The Impact of Big Data on Nielsen’s Market Research Strategies
Nielsen has been a leader in market research for decades, providing companies with insights into consumer behavior and preferences. However, with the advent of big data, the way Nielsen approaches market research has undergone significant changes.
Introduction
Before we delve into the impact of big data on Nielsen’s market research strategies, let’s first understand what big data is. Big data refers to the vast amounts of structured and unstructured data that are generated by businesses and consumers daily. This data is often too complex and large to be analyzed using traditional methods, which is where big data analytics comes into play.
In the context of market research, big data analytics allows companies to analyze a range of data sources, including social media, web browsing behavior, and transactional data. This enables companies to understand their customers on a deeper level, identifying patterns and trends that go beyond traditional demographic information.
The Evolution of Nielsen’s Market Research Strategies
Nielsen recognized the importance of big data early on and began incorporating it into its market research strategies. This involved the acquisition of big data analytics companies, such as eXelate and Gracenote, which provided Nielsen with access to a range of new data sources.
One of the biggest changes that Nielsen has made is the move away from traditional surveys towards more digital methods of data collection. For example, Nielsen now uses digital tracking to gather information on consumer behavior across a range of devices, including smartphones and tablets, as well as traditional devices such as TV sets and PCs.
This shift towards digital data has enabled Nielsen to provide more accurate and up-to-date insights into consumer behavior. For example, Nielsen can now track what individuals are purchasing in real-time, rather than relying on self-reported data collected through surveys.
The use of big data has also enabled Nielsen to move beyond traditional demographic segmentation. Instead, Nielsen is now able to identify more nuanced segments based on behavior and interests. This has enabled companies to target their marketing efforts more effectively, resulting in improved ROI.
Case Study: Coca-Cola
One example of a company that has benefited from Nielsen’s use of big data is Coca-Cola. Using Nielsen’s data, Coca-Cola was able to identify a previously untapped market segment of young women who were interested in healthy living.
Using this information, Coca-Cola launched a campaign targeting this segment, which resulted in a significant increase in sales.
This illustrates how the use of big data has enabled Nielsen to provide companies with more actionable insights, resulting in improved business outcomes.
Conclusion
In conclusion, the impact of big data on Nielsen’s market research strategies has been significant. Through the acquisition of big data analytics companies and the move towards digital data collection, Nielsen has been able to provide more accurate and actionable insights into consumer behavior and preferences.
This has enabled companies to target their marketing efforts more effectively, resulting in improved ROI. As big data continues to evolve, it’s likely that we will see even more changes in the way Nielsen approaches market research, further improving the insights it is able to provide.
