First-Party Data 101

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6 minute read

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What First-Party Data is & How To Use it

Collecting, accessing, and strategically using first-party data is a crucial step to building positive relationships with customers. Why? Because first-party data essentially is your customers. It serves as a dynamic snapshot of who they are, containing multitudes of details, like demographic information, such as the city of residence, and online behaviors, such as page visits or purchases.

Gladly explains the basics of first-party data in this post: what it is, how to use it, and its pros and cons compared to third-party data. Gladly also explains how customer service teams can strategically use first-party data to upgrade the quality of service they’re providing while building more personal, effective customer relationships.

What is first party data?

First-party data is collected and used by companies once customers willingly provide it. Examples include online behavior on websites or apps, CRM or membership data like product preferences or city, and is often gathered on forms or pages.

Examples of first party data

First-party data is information about customers from online and offline sources, such as the company’s website, app, CRM, social media, or surveys collected by individual websites. Because first-party data is provided directly by the customer, it is highly accurate and specific to that individual.

Some common examples of first-party data include:

  • Location information, like home address and city, state, zip code, or country
  • Age-related information, like a birth date (day, month, year)
  • Contact information, like email address, phone number, or social media accounts
  • Past product purchases (type purchased, product cost, date of purchase)
  • Website behavior (landing pages viewed, forms completed, survey responses or participation, etc.)

Pros of first party data:

  • It is more accurate than second- or third-party data
  • It is provided with consent by customers
  • It can be used to target relevant services or products based on a user’s established location, preferences, or past purchases

Cons of first party data:

  • It is limited to interactions that companies have with their customers

Leveraging Customer Data to Deliver on Expectations


Using first-party data to improve customer service

It seems obvious, but it’s true: knowing who your customers are on an individual level is necessary if you want to provide quality customer service. To resolve basic customer issues or answer questions, support teams will need easy access to data like your customer’s location, any items they’ve purchased, or behaviors they’ve taken on your website, like signing up for a newsletter.

To truly level up your customer support–from being reactive to proactive to providing white-glove customer service based on personalized recommendations–support teams need tools that unlock customer data management beyond the basics.

In Gladly’s Customer Profile, first-party data is instantly accessible so that support agents can provide quality support. Let’s look at a few key areas where first-party customer data can be used to improve customer service:

Past Purchase Data

Past purchase data is one of the most useful data points for customer service teams because it unlocks a treasure trove of insights into individual shoppers.

What your customers buy

What are your customers buying? Maybe they purchased an item with a specific setup or handling instructions or a limited edition product with low remaining quantities in your store. By seeing the previously-purchased product, support teams can direct customers to self-service resources with setup or handling information or make recommendations for similar products they can purchase.

Additionally, suppose a customer has an issue with a recently-purchased product. In that case, support teams can see all of those details–like an image of the product and the customers’ order number–without asking the customer.

When your customers are buying

When are your customers making purchases? Perhaps the customer makes purchases annually, during a holiday sale, or on their birthday. Recognizing buying patterns allows customer service teams to anticipate future purchases, possibly giving customers a heads up if another sale is coming up or if there’s a discount code they can use on a future purchase.

How often are your customers buying

How frequently are your customers making purchases? Have they only made one or two previous purchases, establishing them as a newer buyer, or are they a dedicated customer with double-digit purchases under their belt? Customers who are less familiar with your brand require a different approach. Customer service teams should be able to calibrate their interactions for each type of customer.

Product Preference Data

What are your customers’ likes and dislikes? Imagine seeing at a glance which of your products are most popular with your customers. With this data, customer support teams can make personalized product recommendations aligned to the individual customer tastes. Further, support teams can use product preference data to cross-sell appropriately or upsell to your customers–the promised land for customer service teams looking to drive incremental revenue.

A CX Platform that Prioritizes First-Party Data

Customer service is a challenging line of work–even when teams have access to all the data they need to do their jobs quickly and efficiently. Consider: does your current customer service software support the basic needs of your CX team? Does it easily and instantly surface crucial customer data, such as past purchase and preference data? Gladly’s platform does both of these things and places the customer at the center of interactions with your brand, ensuring a more personalized customer service experience.

Take a tour of Gladly today.