This morning I read the blog post I published earlier, and I liked it. That made me think about a follow-up post.
This post is not only about data. It is about the workflow behind the data — the back-and-forth between me, Google Analytics, Google’s chatbot, ChatGPT, and then back to me again. In the middle of all that, there are questions, answers, and a few jargons that can easily make a simple thing feel complicated.
That is where ChatGPT becomes especially valuable to me.
Google Analytics gives me numbers, patterns, and technical terms. Sometimes those words are helpful, but sometimes they are too heavy or too technical for an ordinary reader. I do not want to just look at numbers. I want to understand what they mean in real life.
So the process goes something like this:
I look at Google Analytics.
I ask questions.
I read the answers.
When something is unclear, I turn to ChatGPT.
Then ChatGPT explains the same idea in plain English.
That part matters most.
Because once the jargon is removed, the meaning becomes clearer. I can see what is happening on the blog, what readers are doing, and what may be worth paying attention to next. More importantly, I can understand it without feeling lost in technical language.
This is why I appreciate ChatGPT so much. It does not just give information. It helps translate information into language that feels human and practical.
For me, that is the real value. Not just data. Not just jargon. But understanding.
When I look back, I realize that this whole learning journey is not really about one tool or one report. It is about the conversation between the tools and me. Google Analytics shows me what is happening. ChatGPT helps me understand why it matters. And then I can decide what to do next.
That is the kind of workflow I want to keep using.
Not because it is fancy. Not because it sounds technical. But because it helps me learn, improve, and write more clearly for my readers.
In the end, plain English is not a small thing. It is the bridge between information and understanding. And for me, that bridge is where the real value lives.
My takeaway
The numbers matter.
The questions matter.
The explanations matter even more.
And when ChatGPT turns jargon into plain English, that is when the message becomes useful to me and, I hope, to my readers too.
#AI123 #GoogleAnalytics #ChatGPT #GoogleChatbot #BloggingTips #PlainEnglish #DataExplained #AIForBloggers #ContentCreation #TechMadeSimple
我和 Google Analytics、Google 聊天机器人、ChatGPT 之间的一段对话
今天早上，我读了自己昨天发布的博客文章，我很喜欢那篇文章。这也让我想到，明天可以写一篇后续文章。
这篇后续文章不只是讲数据，而是讲我和 Google Analytics、Google 的聊天机器人、ChatGPT 之间的工作流程——我来回提问、回答，再继续追问。中间会出现一些术语和行话，有时候这些词会让原本简单的事情变得复杂起来。
这正是 ChatGPT 最有帮助的地方。
Google Analytics 给我的是数字、趋势和一些技术性词语。它们当然有用，但有时候太专业了，普通读者看了不容易马上明白。我不只是想看数字，我更想知道这些数字在现实中代表什么。
所以，这个过程大致是这样的：
我先看 Google Analytics。
然后我提出问题。
我阅读得到的答案。
当有些地方不清楚时，我就会去问 ChatGPT。
接着，ChatGPT 会把同样的内容用浅白的英文解释给我听。
这一点最重要。
因为一旦把行话拿掉，意思就会清楚很多。我就能看懂博客正在发生什么，读者在做什么，以及哪些地方值得我继续留意。更重要的是，我不需要被技术语言弄得一头雾水。
这也是我为什么这么欣赏 ChatGPT。
它不只是提供信息，它还帮我把信息翻译成更像人话、更实用的表达。
对我来说，这才是真正的价值。不是只有数据，不是只有术语，而是真正的理解。
回头看，我发现这整个学习过程，其实不只是关于某一个工具，也不只是关于某一份报告。它是工具和我之间的一段对话。Google Analytics 告诉我正在发生什么，ChatGPT 帮我理解这些内容为什么重要，然后我再决定下一步该怎么做。
这就是我想继续使用的工作流程。
不是因为它看起来很高级，也不是因为它听起来很专业，而是因为它帮助我学习、改进，并且写得更清楚，让读者更容易明白。
最后，浅白的英文并不是小事。它是信息和理解之间的桥梁。对我来说，那座桥就是价值所在。
我的体会
数字很重要。
问题很重要。
而解释得清楚，比什么都重要。
当 ChatGPT 把行话变成浅白英文时，那一刻，信息才真正变得有用，不只是对我，对我的读者也一样。