First-party data

What is first-party data?

First-party data (also known as “first party data”, “1st party data” or “1P data”) refers to information an organization collects directly from its audience. This includes customers, social media followers, subscribers, or site visitors – anyone who has interacted or transacted directly with the company. 

There’s no intermediary between the company collecting the data (the first party) and the people from whom it’s collected.

• See also:
  • What is second-party data? (AKA second party data, 2nd party data, or 2P data)

First-party data examples

Any audience or customer interaction across an organization’s platforms and services can generate first-party data. Typical examples can include:

• Audience actions and behaviors (actions taken on a website, app, platform, or product set).
• Basic contact data (such as name, address, phone number or email address). 
• CRM data (which can include any of the other items on this list as well as information like customer feedback or live chat transcripts). 
• Customer purchase history (what, where, when, at what price, in what style, and so on).
• Demographic information (such as age, gender, race, income, or marital status).
• Social media interactions (audience comments and conversations).
• Subscription-based interactions or product info (services or items that customers request, and often pay for, on a regular basis. Examples include access to gated online content, email newsletters, and subscription-based products.)

The advantages of using first-party data

For organizations looking to deliver outstanding personalized and privacy-conscious customer experiences, there are several practical and strategic advantages to using first-party data. The most significant of these include:

1. Strengthen brand loyalty by meeting expectations
   Personalized experiences have caused customer expectations to rise dramatically. This means brands must prioritize and sharpen their first-party data strategy to deliver the personalized experiences customers now expect. By leveraging accurate, consented first-party data, companies can continue to build brand loyalty through superior personalization.
2. First-party data is more accurate and reliable
   As first-party data is collected directly from organizations’ own customer interactions and sources it is more accurate and reliable than second-party data or third-party data. It carries a far lower risk of dilution, distortion, or outright inaccuracy than other data types.
   
3. Deeper customer insights
   First-party data enables far greater depth of customer understanding since organizations can tie data directly to customer identities and connect insights across channels to build a complete picture. With customer segmentation it also enables brands to engage more broadly with customers without diluting accuracy of understanding.
   
4. Find new high-value customers
   Analysis of first-party data can identify the characteristics common to customers with high lifetime value. AI analytics are particularly powerful in this area. These insights can then be used to shape marketing activity that will resonate with lookalike audiences, which share these same traits. 
   
5. Privacy compliance and ethics
   When it is collected with customers’ knowledge and consent, first-party data is compliant with the many privacy laws and regulations in place around the world. Using 1P data minimizes many of the personal data consent issues and privacy concerns that can be associated with acquiring third-party data.
   
6. Ownership and control
   With first-party data, full control is retained over the collection, management, analysis, enrichment, and activation of audience data.
   
7. Build trust
   With first-party data as the cornerstone of marketing strategies and campaigns, an organization effectively pursues a consent-driven marketing model that builds trust and loyalty among existing customers.
   
8. Improved products and services
   Regular analysis of first-party data such as direct customer feedback, buyer behaviors, and on-platform preferences enables brands to enhance their product or service set, and how it is pitched.

Deterministic and probabilistic first-party data

Each of the first-party data examples above can be divided into one of two important data groups. First, there’s deterministic first-party data (what is known for a fact about a customer). Then there’s probabilistic 1P data (what can be inferred about them based on their behaviors). 

Here is a little more detail about each group:

• Deterministic first-party data: This is concrete, factual information an organization knows about the customer and the customer journey. Examples include data the customer submitted, such as name or contact information, but also product purchase history, content downloads, or any direct engagement with the organization’s platforms. It’s solid audience intelligence, with zero guesswork.
  
• Probabilistic first-party data: This is predictive data based on factual audience information. Organizations draw reasoned, logical inferences about customers’ probable preferences and future behaviors by analyzing historical engagements or contextual data points such as a user’s preferred device type, page view frequency, page dwell time, or even IP address.

Why this first-party data knowledge is important for successful campaigns

Successful marketing strategies will combine the unambiguous insights of deterministic first-party data with the scalability and personalization benefits of probabilistic first-party data. 

Marketers can extend campaign reach by engaging customers about products or services they predict will be of interest based on analysis of historical behaviors – customers who like product A also tend to like product B. Similarly, combined analysis of an individual’s onsite behavior or purchase history with customer journey stage device preference (such as mobile) can create personalized experiences, with tailored recommendations, content, and format.

AI amplifies personalization potential

A brand’s ability to deliver personalization with first-party data has received a massive boost from the broad availability of generative artificial intelligence (AI). By applying machine learning (ML) and predictive analytics to customer data, company data, and industry data, organizations can provide self-optimizing customer journeys, tailored to individual preferences. 

• Find out more about predictive personalization and proactive customer service.

Activating, orchestrating, and enhancing first-party data

First-party data is the core and cornerstone of successful audience engagement. But to maximize its impact, to strengthen that customer connection, to optimize individualization means brands are making first-party data work harder for them.

DID YOU KNOW

66% of consumers are more likely to buy from a brand that treats them as an individual

– Acxiom’s first annual customer intelligence survey

First-party data needs to be elevated, activated, and enriched within a broader unified data strategy – drawing in data points from across the organization to deliver more tailored experiences across all channels. 

This can be a challenge, but the effort yields great results. Our research has shown that 66% of people are more likely to buy from a brand that treats them as an individual.

Popular first-party data services include:

• Customer data platforms (CDPs):
  CDPs enable organizations to de-silo, consolidate, and manage first-party data from across the martech stack and offline sources to orchestrate activations across all channels. The 360-degree customer view CDPs provide helps ensure personalized audience engagements.
  • Not sure how to select a CDP partner? Use our CDP buyers’ guide.
  • See how Acxiom amplified the impact of Golf Digest’s first-party data
    
• Data clean rooms (DCRs): DCRs offer a secure environment where organizations can ethically share aggregated and anonymized customer information, excluding sensitive personally identifiable information (PII), to augment customer insights for increased personalization or expand their reach.
  • Learn more about  Snowflake data clean rooms powered by Acxiom’s Real ID
    
• Third-party data enrichment: The more an organization understands its audience, the better it can serve them. This means pulling in information from a broad range of sources to fill in any blanks in first-party data. It is critical that this data is ethically sourced from trusted partners who should deliver a broad spectrum of predictive, attitudinal, behavioral, and transactional insights.
  • Discover Acxiom’s data enrichment services, offering more than 12,000 global data attributes specifically focused on providing personalized experiences – including InfoBase®, Personicx®, and Audience Propensities®.

• Enterprise identity solutions: Every step toward augmenting the impact of first-party data needs to be backed up by an identity solution. Identity resolution enables brands to check, match, distinguish, validate, and append customer engagement data points into more comprehensive, accurate records.
  
  It ensures, for example, that the ‘D Smith’ browsing  a brand’s online store is the same ‘Dana Smith’ who responded to a social media poll. Identity solutions safeguard customer engagements from inaccurate personalization.

Learn more about the award-winning Acxiom Real Identity™ or its cloud-native counterpart Real ID™ enterprise identity solutions.

First-party data privacy, security and compliance

In privacy regulation terms, first-party data offers a stronger, simpler foundation for marketing strategies. However, there are still legal frameworks and best practices to consider.

Be up front, be open, be honest

To ensure compliance with first-party data regulations, a business should prioritize transparency and obtain user consent in line with data protection laws (see sidebar for details). Communicate clearly with audiences about when their data is collected and how it will be used and, again, if possible obtain their permission for its processing. Privacy policies and notices should be transparent and straightforward. 

Avoid first-party data mission creep

Use of legitimately collected first-party data should align with stated purposes and, vitally, audience expectations. If a person signs up to receive news or offers about a specific product or service, that should be the focus of initial engagements – it’s not an opportunity to deluge the person with inventory-wide offers.

Defined structures and processes

Data privacy compliance is not a one-and-done activity. It requires constant monitoring and reviews, defined processes, and dedicated resources. In this way, customer rights inquiries (like data access or deletion requests) can be handled promptly. Structures should be in place to train the personnel involved and to review data privacy practices and compliance protocols.

Securing first-party data

First-party data is a valuable commodity, and organizations are obliged to secure it accordingly. This includes carefully implemented and strictly monitored access controls, sharing protocols, infrastructure security, and information encryption. Data should be consolidated from all customer journey touchpoints – ideally into a single platform or unified data layer.

There should be a clear rationale for the customer information that is retained – only data that is necessary should be kept. Importantly, procedures for securing first-party data should be reviewed regularly to ensure ongoing compliance with shifting regulatory requirements.

Best practices for first-party data acquisition

When it comes to first-party data acquisition best practices, privacy-conscious businesses should focus on direct collection from users. This might include methods such as web forms, user registrations, surveys, lead generation forms, email nurture campaigns, polls, or subscription sign-ups – each one of which carries explicit consent from the individual. 

Other legitimate, if less explicitly consensual, means of acquiring first-part data include collection of information post-purchase, or via website or social tags or pixels (first-party cookies effectively) monitoring on platform behaviors.

Best practices here include the collection of only useful, usable information and provision of clear notice or opt-in procedures when collecting any first-party data. Organizations should also document and review all first-party data acquisition methodologies.

First party data FAQs