Guide to Third-Party Data Trends

sample-featured-whitepaper (1)Many businesses are well aware of the fact that “big data” is the future, using the buzzword to refer to the rapidly proliferating third-party data market. But how exactly is today’s third-party data different from the consumer data and customer lists that marketers have been using for decades?

Here, we provide a practical introduction to modern third-party data, its benefits for brands, and how to make it work for your organization.

Are you an organization looking to enrich your consumer data with alternative data? Get in touch with one of our data experts and see how Mobilewalla can help you learn more about your customers.


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What is Third-Party Data?

Third-party data is information collected by companies that don’t have a direct relationship with consumers. To put this into further context, here are three types of data collection:

First-party data collection is how every customer-facing brand gathers data from its audience. Data such as names, email addresses, order history, etc., is retrieved at their customer touchpoints. For access to more data beyond what you’ve collected in-house, you’ll need to find a second-party or third-party source. 

Second-party data refers to audience information collected by another consumer-facing company. Second-party data exchanges are typically made directly between brands, and its availability, depth, and scope share the same limitations as first-party data.

Third-party data, on the other hand, is collected by a third-party data company, is always readily available, and its breadth and scope are more expansive than what can be collected in-house.

Based on a recent Mobilewalla customer case study, here are basic examples in action:

  • First-party data: A car dealership keeps track of customer name, email address, mailing address, and shopping history so they can be kept up-to-date about offers and promotions.
  • Second-party data: The dealership could consider sharing customer lists with another company that has a similar audience. Or they may receive information on interested buyers from the automobile manufacturers they represent. However, the success of a second-party data exchange relies on whether or not an appropriate partnership can be made.
  • Third-party data: In an effort to reach more customers who have yet to visit their showroom, the car dealership reaches out to a consumer intelligence partner to identify a new (anonymous) target audience segment consisting of people who have recently visited competitor dealerships. They can then serve mobile ads to this audience over social and web channels.

Download Mobilewalla's case study to learn how they helped a luxury automotive company reach valuable prospects.

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How Has Third-Party Data Changed?

Before the internet, third-party data was relatively limited. There were a small number of companies that maintained customer lists for purchase, and they were typically applied in snail mail or telephone campaigns, which had limited utility and attribution capability.

Today, everything that’s connected to the internet generates data. There’s far more data to collect than ever before, and it will continue to proliferate. There are also more ways that marketers and data scientists can use that data. 

Much of the current third-party data activity centers around smartphones. Since most people always carry their phones, they are a key source of location data (anonymized information about where an individual travels) which is otherwise difficult, even impossible, to capture.

Location data fuels initiatives that help organizations improve their machine learning models to reach the right people at the right time, such as advanced audience segmentation, location visitation attribution, and real-time targeting.

Learn how Mobilewalla used location data to help telco companies fight churn and attract customers from the competition.

Another alluring quality of mobile data is the fact that every phone has a Mobile Advertiser ID (MAID) that effectively creates a persistent customer identity, uniting online activity (through app and web browser behavior) and offline activity (through device location). Once this data is anonymized, it provides valuable insights for brands. 

Beyond insights, this data also provides opportunities for reaching customers and potential customers through all digital advertising channels.

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What Are The Benefits of Third-Party Data?

Third-party data has benefits and applications across many industries and fields. The application of big data in internet marketing can help you:

  • Gain revenue-driving consumer insights. Your first-party data is limited to the interactions you have with your customers. When you add third-party data into the mix via data enrichment, you learn more about their habits, behaviors, and demographics which can empower more informed business decisions.
  • Identify new potential customers. Third-party data paints a more thorough picture of your highest value customers. You can then use this information to target new lookalike audiences, audience segments that share the profile of your current customer base.
  • Create innovative location-based campaigns. Remember, third-party data can go well beyond demographics or online activity. It can also include data sets based on the places people have visited. If you need more ways to target new or existing customers based on places they’ve visited (such as a retail location or event), third-party data will help you accomplish this.
  • Improve your machine learning initiatives - Incorporating third-party data and features improves the feature engineering process and leads to more accurate and predictive machine learning models.

Download our case studies of example industries that leverage our third-party data:

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What is Third-Party Data's Relationship to Artificial Intelligence?

If you don’t work in data science, you may not be aware of the critical role that third-party data plays in fueling artificial intelligence (AI). Data sets with more significant breadth and depth better train machine learning algorithms. 

Greater breadth and depth of data yields more accurate AI predictions, regardless of how sophisticated your algorithm is. If the original data set doesn’t have enough scope, depth, or features, which first-party data rarely has, in support of the end goal, then enriching it with third-party data is the key to achieving better AI outcomes. 

If you want to expand your machine learning initiatives, packaged, predictive features and attributes sourced from third-party data suppliers can jump-start your exploratory data analysis (EDA) and make feature engineering more efficient and effective.

Read more about the technical underpinnings of this process in the following whitepapers:

  • How to Increase the Value of AI with Data →
  • Third-Party Data: The Missing Ingredient in Predictive Modeling Success →
  • Why Data Enrichment and Feature Engineering Make the Difference for Predictive  Modeling Quality  →

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What Are The Privacy Concerns Surrounding Third-Party Data?

In this connected world, everything we do generates data. It follows that there are serious concerns about individual privacy when it comes to third-party data collection. Recent privacy regulations like Europe’s GDPR and California’s CCPA and headlining court cases have people wondering whether it’s safe to continue utilizing third-party data in their marketing strategies.

First, it’s important to understand that compliant data partners provide data with consumer consent, the consumer has opted-in to share their data. Second, it's essential to work with a data partner that adheres to strict data governance as to whom they partner with and follows a code of ethics when sourcing and distributing consumer data. As you make a plan for data and the next decade, it’s imperative to work with a trusted data partner to stay compliant with existing and emerging laws.

Read our blog post on maintaining privacy compliance while preventing negative impacts to your marketing strategy.

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Additional Resources


About Mobilewalla

Mobilewalla is a leading consumer intelligence provider, providing the most comprehensive consumer data repository in the digital ecosystem.

We aggregate data from multiple sources, then apply data cleansing techniques, fraud detection measures, and a combination of deterministic, artificial intelligence, and machine learning techniques.

Data analysts, researchers, and marketers leverage our highly-accurate consumer data sets for richer, more robust customer profiles including information about their competitors’ customers and consumers.

With app usage, location, and behavior-based data, enterprises can build a complete picture of current and potential customers to connect with them when and where they are ready to engage.

Connect with our consumer intelligence experts by filling out the form. Learn how enriching your data can help you better understand your highest-value customers.

Discover how you can benefit from leveraging third-party data

Download the Updated Guide to Third-Party Data Strategies