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A top-level guide to data lakes
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Data Warehouse Architecture
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How to Create and Use Business Intelligence with a Data Warehouse
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Data Warehouse Best Practices — preparing your data for peak performance
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Data Warehouses versus Databases: What’s the Difference?
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Key Concepts of a Data Warehouse
Data Warehouses versus Data Lakes
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What Is Customer Data?
Customer Data Analytics
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Collecting Customer Data
The Importance of First-Party Customer Data After iOS Updates
Types of Customer Data
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What is an Identity Graph?
Customer Data Protection
A complete guide to first-party customer data
CDPs vs. DMPs
What is Identity Resolution?
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Data Access Control
Data Sharing and Third Parties
What is PII Masking and How Can You Use It?
Data Security Strategies
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How To Handle Your Company’s Sensitive Data
Data Security Best Practices For Companies
What is Persistent Data?
Google Analytics 4 and eCommerce Tracking
What Is Google Analytics 4 and Why Should You Migrate?
GA4 Migration Guide
GA4 vs. Universal Analytics
What are the New Features of Google Analytics 4 (GA4)?
Benefits and Limitations of Google Analytics 4 (GA4)
Understanding Google Analytics 4 Organization Hierarchy
Understanding Data Streams in Google Analytics 4
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A complete guide to first-party customer data
A complete guide to first-party customer data
Every company wants to optimize its customer experience and digital marketing strategies in order to drive growth. To do that, they need data.
Marketing and advertising teams have historically relied on data collected from third-party sources such as third-party cookies to inform their targeting and advertising efforts. However, both Google and Apple have announced plans to phase out the use of third-party cookies, so it's time to lean into first-party data and the opportunities it affords.
First-party data provides first-hand insights collected directly from the company's digital properties (data sources like websites or apps) and various brand channels. Marketers and advertisers should start using first-party data because it offers a more accurate and complete outline of customer profiles. To do that, you need to understand what first-party data is, why you should use it, and how to use it.
What is first-party data?
To fully comprehend what first-party data is and why it’s better, let’s discuss the other categories of data: third-party and second-party data.
Third-party data is any user information purchased from an external source(data vendors) that doesn’t have a direct relationship with the user. Data vendors collect user data from various sources like surveys, questionnaires, government lists, voter documentation, credit reports, etc. They then aggregate the data, segment it, and upload it to data providers like Acxiom, Nielsen, or OnAudience, for sale.
Third-party data is mainly used for ad targeting and prospecting. For example, a fantasy football league wants to advertise to possible sports lovers, so they buy a list of users who have bought football accessories in the past from a data vendor.
This category of data is pricey, and its reliability, accuracy, recency, and privacy compliance cannot be guaranteed. For example, a list of 1,000 consumers with perceived health conditions costs around $79 and usually requires additional funds and resources to clean after purchase.
Second-party data is much better than third-party data. This data comes from reputable companies that have a direct relationship with the users whose information is being sold. As a result, you can trust its recency, relevance, quality, and accuracy. For example, the same fantasy football league can buy a list of subscribers who frequently watch football from a cable company.
Still, there's the issue of high acquisition costs and limited availability with second-party data. Because second-party data is more exclusive and sold directly from the source, it's usually more expensive than third-party data. Also, finding companies willing to trust you with their data can be a challenge, and your access to their data only lasts as long as you have an agreement with them. Furthermore, because second-party data can't explain what motivates your customers, it can't provide a precise lookalike representation of your customers, so it'll produce lower-quality results when used to run ad campaigns.
That's why first-party data is king. It's free. It's readily available. It offers a complete representation of your customer's behavior, and most importantly, it's yours.First-party data comes directly from software and systems (e.g., websites, mobile apps, emails, social media accounts, call centers, CRMs, etc.) your company owns. This data can take the form of:
- purchase history
- website activity
- email engagements
- sales interactions
- support calls
- customer feedback programs
- preferences of individual customers
First-party data is based on your customers’ actual interactions with your brand across all your consumer touchpoints rather than the behavior of alleged lookalikes from other companies. So, aggregating all of that data gives you a solid foundation for understanding your customers’ behavior.
In turn, this accurate view of customers' behaviors and buyer journey will enable your company to improve ad efficiency, build better messaging, enhance marketing funnels, and create the type of highly personalized experiences that drive brand loyalty, retention, and ultimately, higher ROI.
Why should you use first-party data?
Collecting first-party data allows you to build a holistic view of your customer's preferences and behaviors, which in turn provides your company with enough data to derive valuable insights and make data-driven decisions.
It facilitates predictive analysis
Predictive analysis uses data and machine learning techniques to identify the likelihood of future outcomes based on historical data. When properly collated and unified, first-party data provides companies with the type of data they need to better understand potential customers and predict future customer behavior patterns.
Predictive analysis enables companies to forecast inventory to reduce waste and determine a mix of products to entice consumers to make a purchase and maximize profit. For example, Voot, an Indian premium on-demand platform, used predictive analysis based on first-party data to accurately predict and reduce monthly churn by 35%.
It helps uncover opportunities for cost savings
You can use insights from first-party data to guide marketing budget allocations. Understanding how each point in the customer journey affects conversion provides a more accurate way to analyze attribution and optimize your marketing budget.
For example, with insights from first-party data, Voot not only won back higher-propensity-to-churn users, it also unlocked a new level of cost efficiency: remarketing budgets were now only spent on users who needed that extra nudge rather than those who were certain to return.
It helps to amplify revenue-generating opportunities
Companies can use insights from first-party data to derive and implement growth strategies like offering optimized cross-selling or personalized recommendations tailored to specific interests, preferences, location, and purchase history. They can also use it to draw more accurate conclusions about customer behavior to improve segmentation and targeting efforts. All of which leads to more revenue.
Google found that companies using first-party data for key marketing functions achieved up to a 2.9X revenue uplift. For instance, Eli Lilly, a large pharmaceutical company, used insights from their first-party data to personalize the customer experience across digital touchpoints, which led to a 12% to 35% increase in ROI.
In another case study, Rituals, a bath and body retail company, increased conversions by 85% by using insights from its first-party data to find more valuable customers.
How to collect first-party data
Before you jump into collecting first-party data, you should understand and define what goals you'd like to achieve as an organization. This will help you with your first-party data strategy and determine what types of data you'll need to collect and how you'll use it. Once that's done, you can start collecting data and sending it to various tools, where it will be activated.
However, setting up an efficient pipeline for first-party data collection is not the easiest thing to do. In addition to collecting data from your various customer touchpoints, you'll need to standardize the data, which means clearly defining consistent naming conventions and schemas, as well as providing context for how to interpret the data. You also need to perform quality assurance checks to ensure the data is collected in the exact format specified and any inconsistent data is detected early on. You also have to enforce data consistency to ensure when any data value changes in one place, the changes will also be reflected in other tools to maintain a unified customer profile.
These are all difficult problems to solve. Hence, you'll need the technical expertise of a data engineer alongside a customer data platform (CDP) — like RudderStack. Check out this post to learn how engineering teams use RudderStack to support marketing.
Properly implemented by engineering, a CDP will effortlessly handle the tasks of collecting data from different sources, maintaining data integrity, cleaning up dirty data, and enforcing data consistency. It will also aggregate all the data into a centralized location with a single view of each customer so all teams (marketing, sales, customer success, etc.) can run analyses to derive insights that'll help them attract, close, and retain customers successfully.
First-party data should be the cornerstone of your marketing strategy
With Google and Apple killing the ad cookie in an effort to improve data privacy, one thing is clear: third-party data access is on its way out. Setting up systems to begin collecting the data available to you today in the form of first-party data is laying the groundwork for your company's long-term success.
Learn more about how RudderStack can help your company get started with your first-party data journey.