Data Quality

The complete guide to third-party data

For companies across all industries, the key to staying competitive in a changing marketplace is to meet consumer demands for greater personalization while boosting growth. This all can be achieved by putting the three types of marketing data to work. Using a combination of first, second and third-party data helps improve performance, reduce ineffective marketing spend, and increase long-term loyalty by improving customer experiences and creating relevant, powerful communications. In the final installment of this column, (you can find the previous two entries here and here) we will delve into how to best utilize third-party data.

What is third-party data?

Third-party data is collected by external data providers that do not have any direct relationship with consumers whose data is being collected. The data is collected from various platforms, apps and websites, then aggregated and “packaged up” in data sets. Third-party data is NOT simply lists of contacts for purchase.

Why should companies use third-party data?

Eighty-eight percent of marketers surveyed by Forbes use data obtained by third parties to enhance their understanding of their customers.1 In addition, the Interactive Advertising Bureau (IAB) and the Winterberry Group estimated that spending on third-party data increased by 17.5% in 2018 to $19.2 billion.2

Some of the benefits of third-party data include:

Depth and breadth: While other data types can be more accurate and less costly, they simply can’t match the breath and scale of third-party data. For example, Data Axle has access to more than 16 billion data points across an audience of 320 million+ consumers and 15 million+ businesses

Augment existing data: Third-party data is important for filling in the gaps in your zero-, first-, and second-party data and enables you to develop a complete view of your customers

How do brands obtain third-party data?

Third-party data can be purchased or licensed from a data provider. It can be integrated with a data management platform (DMP) or consumer data platform (CDP) which enables companies to easily append third-party data to their zero-, first-, and second-party data to build more comprehensive audience profiles and better targeting.

Third-party providers have millions of datapoints which are collected from a variety of sources from voter registration to real estate and mortgage information.

Some examples of data types available from third-party providers include:

  • Media affinity (magazine subscriptions, comic book fans)
  • Household income
  • Leisure affinities (biking, hunting, knitting, etc.)
  • Life events (graduation, new mover)
  • Buying habits

What can you do with third-party data?

Third-party data is used extensively by companies to understand their audiences and to better target prospective customers.

Achieve a complete view of your customers
While first-party data is valuable because of its precision and relevance, it often lacks scale. Leveraging third-party data for additional insights into your own audience means achieving a more complete view of your customer which enables marketers to improve communications and generate new opportunities.

Brand example:
In the competitive CPG space, identifying the correct audience is critical for driving brand engagement, awareness and most importantly, sales. Many CPG brands rely on Data Axle to provide accurate audience data, as well as our segmentation and modeling capabilities to reach ideal prospects who ultimately become future customers. The custom audiences Data Axle uses are based on models that extrapolate data on a company’s most profitable and loyal clients to target audiences that are similar in demographics and behaviors.

By introducing custom audiences into their omnichannel marketing programs (Social + Email + DM), Data Axle clients have seen up to a 40% lift in social response rates when leveraging our tailored audiences relative to standard third-party audience solutions directly from Facebook. This lift has resulted in not only an increase in online media engagement but has also served as a key driver in primary secondary objectives such as offline sales and brand awareness.

Target your competitors’ customers
Brands can combine third-party data with social media monitoring tools to find and target a competitor’s social media followers and customers and then deliver communications to steal their thunder.

Brand example:
L’Oreal created a highly targeted campaign focused on wooing their competitors’ customers on Twitter. First, the brand identified the social media followers of its biggest competitors and then cross-analyzed third-party data to match-up social media profiles with consumer data to give the brand additional intel on their competitors followers. The brand used the combined dataset to help them identify 3 key customer segments for the campaign – drugstore, indie, and luxe shoppers and then delivered unique creative and messaging to each segment using Twitter’s Tailored Audiences feature to target specific users. After launching the social media campaign, L’Oreal saw an average of 12% month-over-month increase in purchases across each customer segment and lower cost-per-click for the campaign compared to previous social media campaigns.3

Connect with new customers via personalized campaigns
Retailers can use third-party life event data to enhance their acquisition efforts; they can identify prospects at various life stages – for example, graduating high school, buying a new home, or expecting a baby – and target them with personalized content to engage and convert them.

Brand example:
Crate & Barrel used new mover data to target shoppers that recently moved into a new home. The direct mail campaign offered unique coupons for new movers. Once consumers entered their email to redeem the coupon, Crate & Barrel sent them a personalized series of emails with content geared towards new movers – which included tips for selecting furniture that fits their new space, housewarming party entertaining ideas, and decorating tips.

Advanced data modeling
Brands that do not use third-party data may be shutting themselves off from powerful benefits such as cross-device customer identity recognition and resolution, attribution models, retention models, refined lookalikes, persona and acquisition models, and much more.

Brand example:
A study by Harvard Business Review revealed that 73% of shoppers followed an omnichannel purchase journey.4 Yet a recent survey of retailers indicated only 35% use device ID data to identify consumers across devices and channels, indicating a missed opportunity for retail brands.

Williams-Sonoma uses a combination of their in-house data, second-party data, and third-party data to understand the consumer journey and connect consumer identity across channels, devices and instore purchases. For example, to understand the value in mobile marketing, the brand analyzed the full path to purchase and connected incremental conversions that resulted from activities starting on one device and converting on another.

This analysis helped the brand realize that product research on mobile devices heavily influenced sales across all devices. In response, the brand invested in more mobile-friendly, digital, and visual mediums which contributed to a 70% increase in mobile sales year over year and a 51% overall increase in e-commerce sales year over year.6

Natasia Langfelder
Content Marketing Manager

As Content Marketing Manager, Natasia is responsible for helping strategize, produce and execute Data Axle's content. With a passion for writing and an enthusiasm for data management and technology, Natasia creates content that is designed to deliver nuggets of wisdom to help brands and individuals elevate their data governance policies. A native New Yorker, when Natasia is not at work she can be found enjoying New York’s food scene, at one of NYC’s many museums, or at one of the city’s many parks with her two teacup yorkies.