User Types, Conflating Analytics Data and SGE

When I analyze website traffic in Google Analytics (GA), I find it essential to grasp how new and returning users are categorized. Here are some insights I keep in mind, along with considerations for Google’s Generative Experience in 2024:

-Timing of Visits: I’ve noticed that GA can show slightly inaccurate numbers for users visiting my site around midnight. This often happens as sessions transition into a new day, which can affect tracking. If you’re interested, you can find more details in this resource: [Misunderstood Metrics: New vs. Returning Visitors](https://help.analyticsedge.com/article/misunderstood-metrics-new-vs-returning-visitors/).

-Dual User Labels: Over an extended date range, I see that the same individual can be labeled as both a "new" user during their first visit and a "returning" user when they come back. This can lead to some confusion when calculating totals.

-Interchangeable Terms: I’ve observed that GA primarily uses "users" in its interface but refers to "visitors" in the actual dimensions. Both terms essentially describe unique browsers or devices, whether I’m working with the API or creating advanced segments.

-Session Tracking: Each user generates sessions, and I find that their first session is tagged as "new," while any subsequent visits are marked as "returning." It’s crucial to remember that adding new and returning users won’t equal total users since many users fall into both categories. A higher total of new and returning users usually indicates frequent revisits.

-Cookie Management: While GA aims to store cookies in browsers for up to two years, I’ve seen that users can disrupt this by deleting cookies, switching devices, or using privacy features in browsers like Safari, which shortens cookie lifetimes.

Considerations for Google’s Generative Experience in 2024:

-AI and Traffic Insights: With the rollout of Google’s Search Generative Experience (SGE), I recognize that AI will play a larger role in user engagement. This could lead to increased AI-driven traffic, which might affect the ratio of new to returning users.

-Changing Search Patterns: As users interact more with AI-generated content, I anticipate a potential decline in returning visitors, as quick AI responses may reduce the need for them to revisit my site for information.

-Emphasis on Quality Content: I understand that Google’s AI will favor high-quality, authoritative content. Sites like mine that focus on delivering valuable, expert information are more likely to be featured in AI-generated results, which could attract more new visitors but potentially reduce repeat visits from those seeking basic answers.

-Attribution Challenges: With SGE, I’m aware that attributing impressions can become complex. AI-generated responses might not always lead to direct clicks, making it harder to accurately track new user engagement through GA.

-User Journey Evolution: As AI enhances user experiences, I’m keen to observe how user journeys adapt. Some returning users may bypass traditional search processes and rely on AI summaries, which could impact their frequency of visits.

By keeping these factors in mind, I feel better equipped to navigate the intricacies of GA data in 2024, especially with the advancements in AI and the Search Generative Experience. This approach leads to a clearer understanding of user behavior on my site.