Divide and Rule: Types of Segmentation in Web Anaytics

In order to analyze traffic to your website you need to segment it. A lot of times, possibilities for segmentation will depend on the analytics system you use and the data you track. In this article, I will outline how you can create segments using the data commonly provided by analytics software. I will also evaluate, to what extent you can make use of the created segments.

First group of segments: user-based

Geo and tech characteristics of users belong to this group. If you have a way to find out the gender or the age of your users (registration, dialog windows), you can segment visitors even more granularly.

user-based-segments
User-based segments: by device type.

Geo-segmentation includes segmenting by cities, regions, countries as well as browser languages.

Geo-data is usually collected based on user IP. Although this information seems to be interesting (often presented in form of maps), it is only relevant if you offer a location-based product/service (e.g. only available in a few cities) or if your website is localized for several countries and you want to make sure that international users are routed to the correct country site.

Tech segments are based, for example, on device type or browser name and version, as well on as the user domain. From my experience, these parameters are not going to be used extremely often either. If you get a significant number of visitors from a certain device or a certain browser,  you should better make sure that your site works on them. Other than that, it useful to group sessions where an HTTP or a JavaScript error occurred (if an error is recurring and you can reproduce it, a fix is needed).  Additionally, IP address or user domain name are used to exclude internal traffic (i.e. the traffic from your company).

Second group of segments: content-based

As can be guessed from the name, such segments relate to the content of the site. In other words, by applying this segmentation, you can see what happens on certain parts of your website or on groups of pages. If set correctly, this gives a structured and precise insight into the website performance.

Some ways to apply this segmentation are:

  • By product (if you have a few products, e.g. 1-5)
  • By brand or by product type (if your website showcases a lot of products)
  • By department/division (if this is how your site is organized)
  • By content for different customer groups (gender, age, type of customer: business or private…)
  • By site component (forms, product description, FAQ…)
  • By country site (if the data is not split in the database)

This is by no means an exhaustive list. By looking at your site, you may come up with a more suitable (for you) way to segment content. Then you can use the grouping, for instance, to compare how different products perform or to create a product ranking by popularity/engagement.

Third group of segments: traffic-based

This type of segments will contain general break-up of traffic, without precise description of particular users. The most common segments will include: by traffic source, by referring domain, by time of visit (day of the week, hour).

New vs repeat/returning visitors segment is based on the cookie set on a visitor’s device (however, as a growing number of visitors do not accept cookies or delete them regularly, the data from this segmentation should be treated as an approximation).

Such segments are extremely useful in order to analyze how the performance changes depending on the type traffic flowing to the site. What is more,  traffic type will most probably have a larger impact on performance rather than user-based characteristics,

Fourth group of segments: interaction based

This is a large group of segment that describes how visitors interact with the site.

You can create segments by number of page views per visit (page depth), by bounce rate, by time on site, etc. For the majority of these parameters, you will need to come up data ranges, e.g. number of page views per visit may be split into the following segments: 1 view, 2-3 views, 4-6 views, 7 or more views. Besides, you can include events – such as forms submission,

This type of segmentation will enable you to start the analysis “from the other end”, e.g. what are the traffic sources or pages in best performing segments.

As you can see, applying correct segmentation to site traffic will provide you not only with more data but also with more insights into what influences the amount of traffic and its performance over time. But what if you feel that besides segmenting you need to group and generalize traffic somehow? This would be a clear case for cohort analysis, which I may talk about in one of the next posts.

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Men Shop on Mars, Women Shop on Venus: Gender in E-Commerce

This post is a recap of the 20th E-Commerce Forum at Flagbit in Karlsruhe that was dedicated to the topic of gender in e-commerce.

gender in e-commerce
Source: Unsplash

The presenter, Astrid Wunsch, spoke about the gender-related differences in buying behavior that any online-shop owner needs to consider. The presentation was followed by a lively discussion and experience sharing. Summarizing the main points, the following recommendations can be given.

  • Consider who your audience is. Even though your products will mostly define who your target customers are (make-up products as a female domain, vs. men shopping for electronic goods), do not simply make assumptions without checking your customer data. For example, on the website selling vacuum cleaners, 2/3 of buyers were female. Also consider cross-buying, e.g. women buying clothing for their husbands. On a voucher aggregator platform, one of the most popular vouchers selected by men was that of a perfume shop.
  • Adjust the buying process in your shop. Men are normally result-oriented and know what kind of product they want. They prefer clear-structured shops with search and filter functions and few distractions. Women, on the contrary, like looking around and enjoy the buying experience itself. Their buying decision takes longer, as they need to consider a number of alternatives first. Women also like to be advised in the buying process,  so it is a good idea to set up a live chat or a customer hotline.
  • Think about product presentation. Male users need technical data and product details. They prefer to see the product in 3-dimensional view, isolated from context or other products. They also respond positively to product videos. Female customers pay more attention to colors and patterns of a product page. They also like to see products in real-life context, surrounded by other objects and performing their function. Women get more influenced by stories and testimonials around products, as well as positive social media signals.

In Europe, buying power of women is constantly increasing, and besides, women influence over two thirds of all buying decisions. Nevertheless, most online shops and websites in general still appeal to and made for a male audience. Maybe it is time to start thinking in the other direction?

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