable data.

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How to collect data effectively

Get to know your audience.

You will need to have an intimate and deep understanding of your audience and the people you collect data from. This will ensure you target the right people, ask the appropriate questions, choose the correct methods and channels, and analyse the data in the proper contexts.

There are many ways to get to know your audience better in advance of data collection:

・ Use social media to spend time in the same spaces and groups as your audience members, chat with them, and find out who they are and what makes them tick.

・ Work with your sales and marketing teams — it’s their job to understand your audience, and they’ll have access to valuable insights.

・ Look at who is using your competitors’ brands and products.

Once you understand whom you target, it often helps create detailed user personas, outlining details about your typical audience members like their age groups, income brackets, and education levels. You can then use this information to tailor your data collection strategy to be relevant and valuable.

Prepare for the analysis of your data.

Collecting data is one thing, but you should always have an eye on the analysis of that data. This is where you extract insights and draw tangible value from the data — allowing you to make informed business decisions and create a valuable and applicable market research report.

When planning your collection methods and recording the results, always remember that someone will be analysing this data. Be organised, clear, and detailed, and work with your analysts to ensure they are aligned with your approach.

Use a wide range of methods and channels.

The best data collection relies on various tools and channels instead of focusing on just one or two. By combining a number of the approaches mentioned in this article, you will connect with a broader part of your market, gaining a better understanding of how different demographics feel and leading to a more valuable and insightful analysis.

For example, if you focus solely on digital channels like social media and online surveys, your responses may skew heavily towards younger people. Some in-person interviews, focus groups, and postal surveys help target a broader range of age groups and accurately reflect your market and their views.

Data collection is a critical part of market research. It serves many important purposes, and it is essential to get it right to create effective research reports and complete a vast range of different business objectives.

At Kadence, we help companies worldwide fine-tune their data collection, laying the foundations for informed and effective market research.

Data collection comes with a host of unique challenges, and one of the most significant considerations for researchers is the topic of ethics in market research. It is essential to think about the ethical implications of your market research — are you collecting data in the right way without infringing on other people’s right to privacy, security, and the control of their data?

Before you start your data collection work, you need to ensure everyone on the team is aligned and understands their ethical responsibilities. Failing to do this could result in legal woes, a damaged company reputation, and other serious problems.

This article will show you why ethics are so important in data collection, what you need to be aware of, and how to ensure your data collection always falls on the right side of what’s considered ethical.

What are ethics in data collection?

What exactly do we mean when we talk about ethical data collection? Let’s delve into the definition to clear any misconceptions and ensure the rest of the article makes sense.

Data collection ethics is all about the right and wrong in collecting, analysing, processing, and sharing data.

This article will focus on data collection for market research purposes. The data we’re talking about here mainly refers to the personal data of our research participants.

Ethics has been an essential consideration for as long as we’ve been collecting data. By understanding it, you can ensure that the data you collect and the research you produce is ethically sound, respects the rights of your subjects, and avoids landing you in legal trouble.

Why are ethical considerations so important for data collection?

There are several key guidelines market researchers have to follow so they can adhere to ethical norms when it comes to data collection, such as:

・If you prioritise ethics, it usually results in better research.

When you care about the truth, accuracy, and minimising errors, your findings will be more reliable and lead to more valuable conclusions, benefiting your business.

・If you take ethics seriously, it shows that your brand is trustworthy and has integrity.

Conversely, suppose you’re violating ethical norms with your research; this will reflect very poorly on your reputation and (among other things) make it tough to find future participants for market research.

・You want to stay on the right side of the law.

Today there are more data privacy regulations than ever before, like Europe’s GDPR and California’s CCPA. Unethical data collection can lead to legal trouble and harsh financial penalties.

Guidelines: How to ensure your data collection is ethical.

Follow the guidelines detailed below to ensure your data collection is ethical.

Always obtain the proper consent.

When you collect data for market research, you’re using the personal data of your participants. When someone answers survey questions, takes part in an interview or focus group, or participates in an experiment, the data they share with you is protected by law in many jurisdictions.

From an ethical standpoint, an individual’s data is their personal property. As a result, you have to ensure you have the right to collect and use that data. Make sure to draft a consent agreement that informs your participants about your research and clearly outlines how you intend to use their data. This refers to asking for informed consent — in other words, your participants should know what they’re consenting to instead of being asked to give a blanket agreement.

In short, always get explicit consent from your research subjects before you collect or use any of their data, and always make sure they are given all the facts upfront about how you will use it. This is one area to work with an experienced legal team.

Always be clear about privacy and confidentiality.

You should be clear from the beginning about how private and confidential your participant’s data will be. For example, when publishing a market research report, will you use the names of your subjects or provide any information that could be linked back to their identity? If so, it’s essential to let them know before you collect any data.

You also need to consider technical capabilities in this area. Are your systems secure enough, or are they vulnerable to hacks and data breaches? You can still be legally punished if you lose sensitive user data due to a cyberattack in many cases.

Personally identifiable information (PII) covers many different data types, like a person’s full name, address, credit card information, or identification number.

Avoid bias.

As an experienced researcher will tell you — it’s all too easy to rig research in your favour. Wording specific questions in a certain way, focusing on some areas over others, guiding your subject in a particular direction with verbal nudges and body language — all these things can impact the result of your research.

This isn’t just unethical; it also leads to less accurate data. Pushing your research subjects towards specific answers might fulfill short-term goals, but in the long-term, it leads to a poorer understanding of your market and a shaky foundation for future research. Ensure all your moderators and researchers are aware of this and trained to avoid even subconsciously leading people in a specific direction.

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Nine ways to reduce bias in your market research

1. Minimise confirmation bias.

It’s common for teams to embark on a research project with a clear idea of what they want to discover. Maybe you want to know that all your participants love your planned products, your latest marketing campaign is destined for success, or a specific demographic is a big fan of your brand.

This can lead to confirmation bias, where researchers hone in on answers they like and gloss over ones that don’t support their favourite hypothesis, leading to skewed results that sound encouraging at first but ultimately don’t benefit the company. Be aware that your expected or desired outcome may not happen, and train your research teams to be level-headed and impartial.

2. Be aware of question order bias.

Question order bias is when the order of your questions can influence participants to give a specific answer or be more favourable to a particular idea. For example, if you ask the following questions:

What do you like about the new iPhone?
Can you give an example of a great tech company?

Here, the participant is already thinking about iPhones and Apple after the first question, and this could lead them to give a similar answer to question two, even if they might have said something else had the order of questions been different. Be aware of the order of your questions, and always try to word them as neutrally as possible.

3. Be transparent about your data collection methods.

When you publish your research, you should make your methodology available to anyone who wants to read it. Be clear about what data collection methods and sources you used, whom you spoke to (being careful to avoid sharing personally identifiable information), your goals, the sample size, how you selected participants, and more. This helps people check your findings’ accuracy and shows that you’re credible and professional.

If there are any limitations or anything you’re uncertain about, disclose this. Don’t state something as a clear fact when it isn’t. Certain parts of your findings might need future research to confirm them, and you should clearly state this.

4. Maintain integrity

It may seem obvious, but it’s paramount to collect data with honest intentions and hold yourself to these standards. If you collect data for reasons that might negatively impact others, this is unethical, even if your collection methods and other factors are legitimate.

Make sure the questions you ask are relevant to your research goals. Asking questions — particularly personal ones — about your subjects that don’t inform your research is unethical.

5. Don’t cause harm to your participants.

You should always identify and avoid anything in your research process that could cause harm to your subjects. This could be physical harm — for example, asking participants to sample food to which they may be allergic — or emotional trauma, like asking people to revisit uncomfortable memories or placing them in situations where they might not feel at ease.

Anything that could harm your participants in any way is unethical. Make sure they understand the process from the beginning, regularly check in on them, and be sure to disclose anything that could potentially cause problems.

6. Don’t waste people’s time.

Your participants are busy people. They don’t have vast amounts of time to dedicate to your research, and they’re helping you out by agreeing to take part. Be respectful of your participants’ time and don’t keep them waiting longer than necessary. Aim to keep your research process tightly organised and always inform people about delays and other time constraints as soon as possible.

7. Be aware of unexpected outcomes.

Even the most meticulously conducted research can sometimes have unexpected consequences. It can be deemed unlawful if individuals suffer harm due to your study.

As a result, you need to take extra care to anticipate and prevent any unexpected adverse outcomes from your research. You won’t know for sure until the study is published, but you can minimise the chances of unintended consequences by being cautious and diligent.

8. Correct errors.

It’s normal for research to contain one or two errors. In itself, that’s not unethical, nor does it necessarily mean your research isn’t valuable. However, it is imperative to correct the mistakes as quickly as possible and edit your research report to make this clear.

If you don’t correct errors when you become aware of them, this is unethical as you’re knowingly publishing misleading information.

9. Work with an experienced research team.

The best way to ensure your data collection is ethical is to work with a team of experts. Research professionals understand the ins and outs of data ethics, and they know what to do and what to avoid. They also have an in-depth and current understanding of the legal aspects of market research. At Kadence, we have years of experience helping companies worldwide conduct market research, and ethics is always a priority. Get in touch with us to find out more.

Every market research report begins with data collection, and this stage of the process influences how everything else goes. If you collect high-quality data from relevant sources and use the proper channels, you’ll boost your chances of creating a clear, accurate, and valuable report.

Data collection is at the heart of market research. If you do data collection wrong, the result could be an essentially useless market research report, wasted money, and poorly informed business decisions. Therefore, you need to use the right data collection tools.

The methods you use to gather your data in the early days of the market research will majorly impact the quality of the data and the effectiveness of your research report. This article will look at the best data collection tools available for market research and why they’re so helpful.

Five essential data collection tools for Market Research

1. Surveys

Surveys are one of the most versatile and established ways of collecting data. They come in all shapes and sizes but typically follow the same rough pattern — a series of questions aimed at gathering opinions and experiences around a specific thing like a product, marketing campaign, or brand.

One of the best things about surveys is the number of channels they can be shared through:

In-person paper surveys
E-mail
Social media
Your website
Postal
Mobile message
In-app surveys

The list is almost endless. You’ve probably encountered the series of buttons in public toilets and areas like airports asking you to rate your experience quickly — that’s a fundamental type of survey aimed more at measuring customer satisfaction than market research.

Surveys can be designed in several ways. More qualitative surveys ask open-ended questions like, “What did you like about this product?” They encourage extended, detailed answers to allow deep dives into the data.

On the quantitative side, surveys may use a Likert scale — a series of points (for example, Strongly Disagree, Disagree, Neither Agree nor Disagree, Agree, Strongly Agree). These types of surveys are much more restrictive for the respondent but allow you to gather more numerical data to prove existing hypotheses and create charts and graphs.

2. Interviews

Like surveys, interviews are another way of gaining a deep and personal insight into an individual’s experiences and opinions on a topic. Interviews are incredibly qualitative and the only reliable way of getting an individual’s uninterrupted views on a topic in real-time. Interviews allow for the most profound and unfiltered responses of all the data collection methods listed here.

There are many ways to conduct an interview. Some methods are highly structured with a clear set of questions and the interviewer firmly guiding the conversation. Others can be more informal, with the interviewee free to talk about their experience at length without much input. Interviewers need to ensure they don’t nudge the respondent towards specific answers or encourage bias.

In the past, interviews could only be conducted face-to-face, introducing challenges around finding the time, space, and staff to carry them out. Today it’s possible to conduct interviews via phone call or video chat, making it much more manageable. However, these methods risk missing out on the body language cues and subtle gestures that can spark further questions.

3. Focus Groups

Focus groups bring multiple people together to discuss a particular topic (for example, a new product) and share their experiences and thoughts.

Focus groups can be helpful for several reasons — they help you gather multiple opinions at once, promote healthy discussion, and allow you to be more economical with your time and space. The best focus groups bring together people from diverse demographics and backgrounds.

It is vital to make sure one or two more assertive people don’t dominate your focus group. To prevent this, make sure to moderate the group effectively and allow everyone to have their say. At the same time, be mindful of people adapting their opinions to fit the overall group consensus.

4. Observation

Observation is a time-tested method of data collection that, when done right, allows researchers to gather large amounts of unbiased and unfiltered feedback. It works by giving the participant a series of questions or asking them to share their thoughts on something (like a product) in real-time.

During this process, the observer does not interfere with the participant. They watch closely and note the participant’s non-verbal reactions like facial expressions and body language. The idea is that participants’ verbal responses can be influenced by bias and tailored by the person. However, nonverbal behaviour is much less easy to control and may reflect a more honest reaction.

Observation can be an advantageous way of cutting to the root of what a person believes about a product. You should attain your participant’s full consent before the process begins. You should also be careful not to draw overly firm conclusions from the interpretation of their body language — which should be viewed as a guide.

5. Secondary sources

There are several options here, and depending on your market and research purposes, there may be a great deal of data already available. In addition to the primary methods discussed above, researchers can also look at data that others have already collected. Here are some examples of secondary data for market research:

Government reports. While these are not usually specific to any business needs, they can still be beneficial. Government surveys and reports contain data about income brackets, spending behaviour, customer attitudes, and more. Combined with other data collection activities, this can help you better understand your target market, build more accurate customer profiles, and improve your marketing, among other benefits.

NGO resources. Non-governmental organisations frequently research a range of subjects. Much of the data they collect is relevant to marketers for similar reasons as government reports.

Business reports. Other companies, industry groups, and market research organisations regularly create detailed research reports that you may be able to access and use. These often don’t come cheap, but they can provide valuable insights into your target market — essentially doing a lot of your work.

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Data collection is one of the most important tasks you’ll carry out in your market research efforts. At Kadence, we help companies worldwide with every stage of the research process, including collecting and analysing precisely the correct data. Contact us to find out how we can help you do the same.

Many reputed brands have made costly and avoidable mistakes by not including diversity and inclusion in their product testing and market research. These mistakes usually lead to a backlash from customers and the media, eventually becoming a PR nightmare.

So how can companies prevent this from happening? By ensuring their products and campaigns are diverse, brands can avoid costly mistakes in the first place —and it all starts with diversity and inclusion in market research.

This is because you typically want to hear from as wide a range of people as possible. You want to cast the net wide, gathering ideas from the social, economic, ethnic, and cultural spectrum, helping you gain a rich and complete picture of your market.

However, developing a product or service used by many isn’t always easy. It begins with inclusive research and reaching out to those typically marginalised. When brands consider diversity in gender, sexual orientation, backgrounds, religions, and disabilities, they can create products that work for everyone. This allows brands to craft compelling messages that resonate with their target markets.

Many organisations find it hard to ensure their research is diverse, focusing too much on specific demographics and groups. The result is skewed research with incomplete results, leading to inaccurate conclusions and ultimately harming your growth as a company.

It is somewhat easy to conduct a quantitative research survey asking for a sample of age groups or household income. But if the data comes back skewed heavily to a particular ethnicity, sexual orientation, or gender, it will not be a true reflection of society, which leads to flawed and inaccurate research.

Just how widespread is this lack of diversity? Is it limited to a handful of companies, or is it endemic in market research? In this article, we’ll look at the issue of diversity in market research and how companies can take steps to tackle it and promote more inclusive research methods.

Why is diversity important in market research?

Diversity and inclusion are essential in market research because they allow brands to factor in everyone’s voice and opinions instead of just a homogenous sample. This helps them drive growth and increase usage within their target markets. Furthermore, consumers are very savvy and expect diversity and inclusion in brands. They expect brands to show the diversity and live it through company policy and operations.

Here’s how diversity in market research helps brands create and drive successful brands:

It allows you to gather various opinions and perspectives, leading to more valuable insights about your market, company, and products.

It helps you connect and communicate with different groups more effectively, improving your marketing and expanding your reach.

More diverse research can lead to a broader range of new products and services ideas.

It signals that your brand is interested in hearing from a diverse range of people and does not lack cultural and diversity awareness.

Is there a lack of diversity in market research?

While the market research industry has come a long way in recent years when it comes to diversity, there is still clearly substantial work to be done.

While we have seen many strides in representing diversity in advertising, it is still questionable when it comes to authenticity. Market research companies need to look inward first to be fully diverse and inclusive.

3 Ways Market Research is Falling Behind with Diversity

1. Accurate identification.

A study for the Alliance for Inclusive and Multicultural Marketing (AIMM) found that Caucasians were adequately and accurately identified 68 percent of the time in large digital datasets used for target marketing. However, that figure was only 49 percent for Hispanics, for African Americans just 28 percent, and for Asian Americans, 24 percent.

This is a failure on the part of data collection. Researchers need to be more stringent about the data collection sources, their standards for data quality, and the criteria they rely on for every demographic.

2. Market research teams are often too homogenous.

Marketing as an industry is not diverse at all. Looking at the 2020 Marketing Week’s Career and Salary Survey, we can see that 88 percent of people in the marketing industry identify as ‘Caucasian/White,’ compared to just 5 percent ‘Asian,’ 4 percent as ‘Mixed Race,’ and just 2 percent as ‘Black.’

Furthermore, a lack of diversity in senior positions is stifling business and creativity in this industry. According to the same report, of all senior roles (defined as senior managers to a partner or owner), 38.3 percent of marketers are Caucasian, and 49.5 percent are male.

This lack of diversity in market research will likely increase the dangers of underrepresenting certain cultures and ethnicities. Research participants may be less likely to share certain information with someone of a different background. Moderators, for instance, may also miss specific cultural contexts, and research questions may be inadvertently designed to confuse or exclude other ethnic groups.

Hiring more diverse teams and promoting market research as a potential career for people of all backgrounds can help companies conduct more accurate, valuable, and inclusive research that yields better insights.

3. People worry about inaccurate representation.

A U.S. 2019 report by Adobe found that 66 percent of African Americans and 53 percent of Latino and Hispanic Americans felt they were stereotyped in advertisements. In the same report, 61 percent of people said that diversity in advertising was necessary, and 38 percent said they were more likely to trust brands that do an excellent job of showing diversity in their ads.

Some companies fail to give customers what they want —in this case, accurate, authentic representation in advertising, which is ultimately a failure of market research. Companies need to spend more time researching the different demographics that make up their audience to create advertising that talks to everyone and addresses everyone’s problems, not just a select few groups.

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5 Ways Companies can Help Promote Diversity in Market Research:

While there is still more work to be done to promote diversity in market research, the good news is that companies can improve things.

1. Prioritise diversity.

A commitment to diversity and inclusivity should be a central goal for your research team. Make it clear to team members that this is something to focus on, and help people understand how to achieve more diversity and the mistakes they should be avoiding. Educate and hold regular training to cover all the critical information.

2. Work with more diverse teams.

When researching a diverse market, try to use moderators who belong to the same demographics as your participants. This can help avoid cultural misunderstandings, promote better communication, interpret responses more successfully, and make research subjects feel comfortable.

3. Leave assumptions at the door.

Do everything you can to avoid assumptions, biases, and stereotypes creeping into your research. Have multiple people from different groups look over survey questions to ensure they aren’t explicitly targeted at specific demographics or exclude others.

4. Be aware of cultural differences.

Before you begin your research, take some time to educate yourself on the different demographics you’ll have in your study. This way, you’ll be able to conduct more inclusive, helpful research that yields genuinely useful responses from a wide range of groups.

5. Make things accessible.

Work hard to ensure your locations, materials, and schedules are accessible to many people. Be aware that not everyone has a similar schedule or situation. For example, if your research takes place in an area not accessible by public transport, you’re limiting your responses to people who can afford a car and potentially excluding entire socioeconomic groups.

Read this article to dive into how companies can be more inclusive in their market research.

We have to represent the world we live in, and an increasing number of brands are getting it. 34 percent of U.K marketers say they’ve used racially diverse models. (Shutterstock)
Market research is becoming much more diverse, inclusive, and cognisant of different demographics. However, brands can always do more, and those who prioritise diversity will gain a more comprehensive understanding of their market, access more useful data insights, and connect effectively with more customers.

Working with a professional research agency is a great way to ensure your market research is as inclusive, effective, and complete as possible. At Kadence, we work with companies worldwide, helping them get the most out of their study. Contact us to learn more.

Your business likely serves customers across various demographics, income levels, and ethnic groups, and therefore, your research should reflect that. So, how do you ensure your market research is diverse and inclusive enough?

Many companies fail to achieve diversity in market research. They rely on an overly homogenous group of research participants, drawn from the same places, with roughly similar life experiences, preferences, and biases. The result is preliminary research, with relevant conclusions for only one part of your market. It fails to represent everyone as a whole.

When companies successfully bring in a diverse range of research subjects, they often fail to make the most of it. They inadvertently create a research environment that benefits particular groups over others, leading to skewed results and frustrated participants.

Therefore, brands should do everything they can to avoid these costly mistakes. They need to ensure their market research targets a wide range of people from diverse backgrounds and is modelled in a way that caters to everyone, not just a select few. This article will look closely at diversity and inclusion in market research, why it’s essential, and how to promote more of it in your organisation.

What is the difference between diversity and inclusion in market research?

Diversity focuses on demographics like age, gender, race, ethnicity, religion, and sexual orientation, to name a few, while inclusion allows diversity to thrive. While the two terms are often used interchangeably, organisations need to understand the difference.

As diversity and inclusion expert Verna Myers puts it, “Diversity is being invited to a party; inclusion is being asked to dance.”

Diversity brings people from diverse backgrounds and abilities together, and inclusion ensures you value and include everyone’s contributions in your market research.

Why is it important to have diversity and inclusion in market research?

Brands conduct market research to determine the viability of their products and services, discover their target audience, and uncover what their customers want so they can make better decisions. When you have diversity and inclusion in your market research, everyone’s voice is heard. It allows brands to effectively communicate with their target audience —no matter who they are and where they live.

It is essential to have diversity and inclusion in your market research efforts more than ever before. Consumers expect to see diversity and inclusion from brands in an authentic way. This is even more true of younger consumers. According to a Deloitte survey of 11,500 global consumers, “the youngest respondents (from 18 to 25 years old) took greater notice of inclusive advertising when making purchase decisions.”

As our world becomes flatter and more diverse, brands must reflect the diversity authentically in their messaging if they expect to connect with a broader audience.

1. The best research brings diverse perspectives together.

Diversity allows you to notice things, glean insights you might have missed with a less inclusive approach, and access richer and more valuable data. It gives you a complete and accurate understanding of your target market, helping you see the whole picture instead of a narrow and restricted view. A more comprehensive range of diverse perspectives also leads to improved research outcomes.

2. Most research is too narrow.

Around the world, 80 percent of research participants fall into the same rough category. We can define this with the acronym ‘WEIRD’ — white, educated people from industrialised, affluent, democratic societies. You can probably predict the issue with this — despite making up four-fifths of all research subjects, these people are a minority in the world — less than 15 percent.

Focusing on expanding your research to include a broader range of people will improve your results while giving you an edge over competitors who focus primarily on the same groups.

3. Diversity makes your research more credible.

People can see the methodology you used during your research, and they’re likely to question the reliability of a study that focuses too heavily on certain groups. On the other hand, if you can show that your research included a diverse range of people, your conclusions will be more accurate and trustworthy.

4. Diverse research improves communication and avoids blind spots.

Inclusive research listens to everyone and allows you to tailor your products, marketing, and business strategies to improve things for everyone, not just a select few. If you fail to take all voices into account in your research, you risk creating friction and being perceived as ignoring specific segments of your market.

5. Your customers want to see more diversity.

If your research is inclusive, this will reflect positively on your brand — everything from your marketing messaging to the products you sell. In a UK survey, 51 percent of BAME people said brands do not represent their cultures well in their marketing, and 64 percent said they would feel more favourably about a brand that makes an effort to include ethnic cultures.

In other words, taking steps to include a diversity of demographics in your research will pave the way to building a brand that makes more diverse people feel included.

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How to be inclusive and promote diversity in your market research

Inclusion requires the organisation to understand, appreciate, and embrace diversity fully. It is not just about adopting diversity but also committing to it wholeheartedly and without bias. We live in a hyper-connected world with savvy consumers who will quickly call out a brand if its business values go against its brand messaging or promise. Therefore, when conducting market research, brands need to be mindful of how they will approach the issue of diversity and inclusion at every step of the process.

Here are nine best practises to promote diversity and inclusion in your market search:

1. Build a diverse outreach network.

How do you currently get in touch with potential research participants? Many companies fall short because they rely on the same methods — the same social media pages, established networks of people, local universities, and other such channels.

The result is often a somewhat restrictive pool of people from relatively similar backgrounds and demographics. It would help if you had a more diverse strategy for finding participants for more diverse research.

It would be best to expand your network by recruiting participants from different neighbourhoods, schools, and online spaces.

2. Make sure your pool of participants reflects your audience.

Even when businesses serve a diverse pool of individuals and are aware of this, they often still erroneously focus their research on just one or two groups. Brands need to know their audience and who is in it — and based on this information, build several buyer personas to cover all the demographics in their market.

When you have a good idea of whom you’re targeting, you’ll be able to construct a much more inclusive research strategy tailored to multiple groups and gather a much richer range of information and insights.

3. Make things as easy as possible for everyone.

It’s easy to inadvertently design a research process that prioritises certain groups over others. Maybe your focus groups take place in an area only reachable by car. Perhaps you conduct questionnaires over Zoom, excluding people with poor internet access. Or perhaps you host interviews in the evening, making it impossible for people who work late shifts.

All these things can hinder the effectiveness of your research by cutting out certain groups and leading to skewed demographics that don’t accurately represent your market. Here’s what you should do instead:

Take steps to accommodate different schedules by conducting research activities at different times and in other areas.

Help your research participants attend activities. Offer to provide transport, access to any necessary technology, and anything else (within reason) that can make things easier for them.

Ensure your research facilities are accessible for disabled people.

Compensate your participants. For some people, travelling to a research event can be expensive, and they may have competing obligations. Offer to compensate them for their time, and they will be much more likely to show up.

4. Establish trust when working with vulnerable populations.

Depending on the type of research you’re carrying out, you may need to spend time working with people from vulnerable groups. This could include those with severe mental health issues, victims of serious crimes or abuse, prisoners, or older people.

Getting feedback from these groups can be extremely valuable and provide insights into how the people within them view your brand. It can allow you to develop new products and services that cater to vulnerable groups and create a more accessible and more enjoyable experience for them.

However, this kind of research can present challenges for researchers. For example, people from vulnerable groups may not feel comfortable sharing their thoughts and feelings in a research setting — especially when the questions touch on sensitive topics. Extra care should be taken to ensure your research methods do not cause any distress or discomfort to your participants. Here are some things to consider:

Ensure they give consent and be very clear about how you intend to use their data. Aim to obtain explicit, active permission, and give your participants as long as they need to understand this. Don’t rush your participants, and don’t proceed until you’re not sure they know.

Establish what to avoid ahead of time and create an environment that will be comfortable, safe, and welcoming for your participants.

Be careful not to steer your participants in one direction or another — try to make sure their responses are their own opinions.

Make an effort to predict and avoid any potential negative consequences of the research for your participants.

5. Make things as understandable as possible.

Your surveys, interviews, introductions, guidance, and any other communication should be easy to understand for people from every background. The most obvious example here is differences in language. If a large part of your market speaks a language other than English, you’ll need translators to ensure they (and you) understand everything. Here are some examples:

If you are interviewing people who speak English as a second language, make sure your materials are simple and easy to understand to minimise confusion and frustration for your subjects.

Make sure any examples and cultural references are relevant to the people you’re studying. Even when you share a common language with your participants, misunderstandings can still happen. For example, if your screener uses references specific to a certain demographic, people outside that group may struggle to relate and understand.

Make sure any visual materials are easy to see and understand for people who may be visually impaired. The same applies to audio materials.

6. Be aware of how cultural differences impact research.

Different cultural groups respond differently to research. For example, in Japan, focus group participants are typically less willing to go against the group’s consensus, making this research method tricky when weighing individual opinions.

Cultural differences can impact almost every element of your research process. For instance, a time one culture might consider ideal to attend a research event could be highly inconvenient for another.

Take some time to make yourself aware of these cultural differences and how they relate to your research. That way, you can design research methods that are more appealing and welcoming to different cultures, which yields more accurate and valuable results.

7. Work with a diverse range of moderators.

People from minority groups will often feel more comfortable sharing their thoughts and opinions with someone from similar backgrounds. On top of this, moderators from a diverse range of backgrounds may find it easier to connect with these participants and get more helpful responses.

Working with a more diverse team of researchers helps you draw on different experiences to build a more inclusive research process. When groups are too homogenous, it’s easy to fall into assumptions and miss out on certain blind spots, which results in a process that can exclude specific demographics and lead to incomplete results.

8. Don’t make assumptions.

It’s common for researchers to make unconscious assumptions when asking questions and creating hypothetical scenarios in research. For example, a survey question might assume that the participant is from a typical nuclear family, alienating people who don’t fall into that lifestyle category. Take some time to consider if your questions are relatable to a wide range of people and not just your location’s dominant culture or lifestyle.

9. Work with an experienced market research agency.

The best way to ensure diverse, inclusive research and avoid any mistakes is to work with a team of experts who have done it all before. An experienced research agency can help you take all the necessary steps to avoid excluding certain groups, ensure your research process is as diverse as possible, and help you notice any areas you may have overlooked.

At Kadence, we help companies worldwide carry out effective research that connects with a diverse range of participants. Get in touch with us to find out how we can help you do the same.

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So what is big data exactly, and how does it impact companies?

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How does big data impact business?

Big data in the Banking and Financial Services sector

Retail and eCommerce

Advantages of Big Data

What are the challenges with big data and analytics?

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What is data quality?

So how do you ensure you collect high-quality data that informs decision-making at every step of the organization?

Utilise technology

Advanced profiling

Proper Planning

Recruit the right people

Ensure complete and active participation

Screening dishonest participants

Develop a system of efficient, consistent data quality checks throughout the process

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What is data collection in market research?

Why data collection is so important?

The different types of data collection in marketing research

Primary data

Secondary data

Qualitative research

Quantitative Research

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How data collection in marketing research works

Prior steps

Decide on your data collection methods.

・ Surveys

・ Focus groups

・ Interviews

・Observation and experimental research

Identify and prepare for common challenges with data collection.

Here’s what to look out for:

・Bad methodology results in poor quality data

・Logistical challenges

・Using the proper channels

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How to collect data effectively

Get to know your audience.

There are many ways to get to know your audience better in advance of data collection:

Prepare for the analysis of your data.

Use a wide range of methods and channels.

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What are ethics in data collection?

Why are ethical considerations so important for data collection?

・If you prioritise ethics, it usually results in better research.

・If you take ethics seriously, it shows that your brand is trustworthy and has integrity.

・You want to stay on the right side of the law.

Guidelines: How to ensure your data collection is ethical.

Always obtain the proper consent.

Always be clear about privacy and confidentiality.

Avoid bias.

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Nine ways to reduce bias in your market research

1. Minimise confirmation bias.

2. Be aware of question order bias.

3. Be transparent about your data collection methods.

4. Maintain integrity

5. Don’t cause harm to your participants.

6. Don’t waste people’s time.

7. Be aware of unexpected outcomes.

8. Correct errors.

9. Work with an experienced research team.

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Five essential data collection tools for Market Research

1. Surveys

2. Interviews

3. Focus Groups

4. Observation

5. Secondary sources

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