With the phasing out of third-party cookies in year 2024, and the increasing intensity in the digital advertising market, many brands are gradually turning to first-party data. Brands are shifting their marketing focus from 'acquiring high volumes of traffic' to 'cultivating brand loyalty among existing customers'. To support this shift, brands are increasingly adopting various data analytics tools to gain insights into customer behavior to establish more personalized marketing communications.
Among these tools, GA4, used by over 95% of marketers worldwide, provides rapid insights into online traffic. In contrast, the Customer Data Platform (CDP), one of the most talked-about tools in recent years, focuses more on the integration of multi-channel data and personalized marketing applications. Both GA4 and CDP are indispensable for entering the realm of data-driven marketing. However, the ability to maximize their potential and value depends on the brand’s current operational needs.
This article will provide a detailed introduction to the application scenarios of both tools, helping you to clearly understand the differences between GA4 and CDP. With a better understanding, you can leverage these digital tools to their fullest potential and achieve the greatest impact and effectiveness in your marketing efforts.
GA4 is typically used for analyzing on-site traffic and collecting first-party data from websites and apps. It helps marketers quickly understand user acquisition channels and on-site behavior interactions.
For example, marketers can use GA4 to determine the number of users visiting the website within a specific period, the percentage of users by device type, the average number of pages viewed, and the share of traffic from organic search versus paid search.
In contrast, a CDP acts more like a 'customer data platform' for enterprises. It integrates first-party data not only from brand websites, but also from both online and offline channels (such as e-commerce data, apps, and offline POS and CRM systems). CDPs focus on individual customers, providing a 360-degree analysis of each customer's attributes and behavior preferences. When combined with automated marketing applications, CDPs can help brands achieve highly personalized communication, enhancing customer experience. For example, marketers can use a CDP to understand specific audience segments or individual customers, track which products they add to their cart, what they purchase, and their total accumulated spending, both online and offline.
Overall, GA4’s primary function is to help brands quickly grasp on-site traffic and behavior trends, whereas a CDP does not only collect customer-centric, multi-channel data, but also assist brands in applying insights to personalized marketing, achieving a 'one-stop data integration and marketing application'. For the basic understanding of some important concepts regarding the GA4 and CDP, we will delve into the differences between both the tools in terms of data collection and functional applications in the next section. Join us as we uncover the unique capabilities of each tool!
Both GA4 and CDP are built to understand, design, optimize and help brands achieve marketing goals. However, both have different approach when it comes to marketing automation. GA4 allows marketers to create audience lists based on specific behaviors using its audience-building tools. These lists can then be connected to Google Ads for manual retargeting of ad campaigns. This helps in identifying and targeting users who have performed particular actions on the website, thus enhancing the precision of advertising efforts.
In contrast, CDP’s key advantage lies in its multi-channel marketing automation capabilities. A CDP can integrate data from various sources, including social media, email, websites, and physical stores, enabling businesses to implement unified and coordinated marketing strategies across different channels. CDPs support automated marketing campaigns such as email marketing automation and personalized ads. They also allow the design of customer journeys based on interaction history and preferences, ensuring consistent and personalized customer experiences at various touch points, which enhances brand loyalty and improves conversion rates.
For example, OmniSegment CDP exemplifies these capabilities by combining built-in AI segmentation models to meet diverse marketing needs. Beyond selecting specific audiences for digital ad campaigns, it intelligently chooses the best channels (e.g., EDM, WhatsApp, SMS) for message delivery based on individual interaction behaviors and activity times. It can even automate AI-driven product recommendations for first-time visitors, facilitating real-time, two-way communication that quickly stimulates purchasing intent and boosts brand revenue.
GA4 can only collect data from websites and apps that have tracking codes installed. Offline transaction information and user membership data must be manually imported into GA4’s backend. This process requires careful attention to data format compatibility and the accuracy of data from various channels.
In contrast, CDPs can collect and integrate customer data from multiple sources, including both online and offline channels. This capability is particularly beneficial for brands with a strong physical presence, as integrating online and offline membership identities is a significant challenge. CDPs can automatically and in real-time integrate data from various first-party channels, such as official websites, apps, offline POS systems, CRM membership data, and social media accounts, through pre-established connections. This helps brands build a comprehensive 360-degree customer profile, enabling them to develop customer-centric marketing strategies.
GA4 focuses on 'analyzing on-site traffic', helping marketers understand how many interactions occurred, but not who interacted. For example, GA4 can tell you that product A was viewed 1,000 times, but it won’t tell you who viewed it. If a brand wants deeper insights into each user’s interaction behavior, it must integrate with BigQuery.
On the other hand, CDP helps brands focus on the customer, collecting and analyzing customer data and behavior. For instance, if Member A clicks on a clothing ad via WhatsApp at 10 AM, browses product information on the website at noon, and purchases the product in a physical store after work, all these actions are recorded and analyzed by the CDP. This enables marketers to understand the behavioral intent behind each decision, allowing for more personalized approach of marketing communications, thus improving conversion rates and revenue.
With comprehensive data from a CDP, brands can better understand their customer base, conduct more accurate target market analysis, and design effective marketing campaigns. Additionally, CDPs offer advanced customer segmentation and predictive analytics tools, helping brands automate and personalize marketing activities based on customer behavior, preferences, and transaction history.
GA4 retains data for up to 14 months, with user-level data (such as age, gender, and interests) only available for a 2-month retention period. Additionally, data collection and processing can have a delay of up to 48 hours.
In contrast, the data retention period for CDPs varies by provider. For example, OmniSegment CDP by beBit TECH can retain customer data from various channels for up to 18 months. It can also collect and analyze behavioral data in real-time, ensuring uninterrupted interaction between the brand and its consumers.
GA4 offers '5 recommended audience segments'. To observe other audiences, marketers must use the 'audience builder tool' to extract the corresponding audience categories based on the brand’s operational goals and campaign periods. This function is relatively complex and requires brands to have a keen understanding of member relationship management and a solid grasp of GA4’s various dimensions to accurately segment customers and identify high-value customers through data reports.
In contrast, OmniSegment CDP provides several AI segmentation models, such as RFM (Recency, Frequency, Monetary) and NASLD (New, Active, Sleep, Lost, Deep) models. These models allow brands to quickly and easily activate refined audience segments, gaining rapid insights into different customer consumption intentions and audience profiles.
For example, the NASLD model automatically tags and segments customers based on 'purchase cycle' and 'purchase frequency', categorizing them as 'New, Active, Sleep, Lost, and Deep'. This significantly reduces repetitive manual tasks and, through close monitoring of member status, allows for more personalized messaging tailored to each customer segment, enhancing the return on investment for each campaign.
Conclusion
For marketers, both GA4 and CDP are incredibly powerful tools. Brands should reevaluate their operational strategies and choose the most suitable tool for their needs. GA4 provides quick insights into online traffic, making it ideal for initially understanding member dynamics. However, if a brand aims for deeper, more comprehensive data analysis and personalized marketing, a CDP can help integrate multi-channel customer data, enabling more precise analysis and application, ultimately enhancing brand value.
If you wish to learn more about OmniSegment CDP by beBit TECH, feel free to click the Contact Us button, and our representative will get in touch with you!