In Google Ads, AI Max is not a separate campaign type but a set of AI enhancements embedded within existing search ads. As a result, the methods for viewing data and analyzing performance are integrated into your Search campaign reports.

Once AI Max is enabled, advertisers are most concerned with performance: how do features like expanded keyword matching, automatically generated ad copy, and AI-selected landing pages impact traffic and conversions? In Google Ads, we can use several key reports to gain deeper insights into AI Max performance.

If you’re running search ads, you’re probably familiar with this scenario: you open Google Ads in the morning, and your account is full of keywords to optimize. Some keywords have spent a lot but brought no conversions, while some long-tail searches you never thought of are showing up in the reports. You spend half a day adding and excluding keywords, yet it feels like you can never keep up with changing search behavior.

What is Commercialization?

When people hear “commercialization,” the first thought is often “making money.” That’s not wrong—turning a business, product, or traffic into revenue is indeed the core goal. However, commercialization can be understood in two perspectives: narrow and broad.

Narrow Perspective: Result-Oriented Ways to Make Money

From the most direct angle, commercialization is about converting your business directly into revenue. Some simple examples include:

• Product Sales: Selling goods or services directly generates income, e.g., e-commerce selling clothing or online platforms selling courses.
• Advertising Monetization: Earning revenue from traffic, e.g., social media or short-video platforms displaying ads while users browse content.
• Membership Fees: Users pay for a better experience or exclusive content, e.g., premium subscriptions.

This perspective is obvious: it focuses on “how to make money”, emphasizing results. The key question is how your business generates revenue from users and how to maximize short-term returns.

1. User Insights and Journey Analysis

Before formulating any integrated marketing strategy, in-depth user insights and journey analysis are indispensable foundational work. They help the brand truly understand who the target users are, their needs and pain points, as well as their behavior patterns along the purchase path, thus providing a scientific basis for subsequent strategy formulation.

What is User Insight?

User insight is a deep understanding of the target users, covering their basic profiles (age, gender, region, occupation, etc.), behavior habits, interests and preferences, purchasing motivations, and barriers. It is obtained through data analysis (website behavior data, social interaction data, CRM data, etc.), user interviews, surveys, and market research, providing a comprehensive and multidimensional user perspective.

When taking notes in Obsidian, using images is almost inevitable. Copying and pasting images directly is indeed convenient, but over time you’ll find that the images are chaotically placed, resizing them is troublesome, and centering an image is even more difficult. Another pitfall is that when you delete an image from a note, the file doesn’t actually disappear but remains hidden in the root directory.

What Exactly Are Images in Obsidian?

When it comes to images, many people’s first thought is that “inserting an image means adding an image directly.” However, in Obsidian, images are more like references to “external files.” In other words, the images aren’t directly embedded in the note content but are stored in folders on your computer and then displayed in the notes through links or references.

In the era of information overload, more and more people are realizing that organizing and consolidating knowledge is more important than acquiring it. Obsidian, a note-taking app focused on local knowledge management, has rapidly gained popularity among productivity enthusiasts and knowledge workers in recent years. It is not just another cloud-based note-taking tool but a “second brain” system that emphasizes local storage, Markdown formatting, and linked thinking.

The Core Philosophy of Obsidian

At its core, Obsidian is about building a knowledge network that you control. Unlike traditional linear note-taking, Obsidian advocates for nonlinear linked notes. By linking different notes, you can create a multidimensional, interconnected knowledge graph.