Blog articles by Jerome Hancock
A real-world market research case study with Big Data
The market research industry is no stranger to consumer data. However, the scale of “Big Data” generated through online behavior brings a host of challenges and opportunities for insights professionals and marketers alike. As consumers leave an endless supply of digital breadcrumbs online, how can we most effectively analyze and act on this behavior at the individual level?
Such was the challenge ArchDaily.com faced after amassing 20 terabytes of Big Data over the past three years. As the leading architectural website worldwide, interpreting this data was much more complicated than it had anticipated. With 150-200 million-page views a month, the company could see behavior volumes. However, ArchDaily.com didn’t know what was driving user behavior. It wanted to better predict architectural trends for and identify key drivers to optimize its online content strategy.
Exploring expert views on AI and the role of ‘stats’ in market research
Machine Learning (ML) is everywhere, from social media and virtual assistants to financial services and data security. For sales and marketing professionals, machine learning offers unprecedented analysis of big data. It holds the potential to decode increasingly layered buyer journeys. However, does machine learning truly have a role in market research, a field where we rely on analytical methods to understand nuanced and complex decision-making? Or, is statistical thinking still the essential analytical element behind the insights we deliver today?
Explore a driver analysis solution for analyzing stated and unstated factors
Tracking studies provide extensive information on brand perceptions over time. They play an important role in understanding what influences consumers and professionals to make decisions. However, as these groups become more empowered and have more choices to consider, your approach to brand trackers needs to evolve as well.