Date Posted: 11/14/22
NCP In The News: How NCP is Reinventing Customer Analytics with RapidMiner
(Originally posted by RapidMiner)
Reducing Churn and Re-Engaging Customers with Data Science: An Interview With Thomas Schleicher, Ph.D., VP of Measurement & Data Science at National Consumer Panel
To say that the COVID-19 pandemic changed consumer shopping behaviors would be an understatement. The way people shop, where they shop, and how often they shop shifted radically from pre-pandemic to the early days of pandemic-imposed restrictions. Today, ongoing supply chain disruption, labor market shortages, and extreme inflation continue to impact consumer behavior.
Imagine the disruption this created for companies who rely on high quality market research. National Consumer Panel (NCP), a joint venture between NielsenIQ and IRI, felt the brunt of the pressure to continue delivering insights to their clients. NCP collects and processes a wealth of data from their select panel of shoppers, a representative “mini-USA,” to measure consumer attitudes and behavior. The data NCP generates is essential for their manufacturing and retail clients—it can be used to analyze market penetration, customer loyalty, and product propensity.
NCP’s #1 job is to understand how people shop. At the height of the pandemic, many dedicated shoppers reached out directly to NCP for guidance—how were they supposed to continue providing information about their weekly grocery runs when their entire lives were on hold?
Disrupted Consumers + Disparate Data = No Easy Solution
When Thomas Schleicher joined NCP in 2011 as the Senior Director of the Measurement and Data Science team, his background in experimental social psychology and marketing analytics afforded him unique insight into the “why” behind consumer behavior.
In 2019, Thomas was promoted to VP of Measurement and Data Science, taking on more responsibilities related to data science leadership. Shortly after the pandemic hit, his role became more pivotal. How could he and his team leverage data to engage and retain panelists amidst a wide range of pandemic-induced economic pressures?
Thomas had some tools to get him started. NCP, like many other companies, has a wealth of rich, first-hand data. The issue? It comes from multiple, disparate sources. The data is organized by function, but, as business priorities evolve to keep up with (and ideally ahead of) marketplace developments, its quantity and complexity only grows.
What should he do with all this data? How could he leverage techniques like data mining and data science to discern patterns and optimize panelist targeting?