Resonate is a Consumer Intelligence platform that gives you the deepest, most comprehensive understanding of the U.S. consumer by combining data from our National Consumer Study with direct online behavioral observations at scale.
Using artificial intelligence and machine learning, we’re able to dynamically identify and update 14,000 attributes for over 230 million U.S. consumer profiles.
Resonate’s National Consumer Study
Our proprietary research fielded in our National Consumer Study is homegrown, continuously updated and available in the Resonate platform, as an always-on resource.
Built on scale and speed, our study is the largest of its kind in the United States. We’re continuously in field surveying 120,000 people per year, maintain survey responses on over 200,000 people over a 2 year period and release new data every 8 weeks.
That means every 8 weeks, you have an updated study to use to gain a deep understanding of the entire US consumer population.
Each wave, we ask our Core questions as well as questions that pertain to our vertical theme. Core questions consist of questions around Coronavirus, Social Justice, Values & Motivations, Demographics, Consumer Preferences, Media, Health & Pharma and Politics & Advocacy. Questions asked in a vertical theme are questions such as Restaurants, Retail, Apparel, Home & Family, Food & Non-Alcoholic Beverages, Alcohol & Tobacco & Marijuana, Automotive, Financial Services & Insurance, Technology & Telecom, Travel & Hospitality, and are typically fielded annually.
This understanding serves as the foundation for everything we do. It reveals the Human Element – the who, what, when, where and why about consumers at an individual level.
So how do we know 14,000 things about 230 million U.S. consumers? It starts with a Human.
We ask questions to discover why people do what they do. We then combine survey answers with anonymous online behavioral data to form our ground truth that power our deterministic predictive models.
Let’s go through an example.
Jenna is invited to take our survey. But before she’s allowed to start answering questions, we ensure we’ve seen enough behavioral data against her device over the last 90 days to meet our strict modeling thresholds. If we have not seen enough behavioral data against her device, she will not be allowed to take our survey.
As she takes the survey, she’ll anonymously tell us that she’s female, has a 4-year-old daughter, values spending time with family, and intends to switch banks in the next 12 months – among several other things.
From her online behavioral data, we’ll see that she’s been comparing banks that offer high interest rates, learning about starting kindergarten, and reading about the importance of eating dinner as a family – again - among several other things.
We now know from her survey answers that she’s intending to switch banks, and we know from her online behavioral data that she’s been comparing banks online. We combine these two pieces of information to form our ground truth and our deterministic predictive model for “intends to switch banks.”
Now, when we see a person’s device that hasn’t taken our survey, and we can see from our behavioral data stream that they’re comparing banks, we can confidently predict with a high degree of accuracy that they’re intending to switch banks.
Multiply that by 14,000 attributes that are updated nightly at an individual level, and that’s the depth of understanding that is available in Resonate.
The survey is administered online by our survey panel partners. The survey is not a pop up.
Our partners have a double opt-in process; once on recruitment to the panel, and again via an invitation to take the survey.
While our survey panel partners collect Personally Identifiable Information (PII) from the panelist upon registration (to deliver incentive, verify accuracy, and remove duplication), Resonate never receives this PII.
During the survey fielding process, we strictly enforce a series of demographic quotas to ensure survey panelists are representative of the adult online population.
During the survey loading process, survey respondents are rebalanced through weighting across demographic and behavioral elements to best represent the total online population.
We’re obsessed with data quality. Each and every research wave, we exhaustively examine all possible survey response patterns to identify people who may be answering inattentively. We evaluate response patterns based on answers to “actual” survey questions, and also on "attention check" questions that surreptitiously reflect carelessness.
Typically, 3% to 5% of people who complete a survey are discarded due to the poor quality of their data. By eliminating these records from our survey data, the clarity and stability of our insights, as well as the precision of our predictive models, is enhanced.