Understanding and Using First-Party Data for Your Marketing

First-party data is the term for data that you collect directly from your customers. With first-party data, there is no middleman involved – you are the ‘first party’ to come into contact with the data.

First-party data has always been a thing. Back in the days before computers, shopkeepers would manually track what customers were buying on different days of the week and use the information they gathered to optimize their stock. Then came computers, then the internet, and then customer data exploded.

Businesses could suddenly track every interaction that a customer had online. The customer data landscape became a Wild West of unethical practices, with customers’ data being bought, shared, collected, and used without their consent. 

Which brings us back to the present. Awareness around data privacy has slowly built up and, over the past few years, governments around the world have begun passing legislation to protect customers. This includes the European Union’s General Data Protection Regulation (GPDR) and California’s Consumer Privacy Act (CCPA). 

With governments cracking down on data misuse, first-party data is fast becoming the only type that matters. In fact, 81% of respondents in an Edelman survey said that being able to trust a brand to do what’s right is a major factor in their decision to buy.

Most modern marketers use a suite of tools and platforms to deliver their campaigns. This is great news when it comes to data collection – you’ll likely already have a wealth of first-party data at your fingertips. 

The types of first-party data available through these platforms include:

• • Demographic information (e.g. customer name, age, and location)
  • Firmographic information (e.g. company name, industry, and primary contact details)
  • CRM data (e.g. contact details and purchase history)
  • Social media interactions (e.g. likes, follows, and direct messages)
  • Email marketing engagement (e.g. open rates and click-through rates)
  • Website behavior (e.g. pages visited, time spent, and traffic source)

You can also collect information that customers actively and intentionally share with you. This is sometimes called ‘zero-party data’ and covers things like:

• • Surveys 
  • Reviews
  • Polls 
  • Customer service conversations 

From analyzing different types of first-party data, you can learn about your customers’ needs, interests, and preferences. This will help you to create personalized experiences that resonate at an individual level. 

Different platforms use different technology to track and gather user data. When you collect data via Google Analytics (GA), for example, you install a small piece of code on your website. This code tracks customer interactions across your site, and then bundles up the data and sends it through to the GA platform where it is presented in a digestible format. 

The Facebook pixel works in a similar way. After you add the snippet of code to your website, the pixel connects your website visitor data to your Facebook advertising account. Linking the two means that you can build lookalike audiences based on existing customer profiles, and better understand the actions people take after seeing your adverts. 

Data collection strategies involving direct interactions are generally more straightforward. For example, customers can simply hand you information in the form of survey responses or registration forms. 

When you interact with customers directly through another platform, such as your email marketing platform or webinar platform, in-built analytics tools will do the work for you. The platforms will have their own pixels and code already installed that register when an action is taken and report the information back to you.

Benefits of First-Party Data

Using first-party data offers many attractive benefits to marketers. Here are some of the reasons why businesses increasingly focus on first-party data collection:

• Accuracy and reliability – when you collect the data yourself, you know it’s reliable. It also means you can keep systems updated in real-time, which ensures accuracy in customer communications.
• Enhanced personalization – first-party data is high-quality, relevant, trackable data. It can be aggregated and updated, which makes it ideal for creating ongoing personalized marketing strategies.

• Better customer experiences – first-party data helps you understand how customers interact with your products and services. It’s not just information about them – it’s also information about your business offering and whether it’s meeting customer expectations.

Second-party data is data that’s collected by one business and used by another. There must be a direct relationship between the two businesses for it to count as second-party data. The minute you introduce a third business into the chain, it becomes – you guessed it – third-party data.

Second-party data is shared between trusted partners who have a mutually beneficial relationship. For example, when a customer fills in their details on an insurance comparison website, they consent for their data to be shared with a range of insurance providers. 

Here’s how the advantages and disadvantages of second-party data stack up against first-party data:

• • Wider audience reach (but generally less relevance)
  • High-quality data from working with a trusted partner (but the data is not your own)
  • Can be expensive (customer data is valuable – buying it from another business is therefore usually more expensive than collecting your own)

Third-Party Data

Third-party data is data that has passed through multiple entities before getting to you. It’s often aggregated from various sources, making it hard to trace where the data came from. 

The creation of third-party data often looks something like this: one company collects data from their customers. They sell it to another company, which then combines it with data they have bought from other sources. This data package then gets sold to a further company.

This chain can continue indefinitely, with multiple businesses adding to and adjusting the data as it changes hands. 

Here’s how third-party data compares to its first-party alternative:

• • Very large reach (but potentially very little relevancy)
  • No way of checking data accuracy and integrity
  • Lots of other parties, including competitors, could be using the same data

First-party data lets you retarget customers who have already interacted with your brand. Most online advertising platforms use tracking pixels to do this. When a customer visits your site, the pixel logs their IP address – this is then used to serve them ads in the future. 

Depending on the platform, the pixel might also register what the customer did when they were on your website. This information can be used to make ads more relevant and help customers pick up where they left off.

Personalization

First-party data helps you understand who your customers are, what they need, and what they’re interested in. Once you have this information, you can personalize their interactions with your brand to deliver better experiences. 

Personalized marketing campaigns normally involve segmenting customers into groups based on shared characteristics. They can then be targeted with tailored content, messages, and recommendations. 

The more first-party data that you gather, the more you will be able to refine your marketing segments, and the more successful your personalization efforts will be. 

Customer Engagement 

First-party data can also be used to improve customer engagement rates. It helps you forge stronger relationships with your customers, which makes them more likely to engage with your brand. 

By looking at different engagement metrics, behavioral insights, and customer feedback, you can identify when and why customers aren’t engaging. You’ll also be able to see when they are, which can provide valuable insights that you can use to optimize your strategy going forward.  

Predictive Analytics and Decision-Making

One of the biggest benefits of first-party data is its accuracy – which is why it plays an invaluable part in marketing decision-making. With a rich first-party dataset to draw from, there’s no need for guesswork when deciding strategy or optimization changes. 

Predictive analytics take this one step further. You can use historical data to find patterns that can inform your acquisition and retention efforts. Artificial intelligence (AI) and machine learning speed this process up by analyzing vast amounts of data to anticipate customer needs in a fraction of the time it would take a human.

While first-party data is generally of higher quality and accuracy than second or third-party types, it still needs to be properly maintained to avoid misleading insights. Customers are real people whose interests and behaviors evolve over time, so regular data cleansing to remove outdated information is a must. 

Data validation processes can also prevent inconsistencies or irrelevancies. There are plenty of automated tools available that can speedily check for duplicated entries and other errors to help avoid data contamination.

Finally, data collection methods must be reliable and unbiased to ensure data accuracy. A great example of poor data collection is when businesses hide gated content behind compulsory surveys. Doing so can encourage users to click any answer, whether relevant or not, just so that they can access the content. Just a few instances of this happening can skew overall results to the point that they’re unusable. 

Integrating Data Across Platforms

First-party data is most valuable when it’s combined from multiple sources to provide a complete picture of customer behavior. But with so many platforms to potentially pull from, that can be easier said than done. 

Developing a unified data strategy where all data is collected and recorded in one place will establish consistency between teams and departments. Data management can be made much easier with customer data platforms (CDPs), which centralize data from various sources so that it can be viewed on a per-customer basis.

APIs might be required to seamlessly transfer data between CDPs and marketing platforms. Alternatively, you can opt for tools with integration capabilities built in to save going through unnecessary additional steps.

Major browsers such as Google Chrome and Safari have announced that they’re phasing out third-party cookies in 2024, which has big implications for marketers. Third-party cookies are cookies placed on websites that aren’t the company’s own. They can track users across multiple websites and have traditionally played a key role in ad targeting.

With a cookieless future fast approaching, it’s more important than ever for marketers to learn how to collect first-party data. Leveraging this data will be critical to maintaining personalized marketing and ad retargeting efforts.

Adapting will require new strategies, including enhancing direct customer interactions so that more detailed first-party data can be gathered. Marketers will also need to stay up to date on how cookie changes will affect the data that they see in platforms like Google Analytics.

The Role of AI and Machine Learning in Data Utilization

AI and machine learning (ML) are transforming the way businesses utilize first-party data. The technology can analyze vast quantities of data from multiple sources and find complex patterns that a human might not be able to immediately spot. 

The patterns identified by AI and ML provide valuable insights into customer behavior and speed up the process of customer segmentation. They’re also game-changers when it comes to predictive analytics and delivering proactive, personalized experiences at scale.

Businesses are desperate for relevant, reliable data that they can use in decision-making at all levels. With the use of AI-powered tools like ON24’s Intelligent Engagement Platform and Salesforce’s Tableau, data-driven decision-making becomes more effective and efficient than ever.

Increased Focus on Data Privacy and Compliance

The passing of GDPR, CCPA, and other legislation are just the first steps on the road to greater data privacy for customers. As we’re already seeing with the decline of third-party cookies, regulations will continue to grow over the coming years. 

This means that businesses will need to continually update their data collection, storage, and usage practices to ensure that they remain compliant. It’s a good idea to invest in training and research now so that you can minimize the impact of future regulatory requirements. 

Strict and transparent data governance, including regular audits and clear consent mechanisms, will also help you to build trust with customers and harness the benefits of a long-lasting relationship.

Integration of Omnichannel Data

As we move towards more ethical data collection practices, omnichannel data integration will become the go-to way to build a comprehensive understanding of customer needs. When various touchpoints from across websites, mobile apps, and in-store interactions are combined, they add context to each other – offering deeper insights. 

By integrating data from multiple channels, and with the help of CDPs, businesses are able to create unified customer views. This makes delivering seamless, personalized, and consistent experiences much easier, which is another reason why the trend towards omnichannel data integration is only going to get bigger.