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First, Second and Third-Party Data: Better Together
Blog Feature

By: Laurie Hood

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March 15th, 2021

First, Second and Third-Party Data: Better Together

Editor's Note: This post has been republished from Mobilewalla's website. Mobilewalla is a Marketing AI Institute partner.

To evaluate a dataset’s inherent strengths and weaknesses, you must consider its source. Not all data is created equal, and driving real results with AI and machine learning requires the right mix of owned and licensed data.

Data scientists and marketers classify data into three different categories—first-partysecond-party, or third-party datadepending on its origin. To stay competitive with your data strategy, its crucial to understand the strengths and weaknesses of each category and how they work together.

What Is First-Party Data?

In plain language, first-party data is information you collect from your audience yourself. It might include data gathered through form submissions, a CRM system, website cookies, a customer service center, purchase history or any other engagement you control, either online or offline.

92% of leading marketers believe using first-party data to continuously build an understanding of what people want is critical to growth. Here are some of the reasons why this outlook on first-party data is nearly unanimous:

  • You own it. Any data you collect yourself represents a competitive advantage. Well-maintained first-party data is an easily accessible and cost-effective exclusive asset.
  • It offers a view into your buyers’ journey that’s insightful and can be predictive.
  • It’s relevant and accurate because it’s gathered directly from your customers.

That being said, the exclusive use of first-party data leaves a glaring hole in what you know about your customer. After all, its limited to your customers’ direct relationship with you and what youre able to record. It doesnt capture anonymous browsing behaviors, other brand preferences, or competitor affinity.

And that lack of additional insight and scale can have a negative impact on your business. Without the proper breadth and depth of data, you can’t effectively power the predictive AI and machine learning algorithms needed to stay competitive and drive insights that deliver future ROI and business growth.

What Is Second-Party Data?

Second-party data is first-party data that is collected by another organization. It can boost your overall audience insights, but only when derived from a business or brand with an audience that complements your own.

Because of its narrow scope, it shares many limitations of first-party data, including lack of scale. Second-party data also has limited availability because exchanges are usually made directly between brands. Concerns about competition, privacy, and other complications often prevent such exchanges from even happening.

What Is Third-Party Data?

Third-party data is information collected by companies that dont have a direct relationship with consumers. This information is usually licensed or purchased from a data management platform (DMP) partner or a third-party data vendor who compiles anonymous visitor information such as browsing behavior, location information, app usage or other real-world interactions.

Third-party data is aggregated from multiple sources, so it has a scale that cant be matched by any single first or second-party source. Its most effective when combined with first-party data, giving you the best of both worlds: relevant, accurate audience insights bolstered by supplemental information that creates a more complete picture of your customer and can fuel your AI/ML algorithms.

Data enrichment, the practice of merging third-party data with first-party data, offers far-reaching benefits that:

  • Deepen your understanding of audiences and segments by filling in missing behavioral and demographic insights.
  • Increase your ability to identify the characteristics of your best customers and target new customers with the same characteristics.
  • Provide a large enough scale to significantly increase the prediction quality of AI tools by up to 40%.
  • Enable the creation of highly specific audience segments with advanced targeting and re-targeting campaigns

What Should You Look For in a Third-Party Data Provider?

Not all third-party data is created equal. To maximize your investment, you need data with the following qualities:

  • Scale. The more data you capture, the deeper your insights can become. You'll want to make sure your provider has relevant, significant quantities of data at the scale you require.
  • Insights you dont already have. Most often, theres a demand for real-world intelligence to supplement information gathered online or in-house. Make sure you're getting insights that don't already exist in your organization.
  • Clean data. Unfortunately, mobile ad fraud is rampant, and it compromises the value of this data. You'll want to make sure your provider tracks fraudulent device and location signals to proactively identify anomalous ad traffic and cull bad data.
  • Privacy and security compliance. You want to work with a third-party data provider who is compliant with all local and national regulations (such as GDPR and CCPA) and who participates in industry groups focused on maintaining compliance, data privacy, and transparency. 

Those are just top-level considerations. Once you get close to working with a partner or vendor, you’ll need to evaluate their offerings on a more granular level.

About Laurie Hood

Laurie Hood is Senior Vice President, Marketing at Mobilewalla.

Disclosure: Marketing AI Institute writes about and recommends AI-powered marketing and sales technology. In all cases, content and recommendations are independent and objective. In some cases, Marketing AI Institute may have business relationships with companies mentioned, which may include financial compensation, affiliate compensation, or payment in kind for products or services. View a list of Institute partners here and MAICON sponsors here.