There was a time when I was watching the numbers on AI123.ca almost hour by hour.
The traffic had suddenly exploded.
The numbers were so large that, at first, I wasn't even sure what I was looking at. Google Blogger showed an extraordinary number of pageviews, while Google Analytics was showing a very different picture of where visitors were coming from and how they were behaving.
Eventually, the huge surge ended.
And that could have been the end of the story.
But something interesting happened afterward.
The audience for AI123.ca did not completely return to where it had been before.
Instead, the daily baseline appeared to settle at several thousand pageviews a day.
Then yesterday, something caught my attention again: both the Google Blogger and Google Analytics numbers moved sharply higher—roughly doubling from the previous level.
I don't know yet whether this is the beginning of another sustained period of growth. It is too early to say that.
But after watching this site for several weeks, I have learned something much more valuable than simply watching the numbers go up.
The Big Surge Taught Me Not to Trust One Number
When the traffic first exploded, my natural reaction was excitement.
But excitement isn't analysis.
A large number of pageviews doesn't automatically mean that thousands of people have become loyal readers. Some traffic can be brief. Some can come from search activity, automated systems, unusual distribution, or a temporary event.
So I began looking beyond the headline number.
Where were people landing?
How long were they staying?
Which articles were attracting attention?
Were they looking at another page after arriving?
Those questions changed the way I looked at my blog.
Instead of asking only:
"How many people came to my site?"
I started asking:
"What did they do when they got here?"
That is a much better question.
The Quiet Improvement Was More Important Than the Explosion
The most encouraging development wasn't necessarily the giant traffic spike.
It was what happened afterward.
AI123.ca seemed to establish a larger daily audience than it had before the surge.
That matters to me.
A temporary explosion is exciting.
A permanently higher baseline is potentially much more meaningful.
It suggests that some of the visibility created during the unusual traffic period may have helped the site reach readers who would otherwise never have discovered it.
But I am deliberately using the word "may."
I don't want to turn an encouraging observation into a claim that the data cannot yet prove.
I am still watching.
Google Analytics Became My Teacher
One of the biggest changes in my blogging journey has been learning to use Google Analytics.
Before, I mostly looked at pageviews.
Now I look at landing pages and engagement.
A landing page tells me where a visitor begins the journey.
Engagement tells me whether that visit may have involved genuine attention.
And sometimes the results are surprising.
Some of my articles have attracted readers who stayed for a meaningful amount of time.
That tells me something simple:
People are not necessarily looking for the biggest or most impressive article. They are looking for something useful to them.
I also noticed that some readers were spending time looking at topics related to blogging, Blogger, and the mechanics behind running a website.
That gave me another idea.
Perhaps I shouldn't only write about artificial intelligence.
Perhaps I should also write about what I am learning while building an AI website.
AI Became More Than a Writing Tool
This is where my conversations with my AI companion became important.
I don't simply ask AI to write articles for me.
I bring it the questions that are bothering me.
Why did the traffic suddenly increase?
Why did it fall?
Which pages are attracting attention?
What does engagement time really tell me?
Is a traffic increase meaningful?
What should I watch next?
Sometimes I bring Google Analytics information into the conversation, and we examine it together.
The AI doesn't have a crystal ball.
It cannot tell me with certainty what will happen tomorrow.
But it can help me organize the evidence, explain unfamiliar terminology in plain English, question my assumptions, and see patterns that I might otherwise overlook.
That has changed the way I work.
I am not simply publishing articles anymore.
I am experimenting, observing, learning, and adjusting.
I Am Also Learning What Not to Do
One of the easiest mistakes for a blogger is to become obsessed with traffic.
I know because I have done it myself.
When you see thousands of pageviews appear on the screen, it is tempting to keep checking the number.
But traffic can go up.
Traffic can go down.
A large number can disappear as quickly as it arrived.
What matters more is whether you are gradually building something useful.
So I am trying to take a different approach.
I will continue publishing.
I will continue experimenting with different subjects.
I will continue sharing some of my articles and images on social platforms.
I will continue watching Google Analytics.
But I will try not to let any single day's number determine how I feel about the blog.
What I Would Tell Another New Blogger
If you are starting a blog, I would give you five pieces of advice based on my own experience.
First, don't be discouraged by small numbers at the beginning.
A blog can look very quiet before anyone notices it.
Second, don't become too excited by one giant number.
Investigate where the traffic came from and what visitors actually did.
Third, learn the basics of analytics.
You don't need to become a data scientist. Learn what a landing page, engagement time, traffic source, and returning visitor mean.
Fourth, write about what you are genuinely learning.
Your own experience can be useful to someone else.
And finally:
Fifth, use AI as a thinking partner, not just a content machine.
Ask it questions.
Challenge its conclusions.
Bring it your data.
Let it explain things you don't understand.
But keep making the decisions yourself.
The Story Isn't Finished
I don't know where AI123.ca will be six months from now.
Perhaps this new daily audience will continue to grow.
Perhaps it will level off.
Perhaps another unexpected traffic surge will appear.
Perhaps traffic will fall again.
That's the nature of the internet.
But I have learned something from watching this little website grow.
The real success isn't simply seeing a big number on the screen.
The real success is becoming a better observer.
I started AI123.ca because I wanted to explore artificial intelligence and share what I was learning.
Somewhere along the way, the website itself became another experiment.
I am learning about AI.
I am learning about blogging.
I am learning about readers.
And, with the help of analytics and an AI companion, I am learning how to pay attention.
For now, that is enough.
The journey continues.
Hashtags:
#AI123 #ArtificialIntelligence #Blogging #GoogleAnalytics #Blogger #AITools #BlogGrowth #DigitalJourney #ContentCreation #AIandBlogging #Analytics #LearningWithAI #BloggingJourney #TechForEveryone
AI123.ca 大流量之后，发生了什么？
有一段时间，我几乎每隔一会儿就会打开 AI123.ca，看看网站的访问数字。
那时候，流量突然暴增。
数字大得让我一开始甚至有点不敢相信自己看到的是什么。Google Blogger 显示了非常高的浏览量，而 Google Analytics 则从另一个角度告诉我，访客从哪里来、他们怎样浏览我的网站。
后来，那场巨大的流量高峰结束了。
本来，故事似乎应该到这里结束。
但是，接下来发生了一件让我很感兴趣的事情。
AI123.ca 的访问量并没有完全回到大流量之前的水平。
相反，它似乎形成了一个新的基础——每天仍然有几千次浏览。
而就在昨天，我又注意到了一个变化：Google Blogger 和 Google Analytics 的数字都明显上升，大约比之前的水平增加了一倍。
我现在还不知道，这是不是新一轮持续增长的开始。
现在下这个结论还太早。
但是，经过这几个星期观察 AI123.ca，我学到了一件比单纯看数字更加重要的事情。
那次大流量让我明白：不要只看一个数字
当流量第一次暴增的时候，我的第一反应当然是兴奋。
但是，兴奋并不是分析。
一个非常大的浏览量，并不一定意味着有成千上万的人已经成为你的忠实读者。
有些访问可能非常短暂，有些可能来自搜索，有些可能只是一次特殊的流量事件。
所以，我开始不再只看最大的那个数字。
我开始问：
读者从哪一篇文章进入网站？
他们在那里停留了多久？
哪些文章吸引了他们？
他们进入网站以后，有没有继续阅读其他页面？
这些问题改变了我看待博客的方式。
以前我问的是：
“今天来了多少人？”
现在我更想问：
“他们来到这里以后做了什么？”
我认为，这是一个更重要的问题。
大流量之后的“安静增长”反而更值得关注
对我来说，最令人鼓舞的事情，并不一定是当初那次巨大的流量暴增。
真正让我感兴趣的是：
大流量结束以后，AI123.ca 的每日基础流量似乎比以前高了。
这对我来说很重要。
一次短暂的爆发当然令人兴奋。
但是，如果网站能够长期保持一个更高的访问基础，那可能更加有意义。
这也许意味着，在那次异常的流量期间，有一些新的读者发现了 AI123.ca。
当然，我这里故意用了“也许”。
我不想把目前的数据说成已经得到证明的结论。
我还在观察。
Google Analytics 成了我的老师
这段时间，我最大的一个变化，就是开始真正学习使用 Google Analytics。
以前，我主要看的是 pageviews，也就是页面浏览量。
现在，我开始关注 landing pages，也就是读者进入网站时首先看到的页面，以及 engagement，也就是他们在网站上投入了多少时间和注意力。
一个 landing page 可以告诉我：
读者从哪里开始他们的阅读旅程。
而 engagement 则可以帮助我了解：
这次访问是否可能是真正有意义的阅读。
有时候，结果让我很惊讶。
有些文章吸引来的读者，停留了相当长的时间。
这告诉我一个很简单的道理：
读者不一定是在寻找最宏大、最漂亮的文章，他们是在寻找对自己有用的东西。
我还注意到，有一些读者开始关注博客、Blogger，以及建立和管理网站本身的一些内容。
这给了我一个新的想法。
也许我不应该只写人工智能。
我也可以写：
我自己在建立一个 AI 网站的过程中学到了什么。
AI 对我来说已经不只是一个写作工具
这也是我的 AI companion 对我帮助很大的地方。
我并不是简单地让 AI 替我写文章。
我会把自己正在思考的问题拿出来讨论。
为什么流量突然增加？
为什么后来又下降？
哪些页面最吸引读者？
engagement time 到底是什么意思？
一次流量增加有没有真正的意义？
接下来应该观察什么？
有时候，我把 Google Analytics 的数据带进我们的对话，一起分析。
AI 并没有水晶球。
它不能准确告诉我明天会发生什么。
但是，它可以帮助我整理资料，解释那些我以前不熟悉的术语，用比较容易理解的语言分析数据，也可以提醒我不要太快下结论。
这改变了我的工作方式。
我不再只是不断地发表文章。
我开始：
实验、观察、学习，然后调整。
我也开始学习哪些事情不应该做
一个博客作者很容易犯的错误，就是变得太在意流量。
我知道，因为我自己也经历过。
当你看到屏幕上出现几千、几万甚至更多的浏览量时，很容易不停地刷新数字。
但是流量可以上升。
也可以下降。
一个很大的数字，可能很快就消失。
真正重要的，是你有没有慢慢建立一个对读者有价值的网站。
所以现在，我尝试采用一种不同的方式。
我会继续写文章。
我会继续尝试不同的主题。
我会继续把一些文章和图片分享到社交平台。
我会继续观察 Google Analytics。
但是，我会尽量不让某一天的数字决定我的心情。
如果有人刚刚开始写博客，我会告诉他五件事情
如果你正在开始一个博客，根据我自己的经历，我会给你五个建议。
第一，不要因为刚开始访问量很小就灰心。
一个博客在还没有被人发现的时候，可以非常安静。
第二，不要因为一次巨大的数字就过度兴奋。
先看看流量从哪里来，以及读者来到网站以后真正做了什么。
第三，学习一点基本的分析工具。
你不需要成为数据科学家。
只要弄明白 landing page、engagement time、traffic source、returning visitor 这些基本概念，就已经很有帮助。
第四，写你自己真正正在学习的东西。
你自己的经历，很可能对另一个人有帮助。
最后：
第五，把 AI 当成一个思考伙伴，而不仅仅是一个内容机器。
问它问题。
挑战它的结论。
把你的数据拿给它看。
让它解释你不明白的东西。
但是，最后做决定的人，还是你自己。
故事还没有结束
我不知道六个月以后 AI123.ca 会是什么样子。
也许这个新的每日读者基础会继续增长。
也许它会稳定下来。
也许又会出现一次意想不到的流量高峰。
也许流量还会再次下降。
互联网就是这样。
但是，在观察这个小小的网站成长的过程中，我学到了一个道理。
真正的成功，并不只是看到屏幕上的一个大数字。
真正的成功，是让自己成为一个更好的观察者。
我创建 AI123.ca，是因为我想探索人工智能，并把自己学到的东西分享给读者。
但是走到今天，这个网站本身也变成了我的另一个实验。
我在学习人工智能。
我在学习写博客。
我在学习了解读者。
而在 Google Analytics 和我的 AI companion 的帮助下，我也在学习一件事情：
学会真正地观察。
现在，这已经足够了。
我的 AI123.ca 旅程，还在继续。
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