Our goal was to conduct a study on a research project using big data and to compare the outcome of the analyses with traditional survey research. Online shopper ratings and review data in social media is an exciting and on trend data source and was compared to traditional survey data. The survey data included product tests, i.e. products were placed in-home and consumers evaluated the products using a standardized questionnaire. The objective was to derive substantive insights about the core drivers for a five-star-rating of consumer reviews in online shops or platform ratings for pet care products and compare these insights with drivers of liking from traditional research on pet care products already existing in the market. We validated the hierarchy of drivers for the overall product rating by conducting a meta analyses on previous product tests and assessed the drivers of overall liking.
Our goal was to conduct a study on a research project using big data and to compare the outcome of the analyses with traditional survey research. Online shopper ratings and review data in social media is an exciting and on trend data source and was compared to traditional survey data. The survey data included product tests, i.e. products were placed in-home and consumers evaluated the products using a standardized questionnaire. The objective was to derive substantive insights about the core drivers for a five-star-rating of consumer reviews in online shops or platform ratings for pet care products and compare these insights with drivers of liking from traditional research on pet care products already existing in the market. We validated the hierarchy of drivers for the overall product rating by conducting a meta analyses on previous product tests and assessed the drivers of overall liking.
Borrowing techniques from record linkage and using the latest algorithms from machine learning to link survey data with internal data, whilst still maintaining the individual anonymity.
In a world of ever growing changeability affecting societies' decision making, the ability to monitor behavior is becoming of increasingly necessary. When we are able to collect and monitor behaviors as near as possible to the state of events, the likelihood of reflecting population's current thinking, feeling and acting, increases. There are recent experiences where last week's opinions did not reflect in this weeks' behavior. When surveying large populations with very short surveys, findings tend to reflect both the behavior of the general population and those of niches. This paper shares several experiences across different consumer and societal issues, whereby short interviews across large populations provide a wealth of strategic findings without necessarily asking many questions.
In a world of ever growing changeability affecting societies' decision making, the ability to monitor behavior is becoming of increasingly necessary. When we are able to collect and monitor behaviors as near as possible to the state of events, the likelihood of reflecting population's current thinking, feeling and acting, increases. There are recent experiences where last week's opinions did not reflect in this weeks' behavior. When surveying large populations with very short surveys, findings tend to reflect both the behavior of the general population and those of niches. This paper shares several experiences across different consumer and societal issues, whereby short interviews across large populations provide a wealth of strategic findings without necessarily asking many questions.
Borrowing techniques from record linkage and using the latest algorithms from machine learning to link survey data with internal data, whilst still maintaining the individual anonymity.
Marketing researchers have witnessed an explosion of promises that big data will dramatically improve business performance. What is the role of traditional marketing researchers in big data? This presentation provides a methodology and case study example that fuses marketing research and data science to deliver greater insights than could be achieved with either big data only or with survey data only. The case study suggests that survey research can contribute to predictive modeling through combining methods derived from, on the one hand, survey data and marketing science and, on the other hand, big data and data science. Finally, adding interactive GIS mapping and data visualisation and charting, using open-source tools, provides a visual vehicle to effectively communicate the insights.
Marketing researchers have witnessed an explosion of promises that big data will dramatically improve business performance. What is the role of traditional marketing researchers in big data? This presentation provides a methodology and case study example that fuses marketing research and data science to deliver greater insights than could be achieved with either big data only or with survey data only. The case study suggests that survey research can contribute to predictive modeling through combining methods derived from, on the one hand, survey data and marketing science and, on the other hand, big data and data science. Finally, adding interactive GIS mapping and data visualisation and charting, using open-source tools, provides a visual vehicle to effectively communicate the insights.
Big Data often has demographic and behavioral data, but little to no attitudinal information. This presentation describes the many challenges in using survey data to add attitudinal information to Big Data. We also describe our solution to align demographic and behavioural data stored in large client databases with attitudinal data collected in a survey that was used for developing consumer segments with different needs. We will show that higher predictive validity for survey data does not always mean higher predictive validity for Big Data, and that data fusion and augmentation can be a helpful solution.
This paper describes an approach that allows us to take the findings of a large scale health survey of more than 3,000 Canadians and analyse these findings so as to assess Canadians' reactions not just to specific reform measures but also to broad themes of reform, thereby providing a bigger picture of the overall direction in which health care reform might be taken over the next few years in Canada.