Introduction

Global B2B surveys can produce four different types of data for your business: demographics, behavioral, customer experiences and insights.

The first type of data is demographics, which is the quantitative data describing your sample population

Demographic data describes the characteristics of your survey participants. For example, if you wanted to know the average age of your sample population, or how many members of your sample population are male versus female, demographics are what you would use to derive these answers.

Demographics can be used to compare your sample population with others in order to determine where they differ (e.g., comparing respondents’ ages against the general population's average age). They can also be used as covariates when analyzing other types of information gathered during survey administration (i.e., when analyzing responses on open-ended questions).

The second type of data is behavioral, which describes the activities and interests of your survey participants

Behavioral data is the second type of data that can be collected using Global B2B surveys. Behavioral data provides a qualitative description of your survey participants and their behaviors. For example, behavioral data may tell you that 60% of your respondents use your products or services to help them manage their inventory levels, or that 85% of your B2B survey respondents feel confident in the level of customer service they receive from you.

Behavioral data can be used to understand how customers use your products or services, and why they do so, or to understand how satisfied (or dissatisfied) they are with those services. This information is valuable because it offers insights into what features should be emphasized in future marketing efforts, as well as how best to communicate those features effectively through advertising channels like email campaigns and social media posts.

Another type of data that can be collected from Global B2B surveys is the participants' customer experiences

Customer experience data can be collected in a variety of ways. The most common way is through qualitative customer experience surveys, which are typically open-ended questions that allow respondents to provide detailed comments about their experiences with your product or service. Another way is through quantitative rating scales, where respondents rate your product on a scale from 1 to 5 or 1 to 10. This allows you to collect more objective information as compared with qualitative responses.

Customer experience data sets can be used for multiple purposes. For example, You can use it to analyze customer satisfaction levels across different demographics (e.g., gender, location). If you see that there are significant differences in satisfaction levels based on these demographics, this may indicate something about the quality of your products and services in different markets. You can also use these types of data sets as input for predictive models if you want them integrated into a machine-learning workflow.

Global B2B surveys can show the participants' insights about what makes your products successful in the marketplace

The last type of data that a Global B2B survey can collect is the participants' insights about what makes your products or services successful in the marketplace. Why is this important? It's important because your customers have a unique perspective on why they choose to buy from you and how they think you can improve.

What do you do with such valuable information? You use it to create true innovation and personalization at scale by understanding what customers are saying about your products and services.

Survey research methodologies can produce several different types of data for your business

There are several different types of data that Global B2B surveys can produce. Each type of data will be used for a different purpose and to help you improve your business in different ways.

  • Descriptive analysis: This type of analysis is used to describe what is happening with your business, such as how many customers you have or what products they are buying from you. This can be useful when trying to understand why customers choose one product over another, or when looking at trends within the industry as a whole.

  • Inferential analysis: Inferential analysis looks at how much people like something based on their responses to questions about it (for example, if someone says they like their phone more than others do). It uses statistics to determine whether there is enough evidence here to say that this person's answer provides insight into other people's preferences too (e.g., "I like my phone more than others do"). If there are enough people who answered similarly then inferential analysis can help predict future outcomes such as sales figures or customer satisfaction ratings even though no one has used those products yet!

Conclusion

The best way to determine what type of data you need is to conduct a detailed needs analysis. This will help you identify the types of questions that will be most relevant for your business and its customers. Thus, you can include relevant information in your B2B survey for due diligence.  

For example, if you're looking for ways to improve customer service then it might make sense to ask how satisfied people are with various aspects like responsiveness or quality of service. On the other hand, if you want more information about why customers choose one product over another then asking them which features were most important when making their decision could help uncover some interesting insights. 

It's also possible that none of these approaches would work out well so it's good practice not only considering what types of questions might be included in any given study but whether any alternative methods should be considered as well!