Nielsen Sample Frame Consultation

Young woman working in a broadcast control room on a tv station

Problem

Nielsen wanted to identify potential efficiencies across the approaches for its media measurement panels.

Nielsen was interested in an independent evaluation of their sampling methods and approaches to recommend enhancements to the designs based on NORC’s extensive experience with developing sampling frames and designs for surveys and panels. They wanted to compare alternative designs with their current and proposed approaches to ensure the best methods are applied to meet their panels’ unique objectives.

This work mattered because accurate, efficient sampling underpins the quality of data that informs media measurement and consumer insights. By identifying opportunities to reduce participant burden and costs without compromising rigor, the project supported more sustainable research practices in a rapidly evolving media landscape.

Solution

NORC reviewed Nielsen’s sampling approach for the TV and PPM panels and recommended a detailed sampling design that could serve Nielsen’s media measurement needs.

NORC’s background in Address Based Sampling (ABS), through the use and enhancement of the U.S. Postal Service’s Computerized Delivery Sequence (CDS) file, provides a unique opportunity to assess Nielsen’s current and proposed sample designs. We link commercial vendor data to address or geographic coordinates, in-house procedures for remote listing, ongoing research on sampling and surveying drop points, and statistical models to create address-level data classifiers.

NORC reviewed Nielsen’s current methodology and conducted a literature review to address Nielsen’s biggest concerns with the panels including different methods of selecting alternates for substituting nonresponding households. We recommended designs that use predictive modeling with Big Data Classifiers to oversample households of interest to create efficiencies in sampling and recruitment while helping adjust for anticipated household nonresponse during sampling.

NORC’s recommendations provided Nielsen with actionable strategies to enhance sampling efficiency while preserving data quality. By combining predictive modeling with ABS innovations, NORC demonstrated its ability to merge traditional survey science with cutting-edge techniques. These improvements can strengthen the reliability of insights gathered from Nielsen’s panels.

Result

NORC provided recommendations for two sampling designs and processes that Nielsen could use for their panels.

NORC provided a detailed report that included multiple options to meet Nielsen’s needs. We first proposed selecting both standard and alternate households from the same group of neighborhoods. This would provide the most complete and accurate results, with the fewer gaps in coverage. However, it would also be more expensive and harder to carry out, since it would require in-people visits and equipment setup.

As a more practical option, NORC recommended selecting standard households from grouped neighborhoods and alternate households from a broader nationwide list. This approach balances quality and cost while meeting each group’s unique goals.

There are several advantages to this second option:

It’s more efficient and less costly because households are grouped by location.
It can reduce bias, improve how well the sample represents the population, and reduce design effects.
It supports tools like remote listing within selected areas, making it easier to update household information and saving time and resources.

This flexible design offers a strong balance between accuracy, efficiency, and cost-effectiveness.