Customer
Experiences
Consumer opinion plays a decisive role in the assessment of products and services.
Comprehensive surveys in the form of online panel surveys are carried out regularly by the German Institute for Product and Market Evaluation. The aim is to collect systematic feedback from various areas of products and services. The data obtained in this way provides valuable insights into consumer preferences and perceptions, makes it easier to identify trends in the market and helps to improve the focus on customer needs.
The online panel survey is a quantitative research method used to systematically collect data on consumer attitudes, opinions and behaviors. This process uses the internet to gain access to a pre-recruited group of participants who are representative of a larger target group. The method makes it possible to collect a large amount of data quickly. In the following, the online panel survey process is described in detail and in its methodological steps.
The methodology
Concept and design of the study
The first step is to precisely define the research objectives and develop an appropriate study design. The variables and hypotheses to be investigated are determined and the target group of the study is defined. On this basis, a questionnaire is developed that is tailored to the specific information needs of the study.
Selection and recruitment of the panel
The selection of panel participants is crucial for the representativeness of the results. As a rule, recruitment is carried out via online platforms that offer access to a broad base of potential participants. Various strategies are used to ensure a demographically and geographically representative sample. These include random selection procedures, quota selection or targeting specific target groups.
Conducting the survey
After recruitment, participants receive an access link to the online questionnaire. AI-supported software solutions allow the questionnaire to be designed flexibly, including different question types (e.g. multiple choice, Likert scales, open questions) and multimedia content.
Data analysis
After checking for completeness and consistency, the statistical analysis is carried out, which can include different methods depending on the research question, from descriptive statistics to complex multivariate analyses. The results are interpreted in the context of the original research objectives and taking into account possible limitations of the study.
Subject pool
As part of the development of a representative and realistic pool of respondents for various panel surveys, a methodologically sound concept is pursued in order to reflect the diversity and representativeness of the target population. The construction of this pool is based on a careful analysis of demographic, socio-economic and psychographic characteristics found in society. Our subject pool provides robust and reliable data, both quantitatively and qualitatively, for a wide range of research questions.
Structure of the subject pool
The subject pool comprises 9,000 individuals covering a wide range of demographic categories to represent the diversity of the population in Germany.
Panel distribution
Depending on the study and survey objective, the survey panels are compiled from the respondent pool in order to achieve valid results and minimize wastage.
Demographic characteristics
Age distribution:
The pool reflects the age structure of the population, with an even distribution across the following age groups: 18-24 (12%), 25-34 (18%), 35-44 (17%), 45-54 (20%), 55-64 (17%), 65+ (16%).
Gender:
The aim is to achieve a balanced distribution between men (49%) and women (51%).
Geographical distribution:
Participants are recruited from all federal states. The distribution is between the new federal states (72%) and the old federal states (28%).
Educational level:
The pool reflects the educational distribution in Germany with a mix of lower secondary school qualifications (20%), intermediate secondary school qualifications (40%), A-levels (30%) and university degrees (10%).
Socio-economic characteristics
Professional status:
A mix of full-time (50%), part-time (20%), self-employed (10%), unemployed (10%), retired (10%).
Income distribution:
The income distribution in the pool reflects the social stratification, with lower (20%), middle (50%) and upper income quartiles (30%).
Psychographic characteristics
Lifestyles and values:
The pool includes a variety of lifestyles and values that are identified through specific screening questions to cover diverse consumer segments.
The percentages are based on data collected as of January 30, 2024 and may vary at the current time. We attach great importance to the protection of our respondents and their privacy in accordance with the GDPR. All information in our online surveys is treated anonymously and confidentially, used for statistical purposes only and protected by strict security measures.
Recruitment and maintenance of the pool
Recruitment is conducted through various channels, including online platforms, social media and collaborations with educational institutions to reach a broad and diverse participant base. Regular updates and maintenance measures ensure that the pool remains current and panel fatigue is avoided. This includes regular communication with participants, incentive schemes to encourage participation and quality assurance measures, such as checking the consistency of responses.
Are you interested in participating in panel surveys as a respondent? We invite you to contact us without obligation so that we can include you in our survey panels. It is important that all participants in our surveys guarantee their independence. Please note that we cannot consider every application. Inclusion in our survey panels depends on a number of factors, including demographic, socio-economic and psychographic characteristics.
AI-based opinion research
One of our innovative approaches in the area of customer experiences is AI-based opinion research. This area includes screening and analyzing online content for public perception and opinion on specific brands, products and services. We use proprietary AI algorithms to systematically screen and analyze a wide range of digital platforms, including review portals, social media and blogs. This methodology allows us to paint a comprehensive and nuanced picture of brand perception that goes far beyond traditional survey methods. Depending on the object of research, the methods are applied in parallel.
Big data for opinion research
At the heart of this research method is the collection and analysis of large amounts of data from the internet. AI models, specifically Natural Language Processing (NLP) algorithms, are used to analyze text content in terms of sentiment, topics and specific opinions. These algorithms are able to identify and classify both positive and negative statements, as well as recognize trends and patterns in public opinion.
Screening process and data analysis
The screening process begins with the systematic collection of content from pre-selected platforms. This data is then filtered to remove irrelevant information and focus on high-quality, meaningful data. A crucial step in this process is the elimination of extreme outliers that could distort the results. Extremely positive or negative statements that are not representative of the general public or could have manipulative intentions are carefully identified and excluded from the analysis. This ensures that the final results represent a realistic picture of general brand and product perception.
