The Data Daily

3 Reasons Brands Need High-Quality Third-Party Data

3 Reasons Brands Need High-Quality Third-Party Data

Enriching your existing data with third-party data gives you the breadth and depth of data to better understand consumers and fine-tune your machine learning capabilities. But the abundance of data options — and the various sources data is collected from — means that some of it is likely to be lacking in quality. Investing in data that lacks quality will cost you time and money and have a negative impact on your machine learning efforts. That’s why researching third-party data partners and ensuring they are providing high quality, privacy compliant data is a must.

Third-party data solutions increase the breadth, depth and scope of your existing data and provide rich insights into consumer behavior that aren’t available through first-party data collection alone. These insights and attributes can help organizations better understand, acquire, and retain their most valuable customers. In artificial intelligence applications, these attributes optimize and improve machine learning and predictive modeling processes to make more efficient, accurate predictions about consumer behavior.

Here, we’ll go into more detail on third-party data quality, with three reasons only high-quality data works for today’s marketers and data scientists.

The phrase “garbage in, garbage out” in reference to data may date back further than the computer itself¹, but it remains an important truism. This longtime saying especially applies to artificial intelligence and machine learning, technologies whose algorithms are only as reliable as the data being fed to them.

Companies are increasingly relying on AI and machine learning to produce effective predictive models that inform business decisions. But while the North American AI market is projected to reach nearly $100 billion in the coming years², recent studies show that up to 75% of companies have AI models they’re not using and 87% of employees say that data quality issues are the main reason why AI and machine learning couldn’t get off the ground at their companies.³

By employing a third-party data provider, companies can begin to address those data quality issues and get closer to unlocking predictive modeling’s potential.

Advanced predictive modeling might be out of reach depending on the size of a business or its data science department. But businesses shouldn’t lose sight of the role data quality can play in providing insights about high-value customers and lookalike audiences.

Let’s say a food delivery service has a trove of first-party data about its current online customers but wants a clearer picture of these customers outside of their relationship — what else do they do, what else are they interested in?

In this case, the service could look to enrich their existing data with third-party data, giving them insight into their most valuable customers and allowing them to use this insight to identify prospects that might be interested in their products. Quality data is critical to providing a 360-degree view of the customer and building a picture of the high value consumer, and bringing key customer insights and context that can be used to help identify potential high-value prospects.

As the amount of data created and consumed in the world has grown exponentially in recent years, so have concerns about consumer privacy and consent. That means that businesses need to partner with vendors who have a rigorous framework for ensuring that the data they are providing has been collected in compliance with all local, regional and international regulations. Businesses must ensure that their data, regardless of the source, is collected, stored and managed with consumer privacy and consent as a priority. Otherwise, the company is at risk of costly fines from violating Europe’s General Data Protection Regulation (GDPR) or the California Consumer Privacy Act (CCPA) or worse, losing consumer trust.

At Mobilewalla, we aggregate data from multiple sources, then apply data cleansing and fraud detection measures with a combination of deterministic, artificial intelligence, and machine learning techniques to generate highly accurate data. This means that the data we provide needs no additional quality-enhancing measures and can be used for predictive modeling and data enrichment. Mobilewalla takes consumer privacy and consent seriously and as a steward of data are compliant with all local, national and international regulations (such as CCPA and GDPR). Each Mobilewalla data partner must meet rigorous criteria and are required to represent and warrant that they have a consent and privacy framework and associated processes for active compliance. Partners must also confirm that the data they provide has been obtained lawfully and in compliance with local regulations where the data was sourced. Mobilewalla processes consumer opt-outs received through our data partners, the Digital Advertising Association, opt-out request proxy companies, as well as through direct submissions at multiple points in our processing to ensure that data is not used in compliance with regulations. Connect with our data experts to learn more about Mobilewalla’s feature-rich data enrichment offerings that harness the most comprehensive repository of consumer behavior and demographic data in the industry.

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