Second-party data

Second-party data: what it is, how it works and why it enriches marketers’ audience understanding

May 17, 2021  |   Martin Wallace

The new search to uncover audience insights

Marketers have long relied on first- and third-party data to support their marketing activities – and with good reason.

First-party data is rich, reliable and precise – gathered directly from loyal customers through sources like loyalty programmes, newsletter signups, purchase history and more.

Third-party data – user level data acquired across a variety of external sources – brings the opportunity to uncover more potential customers at scale, whether that is through demographic targeting, persona-based audience building or early intent signals.

But both have limitations when used in isolation – for brands seeking to branch into new markets, first-party data alone is smaller scale and less directly usable for customer acquisition.

And as third-party cookies head towards extinction, premium, authenticated third-party data with strong foundations in consent and privacy is still valuable. Marketers will still have access to their first-party data, but alone this will impair their ability to prospect new customers.

Today’s marketers need a safe place to build accurate consumer insights, learn more about their data and expand their audience.

Second-party data delivers the best of both worlds

Second-party data is essentially another brand’s first-party data. It is a means of unlocking access to high value in-market data outside a brand’s own walls. Brands can use second-party data to build a better picture of their customer base, finding out more about their own customers.

The process relies on trusted strategic partnerships: separate parties with a vested interest in reaching similar audiences collaborate with first-party data in a secure, tightly controlled environment. It means both parties can measure and analyse new data to increase their audience understanding through previously inaccessible data points.

Through these insights, marketers can scale audience activation with more optimised targeting, enabling them to retain and grow existing customers, as well as acquire new customers.

And crucially, second-party data is inherently easier to validate from a consent and permissions perspective. You know where it comes from and you can review your data partner’s privacy and consent policies.

But for as many possibilities as second-party data opens up, there are some measures required to ensure it’s used safely and effectively within these new strategic partnerships.

Using second-party data safely and effectively

The key to safe data collaboration is a secure environment or platform with pre-agreed parameters—chiefly for setting permissions on how your data is accessed and used by your partners and vice versa.

Without the clarity, quality and flexibility that data collaboration needs, neither party can work from a position of trust. 

And that’s a problem. Trust forms the basis of every successful data collaboration partnership. With platforms like LiveRamp Safe Haven, partners and retailers can align in granted permissions to build consolidated audiences agnostic of where the data was collected.

Together, this forms the foundation for a trusted and collaborative infrastructure around your data – for example some marketers may use first-party for precision, second-party for enrichment, and third-party for scale.

You can leverage your data partnership to build audience-wide insights, understand consumers or move into new markets, with partners able to set the right level of permissions in each domain they’re working with.

Collaboration done right holds partners to a standard that drives more valuable and relevant content to consenting consumers.

It’s a virtuous, mutually-beneficial circle built on trust.

Second-party data in the real world

Let’s look at how this works in practice.

Take Carwow – a car buying marketplace with a European customer base.

Through the Safe Haven platform, a car brand can collaborate with Carwow to leverage:

  • Declared data: survey results, demographics etc.
  • Inferred data: predictive models, analytics
  • Observed data: qualitative indicators, like individual car configuration and requests for quotes 

With that new data source, the car brand can glean richer customer insights that feed new activities, like:

  • More effective media budget management through smarter targeting of in-market car buyers
  • Better measurement by tying spend to actual outcomes e.g. connecting ad interaction data to a car purchase at a dealer
  • Elevated consumer privacy in a permissioned and secure environment
  • Deeper consumer insights and modelling as described below 

Carwow also provides a comprehensive view of customer behaviour across the funnel, from consideration stage to sale, across all major makes and models.

Combined with Carwow’s datasets, the car brand can interrogate its own data models and uncover new insights that inform its marketing efforts.

For example, c.50,000 individuals were flagged as in-market (actively browsing and comparing products) by one brand’s prediction models over a period of 180 days. However, Carwow flagged a total of nearly 110,000 brand-provided individuals as in-market, indicating the brand’s models are only 49% accurate at predicting in market.

Given the significant overlap and incrementality between these data sets, the brand can now use these insights to examine and improve its in-market models for retention and acquisition targeting. For example, the brand can better predict when a customer is likely to be considering a new car upgrade.

This insight also allows advertisers to target users who have shown interest in the brand’s specific makes or models, as in-market car buyers browse multiple digital channels and publishers throughout the car buying journey.

Of the c.110,000 individuals in the car brand’s base that Carwow listed as in-market, only 28% were interested in their vehicles. The brand can now seek to re-engage the remaining 72% via their owned channels to reduce customer churn.

Marketing planners and strategists can also accurately benchmark campaign effectiveness using Safe Haven’s measurement capabilities, by connecting campaign audiences with those who went on to enquire and purchase.

Data collaboration goes beyond marketing

Data gathering and data analytics are stronger and better when they support collaboration.

It widens the scope of co-marketing into a more business impactful practice, becoming more than a pure marketing programme.

The businesses that are winning today understand their customers intimately. They preempt what their existing customers want to do. And they identify people that are likely to become customers.

All without a third-party cookie in sight.

Find out more about how LiveRamp can help you bring confidence, accuracy and security to your data strategy.