Table of Contents
- What is First-Party Data
- What is the Difference Between First-, Second-, and Third-Party Data
- Examples of First-Party Data
- How is First-Party Data Collected
- How is First-Party Data Used
- Benefits of Using First-Party Data
- How to Develop a First-Party Data Strategy
- Final Thoughts
The customer data landscape and how to create personalized experiences for consumers is a major discussion in the current day and age. While customers expect content to be tailored to their preferences and needs, they’re also demanding greater transparency and control over how their personal data is used.
Historically, digital marketers have relied upon first-, second-, and third-party customer data to personalize content and anticipate customer needs, but with Google phasing out third-party cookies by 2022 and customer data regulations on the rise, what’s a marketer to do?
The answer lies in first-party data.
What is First-Party Data?
First-party data is any information collected directly from your audience or customer base. There are many advantages of using first-party data and value that this data can offer. First-party data provides the most quality insights into your audience so you can create a personalized experience for users, improve the retargeting strategy to better performance, and predict future trends.
First-party data is top quality when compared to other forms of customer data for several reasons. For starters, first-party data is data that you have collected, so it is the most reliable data available to you. First-party data is also the least expensive option because you can collect data at no cost. Lastly, privacy concerns surrounding first-party data collection are very minimal because you know where it came from, you’ll know if you have the necessary consent to use it, and you’ll essentially own it outright.
What is the Difference Between First-, Second-, and Third-Party Data?
There are three distinct types of customer data: first-, second-, and third-party data. Each relies on different methods of collection and differs in scale and accuracy.
A Definition of Second-Party Data
Second-party data is any first-party information collected by an organization outside of your own. It comes from a source other than your audience, but is still relevant and related. Examples of second-party data include:
- Activity on websites
- Mobile app usage
- Social media data
Second-party data is very similar to first-party data, but it comes from sources other than your own audience. Second-party data is usually owned by another company, such as a publisher. For example, publishers sell their first-party customer insights to advertisers as second-party data. Purchasing second-party data can be useful because you can tell the organization exactly what you want and don’t want from your data set. That way, you don’t need to spend countless hours looking for one piece of information.
A Definition of Third-Party Data
Third-party data is any information that you buy from a data aggregator or outside source that does not have a direct relationship or link to the visitor or customer. Examples of third-party data include:
- Audience behaviors
Third-party data is typically collected by independent researchers that use surveys, interviews, and feedback forms to gather information about a large sample of audience. Then, organizations can purchase this data set for their own use. Since third-party data is conducted on random sample sizes and surveys anybody willing to fill out the form, information that’s derived from the audience might not be useful for your business. Not to mention Google is also phasing out third-party cookies by 2022 for users operating Chrome. Cookies help marketers collect data to inform consumer behavior analysis, metrics processing, and ad retargeting. That being said, if your organization relies on third-party data, it’s not too late to start considering alternatives now.
Examples of First-Party Data
Now that you have an understanding of what first-party data is, here are some examples of it:
- Behavioral data: By implementing website tags, you can automatically collect data about how people interact with your website through clicks, views, purchases, and much more.
- Subscription data: You can analyze who subscribes to your content so you can have a more in-depth understanding of the types of people that are interested in your company and content.
- Social data: You can analyze the people that follow you on social media by noting how they are interacting with your posts through likes, shares, and comments. By evaluating your audience’s social profiles and leveraging built-in analytics dashboards, you can also learn about your audience’s interests, behaviors. and preferences.
- In-store purchase data: By combining in-store purchase data with your e-commerce sales data, you gain a comprehensive understanding of your customers’ purchase behaviors. This data provides insights into which products are the most popular, and which types of customers prefer which products.
- Cross-platform data: You can analyze behavioral data as users move across various platforms, such as the native app, your mobile site, and your desktop webpage. When you take into consideration the user data across multiple platforms, you start to gain a full picture of user behavior.
- Survey data: You can collect data by asking for feedback via paper survey forms, online forms, emails, and other channels. Within that survey, you can ask about your customers’ demographics, opinions on a product or service, or the kind of content they prefer.
- Customer feedback: You can collect first-party data by analyzing direct customer feedback, such as comments on your website, phone calls to customer service, and direct messages on social media. Both positive and negative feedback is valuable for knowing what’s working and what you need to improve on.
- Customer information stored in your CRM: You can also leverage customer information and demographics that are typically stored in your CRM, such as career and education details, family details, the number of purchases the customer has made, the number of times they’ve visited your website, and much more.
How is First-Party Data Collected?
There are many ways first-party data can be collected, such as:
- Website Pixels: You can collect first-party data by adding tracking pixels to your website, product, or social media profiles that gather information about consumer behaviors and actions. Whenever a visitor lands on your website, engages with your social media posts, or looks at your products and services, that data can be collected and analyzed to help inform business decisions.
- Customer Relationship Management (CRM): Customer Relationship Management (CRM) platforms gather data through direct interactions customers have with your brand and store this information for future use. Interactions may be tracked by email, over the phone, on social media, website, or webchat. Types of data that CRM collects include contact information (name, email, title), purchase history, lead source, customer interaction record, and more.
- Data Management Platform (DMP): A DMP can collect first-party data from a variety of sources and segments based on specific behaviors such as downloads, clicks, purchases, interests, or demographic information. DMP typically collects and categorizes anonymous data from multiple sources, such as cookies, IP addresses, device IDs, to help marketers target ads to the right audience segments. All of your audience data can be stored and organized in a central data management platform for a quick understanding of your customers and how to reach them effectively.
How is First-Party Data Used?
First-party data is highly valuable compared to the other forms of customer data. There are many options for how marketers want to use first-party data because of the opportunities that this particular form of data provides:
- Predict purchasing behavior: Because first-party data provides relevance and accuracy, you can predict your customers’ future purchasing behavior with confidence. For example, if you notice that a particular website visitor has been browsing web pages offering bikes and placed one in their shopping cart, you can assume that they may buy a bike in the future. Then, you can leverage first-party data to target personalized ads for the bike and related products to this visitor to encourage them to actually purchase it.
- Gain audience insights: You can analyze your data and look deeper into your customers’ profiles to truly gain a full understanding of your audience. What does he or she like and dislike? What webpages do they interact with the most? Which products do your visitors want to purchase? What product(s) or service(s)have they placed in their shopping cart?
- Personalize content and advertisements: Gathering your first-party data makes it easier for you to segment users into specific groups to target. In doing so, you can create highly personalized experiences based on your segmented audience’s interests and needs.
- Comply with data privacy regulations: General Data Protection Regulation (GDPR) is a legal framework that governs the collection and processing of personal information from individuals that live in the European Union (EU). Since you technically own first-party data and are responsible for collecting consent from all users prior to collecting the data, it is the most transparent and trusted form of customer data there is.
Benefits of Using First-Party Data
Below are the most important benefits of using first-party data:
- Collect data in compliance with regulations: You can use first-party data with minimal risks because you know the source of data and the way it was gathered. First-party data ensures your collection processes are in compliance with regulations. You can also try using third-party platforms with built-in compliance, like Emarsys, to collect customer insights.
- Data quality: First-party data is coming directly from your customers and audiences, making it as accurate and precise as possible. Compare that to third-party data which is collected from multiple platforms and combined into a larger data set so marketers generally don’t know the exact sources of their data.
- Data accuracy: First-party data is typically very accurate because you gather data straight from the source. Minimizing the distance between your company and the source of the data reduces the opportunities for error or obfuscation to occur.
- Relevancy: First-party data is highly relevant to your organization because it is coming directly from your audience. As such, you gain valuable insights into exactly how your customers and prospects behave on your site, which means you are better able to determine their preferences.
- Cost-effectiveness: Collecting first-party data is very cost-effective because you already have it in your systems — you just need to put it to use. Unlike second- and third- party, you never have to pay for first-party data because you simply own it.
- Replacing Third-Party Cookies: The GDPR and CCPA are starting to prevent data collection without consent to promote equity in customer privacy, which means third-party cookies will be eliminated by 2022. Many companies have stopped incorporating third-party data into their digital marketing strategies and leveraging third-party cookies for tracking and purposes of customer identification. So what does that look like for marketers? They will have to adapt and learn to leverage first-party data instead.
How to Develop a First-Party Data Strategy
Developing an effective first-party data strategy may seem daunting at first, but it doesn’t need to be overly complicated to yield a high return on investment. Here is the five-step process to developing your first-party data strategy:
1. Inventory Existing Customer Data
The first step in developing your first-party data strategy is to create an inventory of potential data points across different platforms. You can also consider leveraging data management platforms (DMPs) to help gather and organize all of your different data sources . Combining customer data points enables you to have a holistic view of your customer data and a better understanding of your audience.
2. Determine Your Data Needs
As you are creating an inventory of your possible data points, you most likely will discover that there is far more data that exists within the system than you initially thought. Before you go and start collecting additional data, you must take a step back and analyze what available data points you actually need to inform your strategy. Data is used to provide valuable audience insights and enable you to create more effective personalization and marketing campaigns. As such, you should spend some time mapping the customer journey and figuring out what data is needed to enhance each step within the journey. This will help you determine your data needs in a more focused manner.
3. Gather and Collect Data
After you know the data points you have and need, it is time to start pulling all the data together. To truly deliver personalized experiences to your customers, you would need to consider collecting user registration data. If you don’t have any user registration data, you’ll need to consider some creative methods for asking users to register to the website. Here’s an example that involves an e-commerce company.
Kate Spade collects first-party data by offering great discounts and free shipping when visitors provide an email address and zip code. Visitors also have an option to proceed without registering by clicking: “No thanks, I don’t want 10% off.”
The next step is to collect additional data about the user, such as demographics, career industry, and any other attributes you’d like to know. However, asking your users to provide all of this information up-front will kill the user registration process altogether. As such, you should slowly integrate additional data collection as they use the site. As users engage more with your content and offers, you can slowly start to collect additional information via registrations, coupon offers, surveys, and more .
You can also collect behavioral data and click attributes via event-based tracking. Behavioral data is raw event data that’s generated when visitors click and navigate a site or a mobile app. You can leverage behavioral data to identify common consumer behaviors, to understand users’ likes and dislikes, and to make specific products or services more appealing.
It’s important to note that your data points also require extensive metadata that is often processed by internal or external team members. That being said, it is important to standardize and coordinate data collection and governance in your metadata. Lack of coordination and standardization will result in your first-party data being at risk for inaccuracy and inability to be used effectively.
4. Leverage a Customer Engagement Platform or CRM
Before you can build a resilient first-party data strategy, your customer data needs to be collected, organized, unified. Marketers need an open data framework where information can flow between multiple systems such as from their website to their CRM system to customer support portals. A Customer Engagement Platform (CEP) can create comprehensive customer profiles that draw from multiple data sources and systems. In doing so, marketers can have a holistic understanding of where, when, and how customers like to interact.
You can leverage CEPs to help pull essential customer data from disparate sources so you can draw more precise conclusions about customers’ preferences, effectively segment and target different audiences, and achieve scalable 1:1 personalization.
5. Test, Measure, and Refine
Before you start running your campaigns, make sure to test your audiences and messaging to ensure that your campaigns will be successful. Testing will help you make needed adjustments before launching the full campaign. Over time, you will discover how specific audiences react to different campaigns and offers which will help you make more informed business decisions that drive results.
As marketers, we need to understand several things about our retail and e-commerce customers to deliver the right content, in the right place, and at the right time. To best understand customers and meet their needs, brands need insight into who is buying, how much they’re buying, and when and where they’re buying it. In the wake of recent data collection news, first-party data prevails as the data collection method of choice, and for that reason, it is imperative that consumer brands understand how to create and execute a first-party data strategy. Use the tips and tools above to develop a successful first-party data strategy and delight your customers, both online and in-store.