Two Types of Online Users: Simplifying the Segmentation

Below I will describe a simple approach to customer segmentation online, based largely on behavioral characteristics.

There are numerous approaches to customer segmentation, some of which include a lot of hard and soft factors and fracture the customer base down to “a segment of one”. However, this micro-marketing is hard to apply in practice: modern online marketing is largely data-driven and the problem is rather to generalize and structure the massive amounts of user data and to incorporate it in simple procedures that you can actually manage and apply.

Below I will describe a simple approach to customer segmentation online, based largely on behavioral characteristics. All users can be subdivided into two groups. There is empirical data by Yandex proving the existence of these two user types, as well as some surveys  such as the one by Novomind  introducing the subdivision of online users/buyers into two main types.

Let us see how the theory can be applied to understanding the user behavior and conversion on a website.

Segment 1: “Experimenters”

Type 1 users, “experimenters”  or “synthetical” type are driven by emotions rather than reason.

  • They tend to “skim” through the page or read it “diagonally” paying attention to the parts that stand out or create a structural break in the page.
  • They are more likely to click on a CTA that is three-dimensional, large or made in contrasting colors.
  • They seldom read the text attentively and are not moved by detailed explanations.
  • If offered a choice of products, they make their decisions rather quickly without much scrolling and clicking, though having a lot of choice is important for them.
  • They tend to break off if prompted to type in extra data, or if forced to do extra clicks.
  • They leave the page rather quickly if they do not find what they want immediately.
  • They are often on the lookout for new, innovative or exclusive products.
  • They are prone to do spontaneous purchases if offered a good deal on the spot.
  • They seldom make repeat purchases and have less customer loyalty to an online shop.
  • These users are slightly more likely to be male or younger users.

Segment 2: “Readers”

Type 2 users, “readers” or “analytical” type tend to be more consistent and methodical when navigating a page.

  • They normally navigate the page “top to bottom” thus paying attention to less “visible” elements
  • They make less spontaneous clicks.
  • They react to CTA’s that match the background design of the page, as this makes them more “trustworthy”.
  • They tend to look thoroughly through the website and need time to make a final purchase decision.
  • They get irritated if the website lacks a clear structure or if there is too little information about the products or services.
  • They often  break off the buying process if feeling insecure about their personal data or feel pressed for decision (“limited offer, buy now!”).
  • If satisfied with service and products, they are likely to return and even become permanent customers.
  • These users are slightly more likely to be female or older users.

Implications of the Segmentation

Having in mind these two customer types helps to explain why the same conversion optimization measures yield completely different if not contradictory results when implemented on different websites (as their customer base may predominately have users of type 1 or type 2).

While the first user type require interactivity, large print and colors to attract their attention and reacts negatively to the informational overload, the second type, on the contrary, require clear and detailed information and dismiss anything that seems suspicious to them or resembles advertising.

If one is not quite sure what type of users a website has or if there seems to be a good mixture of both, balancing off the interests of both groups (e.g. additional information is easy to find, but can as well be skipped through) or even designing several types of interfaces for different landing pages may serve as a solution.

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Author: Elena

I acquired a BA degree in International Business with a specialization in Marketing from Nuremberg Technical School and a parallel degree from Leeds Metropolitan University. In 2013-2014, I worked in the field of performance and conversion optimization with an IT company and then was employed in content marketing. In 2016, I went back to working with Web Analytics and gained additional experience in project management. During this time, I received an Award of Achievement in Digital Analytics from the University of British Columbia (Canada). Currently, I am employed in Online Marketing. My areas of specialization include online marketing strategy, content creation, web analytics, conversion optimization and usability.

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