First-party Data: Benefits, Types, Collection Methods & Use Cases

First-party Data: Benefits, Types, Collection Methods & Use Cases cover

Want to truly understand your customers and deliver experiences that keep them coming back for more? The secret lies in first-party data.

This article will explore how to collect and analyze it effectively, diving into methods like feedback surveys, product analytics, and more. We’ll provide practical examples and actionable advice that will inspire you to create personalized user experiences based on data.

TL;DR

  • First-party data is information you collect directly from your audience or customers.
  • Benefits of using first-party data:
  1. Higher accuracy and relevance because you’re getting information from the source.
  2. Better opportunities to create personalized customer experiences.
  3. Long-term cost savings since you don’t have to pay for third-party data providers.
  4. Greater control and ownership over customer data.
  • First-party data types include behavioral data, customer purchase history, and demographic and psychographic data.
  • You can collect first-party data in the following ways:
  1. Track user behavior on your website and app.
  2. Trigger contextual customer feedback surveys.
  3. Dig into your CRM systems and customer support interactions to gather insights.
  4. Track social media interactions to understand customer sentiment.
  • Here is how you can use first-party data:
  1. Trigger personalized experiences for different audience segments.
  2. Perform predictive analysis and identify upsell opportunities.
  3. Use product usage insights to make data-driven improvements.
  4. Leverage user behavior data for targeted advertising.
  5. Send targeted emails based on first-party data.
  6. Create a tailored content strategy that addresses user needs and preferences.
  • Other types of data include:
  1. Zero-party data: Information customers willingly and proactively share with you.
  2. Second-party data: Another company’s first-party data shared directly with you through a partnership.
  3. Third-party data: Information collected by external entities and sold to businesses.

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What is first-party data?

First-party data is the information your company collects directly from its audience or customers.

This data is typically gathered through touchpoints like website visits, in-app interactions, customer surveys, social media engagements, and purchase histories.

Why is first-party data important?

There are various ways to source customer information and get data-driven insights, but here’s why first-party data is a more effective tool:

Higher accuracy and relevance

Data from your audience is inherently more accurate and relevant than other types of data because it is sourced from your own channels.

This eliminates any concerns about the information being outdated or biased, which can often be the case with second or third-party data collected from external sources.

Additionally, a first-party data strategy enables you to collect data specific to your business. You can design data collection mechanisms that prevent data discrepancy and capture the exact information you need.

Improved personalization

Many companies struggle to deliver targeted product marketing messages.

First-party data helps you solve this problem. How, you ask? By obtaining critical data about your audience’s interests, purchase history, and behavior, you can better tailor their experiences and improve conversion time.

For example, if your behavior analytics show a specific user group enjoys video content better, you can trigger more of these when delivering in-app tutorials, increasing engagement and adoption rates.

Cost-effectiveness

By using first-party data, you reduce reliance on costly third-party data providers. The initial investment to build your own solution may seem expensive, but it will lead to long-term cost savings because you can improve your ROI on marketing campaigns and product development.

With a deep understanding of your customer’s needs and preferences, you can create targeted product marketing campaigns that are more likely to resonate with your audience and drive conversions. This reduces wasted efforts on ineffective marketing campaigns that target a broad, unsegmented audience.

In addition, you can always consult first-party data accumulated over time to identify areas for product improvement or new product opportunities.

Greater control and ownership

With first-party data, you have complete control over how your data is collected, stored, and used. This means you can tailor your approach to meet specific business goals, comply with relevant regulations, and maintain user trust.

Plus, since only you have access to this wealth of customer information, you can conduct data-driven analysis and generate insights to build your competitive edge and establish yourself as an industry leader.

Case in point: we created a SaaS product metrics benchmark report based on first-party data from 547 companies—go check it out!

Types of first-party data

First-party data comes in various forms, but here are the main types:

  • Behavioral data: This includes details about customer browsing patterns, page views, time spent on a page, button clicks, most used features, and other relevant behavior data from your analytics tool.
  • Purchase history: This data covers a customer’s financial interaction with your brand. It includes subscription plans, purchase frequency, total spending, etc.
  • Demographic data: This provides insights into your customers’ characteristics, such as age, gender, location, job role, company size, and industry. It allows you to segment your audience and tailor marketing campaigns and product experiences to specific groups.
  • Interests: This data uncovers which topics, features, or product categories your customers are most interested in.

How to collect first-party data?

There are three main channels for first-party data tracking:

On your website

Some methods of collecting first-party data on your website include:

  • User behavior: Use behavior tracking tools to record mouse movements, clicks, time spent on different pages, etc. This will help you understand what content resonates, where visitors might get stuck, and how to improve their overall experience.
  • Form submissions: Use newsletter sign-ups, feedback forms, or account registration forms to collect visitor data and learn more about them. Don’t make your forms lengthy; just aim to gather basic info like names, email addresses, job roles, and company size.
  • Cookie data: Cookies are small files stored on a user’s browser when they visit your website. They can show you how often a person visits, which pages they favor, and where they come from. First-party cookies are more important than ever as major browsers continue to phase out third-party cookies to limit cross-site tracking.

In your apps

App interaction is one of the best channels for collecting first-party data. Here’s how to go about it:

  • Auto-capture: Analytics tools like Userpilot have auto-capture features that allow you to automatically track user activity in-app. You can record actions like clicks, text inputs, and form submissions without manually tagging them or waiting for your busy engineers.
raw_data_settings-Userpilot-autocapture-first-party-data
Track first-party data code-free with Userpilot.
trend-analysis-Userpilot
Trend analytics report generated with Userpilot.
  • Customer feedback: Trigger feedback surveys to gather customer opinions about your flows and features, and then analyze the data to identify friction points and make improvements.
RecruitNow-inapp-survey-first-party-data
RecruitNow onboarding survey.

Through customer interactions

Direct customer interactions offer a ton of opportunities to collect valuable first-party data that can drive your business forward. Here are some examples:

  • CRM systems: Your customer relationship management (CRM) system meticulously records every touchpoint, from sales inquiries and support tickets to purchase history and communication logs. Analyze this data to gain a comprehensive understanding of individual customer preferences, behaviors, and pain points.
  • Customer support: Track user interactions with your customer support, whether it’s with an agent, chatbot, or via email.
Userpilot chat support.
Userpilot chat support.
  • Customer interviews: Schedule one-on-one or group interviews to gather more in-depth feedback. User interviews are effective because they allow customers to express themselves more openly and elaborately than they might in an in-app survey.
Interview in-app invitation generated with Userpilot.
Interview in-app invitation generated with Userpilot.
  • Social media interactions: Actively monitor and engage with customers on social media to gain insights into their opinions, sentiments, and perceptions. You can also use social media to conduct polls, surveys, and contests to gather additional first-party data.

How to use first-party data to make informed decisions?

Now that you’ve learned how to gather first-party data, let’s explore ways to maximize it and drive product growth.

Personalized experiences for different segments

You can trigger a welcome survey to collect first-party customer data upfront and use that information to deliver personalized onboarding flows.

As customers increasingly seek tailored experiences, they are often willing to share basic information in exchange for personalization. However, ensure that your welcome survey is as brief as possible. Ask for only essential details such as name, industry, role, and jobs-to-be-done, like in this example:

welcome-survey-Userpilot
Userpilot welcome survey.

Once you’ve gathered sufficient data, leverage it to segment users and trigger tailored onboarding experiences. Your onboarding should highlight relevant features, provide industry-specific templates, and offer personalized tips to help them make the most of your tool.

Besides welcome surveys, you can also use behavior data to understand customer needs and provide personalized product recommendations.

For example, an e-commerce brand could trigger special offers to website visitors based on their browsing behavior. This targeted approach will make customers feel understood and boost their chances of buying.

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Tarte personalized product recommendation.

Predictive analytics for upselling

Avoid triggering upsell messages randomly, as they can annoy users if sent at the wrong time.

Instead, leverage your first-party data to conduct predictive analysis and determine the optimal time for upsells. For example, if a user consistently maxes out their storage limit before the end of the month, an ideal time to upsell would be shortly before the next month’s limit resets.

Userpilot can help you analyze customer data, determine upsell opportunities, and create contextual triggers like this:

upsell_prompt-first-party-data
Upgrade tooltip made with Userpilot.

Data-driven product improvements

By analyzing product usage and feedback data, you can understand how users interact with your tool, which features they use most frequently, and where they encounter friction. Then, you can use those insights to prioritize your product improvement efforts.

This strategy also works when you need to validate a new product idea. For example, imagine your team is thinking of building a “Goals” feature to help users perform better project management, but you’re unsure if users will like it.

You can build a fake door test by creating a modal that briefly explains what the upcoming feature does and invites users to sign up for a beta. If you have a good percentage of users clicking your fake door test, that’s a sign customers are interested, and you should prioritize this feature.

Fake-door-test-Userpilot
Fake door test with Userpilot.

Behavioral targeting for ads

Leverage the first-party data you have about users to create behavioral marketing campaigns that target them based on their browsing history, purchase behavior, and in-app interactions.

For example, if you’re an online retailer, you could identify users who have shown interest in a particular product but haven’t yet made a purchase. With behavioral targeting, you can send them personalized ads showcasing relevant products, discounts, or limited-time offers to increase your conversion rates.

Customized email campaigns

Segment your email list based on relevant factors such as past interactions, purchase history, browsing behavior, and demographics. Then, send targeted emails that resonate with their needs and interests.

For instance, if a trial user of your graphic design platform frequently uses the social media template creation feature, you could send an email highlighting upcoming webinars on social engagement, exclusive template bundles for paid users, or a limited-time discount offer.

This data-driven email marketing is more likely to convert them to a paid subscription than a generic reminder, as it demonstrates the value of your platform in regards to their specific interests.

You can also integrate Userpilot with HubSpot and automatically send emails to users based on specific actions like feature usage, survey response, or engagement with in-app flows.

hubspot_userpilot-integration
HubSpot and Userpilot integration.

Tailored content strategy

First-party data on your audience’s pain points, preferences, and behavior can help you create a content marketing strategy that addresses their needs and aspirations.

For example, a fitness app can create personalized workout guides for different customer segments, such as beginners, intermediate, and advanced users, based on first-party data like workout history and fitness goals. This tailored approach ensures the content is relevant and engaging for each segment, increasing user satisfaction and retention.

Other types of data

Here are other data types you can combine with your first-party data for a more comprehensive data-driven analysis:

Zero-party data

Zero-party data is information that customers intentionally and proactively share with your brand.

Similarly to first-party data, zero-party data is highly valuable because it comes directly from the source and often reveals preferences, interests, and intentions that you might not easily infer from other data types. You can collect it through feedback surveys, user reviews, direct communication, etc.

Second-party data

This is another company’s first-party data that is shared with you through a partnership. Collecting second-party data requires establishing mutually beneficial partnerships with other businesses, which could involve co-creating marketing campaigns, mutual data sharing, or cross-promoting products.

You can also use a customer data platform like Snowflake Data Marketplace and AWS Data Exchange to gain marketing analytics data (e.g., campaign performance, customer behavior), customer success data (e.g., churn rates, product usage), and general business data (e.g., industry trends, competitive analysis) from other companies.

Third-party data

This is data collected by external entities that do not have a direct relationship with your users. It’s often aggregated from various sources and sold to businesses for marketing and analytics purposes—a good example is Qualtrics’s market research service.

While third-party data can be useful for supplementing your own data and gaining a wider perspective—thus adding another layer to your customer intelligence efforts—it’s important to remember that it’s not as specific or reliable as first- or zero-party data.

Conclusion

And that’s a wrap!

First-party data is one of the most effective tools for understanding your customers and creating delightful product experiences.

The sooner you start, the more historical insights you’ll gather for making strategic decisions. You can begin right away—grab a Userpilot demo to see how our platform can automate customer data collection and help you build a better product based on user interactions and feedback.

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