Are we segmenting and taking advantage of this information?
Posted: Thu Dec 05, 2024 4:27 am
Remember also that in Analytics you can apply segments, and analyse, for example, where people who end up viewing certain pages on the website come from. Wait, let's give an example.
3.4.- Example: Beyond keyword capture analysis in SEO
We have two landing pages that attract 60% of web traffic, with an acceptable bounce rate within the average of the website and in a positive trend (decreasing) thanks to on-page improvements made.
Partly yes, but qualitative analysis can be much more in-depth. Here are some tips.
In the Google Analytics dashboard that I shared with you, you can apply dynamic segments. Segments allow us to include a greater degree of context in our reports and to be able to compare behaviors on an individual basis.
If we have identified desirable user behaviours within an e-commerce site, we can segment and analyse them in detail. Let's imagine that we have an integrated chat and that we have identified that users who chat have a greater propensity to buy than those who don't. Voila! We have taken the first step.
Now we can create a segment that list of cambodia consumer email defines these users (I won't show you how to do it since it will depend on the platform you use for your chat, although some like Zopim already automatically generate the events necessary to track it from Analytics).
This segment of chatting users can be compared to another segment where this first one is excluded and which we define as “users who do not chat”. If we include these two segments in our panel and analyse them comparatively, we could identify landing pages that attract a higher percentage of chatting users, and therefore have a greater value for the company’s objectives.
If you have a blog, you can apply the same, even if chats are not normally used on blogs. For example, we could analyse it based on “they use the blog’s internal search engine” or “they subscribe to the newsletter” as specific segments. Thus, the reasoning applicable would be the same as in the case of an e-commerce, and we could discover not only the landing pages that attract the most traffic and the adequacy of the content with what was being searched, but also which landing pages participate more in the objectives proportionally. Perhaps a landing page with a slower rate of visits is attracting a greater number of subscribers, and therefore we should try to boost the SEO strategy associated with that landing page (keywords and internal article structure). Don’t you think so.
3.4.- Example: Beyond keyword capture analysis in SEO
We have two landing pages that attract 60% of web traffic, with an acceptable bounce rate within the average of the website and in a positive trend (decreasing) thanks to on-page improvements made.
Partly yes, but qualitative analysis can be much more in-depth. Here are some tips.
In the Google Analytics dashboard that I shared with you, you can apply dynamic segments. Segments allow us to include a greater degree of context in our reports and to be able to compare behaviors on an individual basis.
If we have identified desirable user behaviours within an e-commerce site, we can segment and analyse them in detail. Let's imagine that we have an integrated chat and that we have identified that users who chat have a greater propensity to buy than those who don't. Voila! We have taken the first step.
Now we can create a segment that list of cambodia consumer email defines these users (I won't show you how to do it since it will depend on the platform you use for your chat, although some like Zopim already automatically generate the events necessary to track it from Analytics).
This segment of chatting users can be compared to another segment where this first one is excluded and which we define as “users who do not chat”. If we include these two segments in our panel and analyse them comparatively, we could identify landing pages that attract a higher percentage of chatting users, and therefore have a greater value for the company’s objectives.
If you have a blog, you can apply the same, even if chats are not normally used on blogs. For example, we could analyse it based on “they use the blog’s internal search engine” or “they subscribe to the newsletter” as specific segments. Thus, the reasoning applicable would be the same as in the case of an e-commerce, and we could discover not only the landing pages that attract the most traffic and the adequacy of the content with what was being searched, but also which landing pages participate more in the objectives proportionally. Perhaps a landing page with a slower rate of visits is attracting a greater number of subscribers, and therefore we should try to boost the SEO strategy associated with that landing page (keywords and internal article structure). Don’t you think so.