5 Steps-Data_Is_Legit

Is Your Data Legit? Here Are 5 Ways To Know For Sure

Third-party data is kind of like a C-list celebrity; it doesn’t have the best reputation. Publishers still need it to bulk up audience targeting efforts or for demo requirements. So that means data vendors must be able to show transparency and accuracy of its third-party data.

Here are five questions to address with your data vendors:

1. Data Collection: Ask them how the data was collected and if it contains observed behaviors, as well as online and offline data. Also, there are a lot of audiences based on fake online profiles. It’s important to know whether the data can be tied back to real people.

2. Data Freshness: Ask your vendor to confirm if the data was recently collected. Data from a year ago or even six months ago won’t be as accurate as more recently collected data. The best data is not more than 30 days old.

3. Data Type: Make sure you know what kind of data you’re getting from your vendor. There are three different data types–declared data, inferred data and observed data. Declared data can include survey data, demographics, interests and purchase behavior and is considered more reliable because the customer shares it. Inferred data is assigned to a person based on their online activities and actions, which helps to assign a classification to a user based on what they searched for, read, watched or bought. Observed data is based on a person’s engagement with content or a product and is used as the basis for retargeting.

4. Data Verification: Verified data ensures that the third-party data you’ve purchased is authentic. Find out if your provider self-verifies their data or uses a verification service?

5. Data Intelligence: Are you getting insights that go beyond demographics, psychographics and behavioral data? Can the vendor provide rich audience insights and profiles that tell you new details about your audiences? You’ll want to understand the why that drives the what behind a person’s decision to buy or support certain brands, retailers, products or causes. This insight better enables you to meet your business goals.

How Resonate Ensures Data Quality

Resonate’s deep consumer insights are forged from two powerful types of data: consumer surveys and streams of online and offline consumer activity. Resonate runs continuous waves of long-form surveys throughout the year that yield hundreds of thousands of responses. The goal of these surveys is to get not only basic demographic variables, product and retailer preferences but also to understand why people have made those decisions and the values that guide them.

Getting bad survey responses has terrible implications for a company seeking high-quality surveys, including skewing data and throwing off compositions used in business decisions. We estimate that about $3 billion-$4 billion is wasted annually on bad data. Resonate uses a proprietary “fraud score” to throw out 10-20% of what is scoring as bad data. It’s the only way we’ve found to ensure that the insights we’re providing are the closest measure of consumers.

Resonate then turns to online activity to complete the story at scale. We analyze tens of billions of daily web events linked to the survey respondents. These events and activities are anonymous and compliant with all consumer privacy principals. Artificial intelligence and machine learning analyze survey responses and digital activity to create predictive models that help marketers understand and connect with their target audiences. Our insights are updated nightly, so we also guarantee that you’re getting the most up-to-date picture of your audiences.

Learn more about data quality for publishers and reach out to see Resonate’s data quality in action.

This article originally appeared in AdMonsters.

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