Many marketers 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 than 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.
Third-party data is information collected by companies that don’t have a direct relationship with consumers.
To put that into context: virtually every brand gathers data directly from its audience – names, email addresses, order history, etc. This information is called first-party data. 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, directly from the consumer.
Here are basic examples in action:
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 marketers reach the right people at the right time, such as advanced audience segmentation, location visitation attribution, and real-time targeting.
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.
Third-party data has benefits and applications across many industries and fields. The application of big data in internet marketing can help you:
Example industries that can leverage third-party data include:
Retail and eCommerce:
Quick Service Dining and Restaurants:
Telco and Consumer Technology:
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). To put it in plain language, data sets with more significant breadth and depth better train machine learning algorithms. Without the right data input, there can be no AI.
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 in support of the end goal, then third-party data is the key to achieving better AI outcomes.
Read more about the technical underpinnings of this process in the following whitepapers:
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 anonymized data. Second, these regulations don’t change the fact that third-party data is a mainstay of marketing strategy and will become increasingly essential in maintaining a competitive advantage. As you make a plan for data and the next decade, it’s essential to work with a trusted data partner to stay compliant with existing and emerging laws.Learn more:
Third-party data vendors collect anonymous consumer data in several formats and from multiple platforms. Every data source feeds into larger repositories that DMP partners can filter to provide organizations with what they need to best inform their marketing strategies.
Marketers and other non-technical data buyers typically purchase third-party data in the form of audience segments ready for immediate deployment in digital and social channels including Facebook, Twitter, and Instagram.
Data scientists and other buyers pursuing data for predictive modeling or machine learning may purchase data sets looking for specific features and attributes. The details of the data and features are documented for a data set through a data schema. The exact data schemas available vary by provider.
Mobilewalla offers four different data sets available in various forms to easily integrate with existing internal systems via system-to-system transfers. Contact us for details.
The ecosystem is crowded with third-party data providers. When evaluating a potential consumer intelligence provider, ask critical questions about the company, their methodologies, compliance, and deliverables, such as:
For more comprehensive guidance on selecting a data partner, download our Data Ecosystem Guide as a go-to reference tool.
Mobilewalla is a leading consumer intelligence provider, boasting 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.
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