At Resonate, we are committed to delivering unparalleled consumer data that empowers you to know more, act faster and drive growth. This requires consistent innovation and investment in our AI-powered data infrastructure, and we are pleased to share news of some recent advancements to our modeling & data collection practices.
First, we continue to evolve our AI and machine learning processes by incorporating new deep-learning techniques that further enhance the precision of our predictions by more effectively identifying complex relationships within large datasets such as those found in our Connected Profiles and U.S. Consumer Study.
Additionally, we are supporting advancements in our predictive models by enhancing the data collection processes for our ground truth, the Resonate U.S. Consumer Study (USCS). With a more unified collection approach, survey respondents are answering more questions across industry verticals every fielding period.
Finally, we are expanding our weighting methods to better reflect established U.S. benchmarks such as the U.S. Census Bureau's American Community Survey (ACS) and Pew Research Center's National Public Opinion Reference Survey, particularly for various multicultural groups. As part of our continuous effort to improve data quality, you may observe data that better reflects changing market dynamics.
So, what does this mean for you? As these changes are rolled out, you may notice some positive shifts in the data as a result, including:
- Audiences reflecting more precise index and composition metrics. The amount of change will depend on specific audiences or insights but should result in minimal impact (most composition change to be within 0.05 percentage points; index change within 10 points).However, it will not be unusual to see some larger shifts depending on specific audiences or sights, possibly in the 10-15 point range.
- A sharper contrast across insights that may provide more nuanced understanding of audiences.
- Audiences that better reflect composition within the Hispanic population and offer more flexible age or household income targets.