Three patterns of how users behave on the web

Lena Pietsch • 15.04.2021
Lena Pietsch

Psychology has taught us that behavioral intention has the biggest impact on people's behavior. Whether users decide in favor of or against our products depends on these intentions. Most online behavior patterns, according to studies, can be divided into three groups.

You have to recognise these user behavior intentions

  • Interaction Patterns
  • Information-Seeking
  • IA Development

In reality, there are countless behavioral intentions that can each lead to many more actual behaviors. They are so numerous that managing each one individually would keep us UX specialists eternally busy. To avoid being completely overwhelmed in our daily doing, we need to organize these behavioral intentions into categories. Ideally, these should span such that the majority of intentions can be clearly assigned and identified. Here we speak of “intentions of use” as a more concrete term in the context of digital products, because the behavior is expressed in the use of the product, regardless of its type.

Studies reveal user behavior patterns

I discovered three fascinating studies while attempting to categorize the various intentions of use. Even though some of these research results are older than 22 years, the lessons they contain are still applicable today, and are still supported by recent studies. Upon closer look, I discovered a lot of unrealized potential in the research which could be useful to us in our day-to-day work.

An article on "Behavioral Patterns and User Expectations" in the context of information-seeking behavior was published by Nielsen Norman Group in May 2020. An internal study served as the foundation for that article. This study examined how information-seeking behavior has changed over the past 20 years, and replicated a Xerox-PARC study from 1997.

The only remaining copies of the Xerox-PARC study documents are online as scans. Inconvenient, but incredibly captivating. In particular, the methodological taxonomies are fascinating. They discuss the strategies people use on the Internet to accomplish their goals.

Ein Laptop steht auf einem Holztisch, daneben eine Tasse, verstreute Dokumente und ein aufgeschlagenes Notizbuch.

Taxonomy of the University of Toronto (1998)

  • Explore. General search for information. The search is not triggered by a specific goal.
  • Monitor. Repeated visits to specific websites to update information. The search is not triggered by a specific goal; it is a routine behavior.
  • Find. Searching for a specific fact/document/information. The search is triggered by a goal.
  • Collect. Search for multiple pieces of information. The searcher is open to any answer, not looking for a specific one. The search is steered toward a goal.

It wasn't until 2001, four years after the study was conducted, that Xerox-PARC researchers published their findings, referring to another study conducted by the University of Toronto in 1998. Upon closer examination, I noticed that this study came to similar conclusions. Only the categories were named differently. The scientists were able to identify four so-called "modes of scanning". The descriptions of these modes are similar to those of categories from the Xerox-PARC study.

Taxonomy of the Xerox PARC study (1997)

  • Undirected Viewing. Users participate in an activity without any predetermined objectives. They comb through enormous amounts of information from various sources during this process, but they are only ever able to retain small bits of knowledge. This strategy helps them get a quick, general overview.
  • Conditioned viewing. Users can already define a particular area of interest. They utilise a general framework, even if the goal is not yet precise.
  • Informal Search. Users research the topic in greater depth. A specific topic or subject area already defines their intended course of action. To be able to decide in the next step, they want to strengthen their knowledge or look for a comparison.
  • Formal Search. Users can already specify a specific informational or practical objective. They move methodically and adhere to a defined structure. They also place a high value on accuracy and quality. The decision-making process is the focus of the information search.

As was already mentioned, the Xerox-PARC study's research design was repeated under the current circumstances. The study design was to be altered as little as possible to allow for future comparisons. Despite a 22-year gap between the two studies, their findings were remarkably similar. The quantitative distribution of the various categories showed only slight variations.

Behavioral patterns compared

We have compiled for you all the key facts from the three studies in the following table. Comparing the relevant categories in each case, it becomes apparent that the overlaps in the findings are significant. These served as the foundation for the three categories we created for our own work.

Comparison of findings from the studies by Xerox-PARC, Nielson Norman, and the University of Toronto

Synthesis of three »intentions of use« categories

We have identified three categories that correspond to what we know from practice:

  • Act. The website is used with a specific goal in mind. Users typically have no trouble outlining their desired outcomes. They move forward in a focused and organized way. They want to get there as soon as possible and without detours, within the limits of their knowledge and skills. Users anticipate a clear outcome.
  • Understand. As with the above, there is a primary objective in play. However, users are initially unable to name a specific result they expect. Their actions are marked by a methodical approach that could take some time. The users' goals are to gather as much information as they can, incorporate it into their mental models, and contrast the results with other data. They expect the website to advance their understanding.
  • Explore. Users struggle to articulate their motivations for using the website. They typically consume a lot of varying content in a brief amount of time. This behavior is motivated by objectives like inspiration, amusement, and diversion. They are seeking an experience.

Which questions to use when classifying the intentions of your users

These three categories, in our experience, correspond to the majority of practical use cases. We have combined the results of the three studies using a various dimensions to further emphasize the distinctions between categories. Thanks to this matrix, you should find it easier to assign your use case to one of the three categories. Further, it can assist you in incorporating the three categories of Act, Understand, and Explore into your future day-to-day work.

We have selected the following dimensions for this:

  • Want. What actual need is driving this behavior?
  • Goal. How precisely can users describe their goals for taking action?
  • Focus. What is the action's main focus? What is the key point?
  • Time. How long are users prepared to spend completing the task?
  • Manner. Do users adhere to a specific structure?

Not all individual parameters have to match exactly. Though it should be obvious from the sum of all dimensions whether the intention of use is Act, Understand, or Explore.

Dimensions for the classification of behavioural intentions

Research questions for the future

You might have noticed that we left out two other categories from the comparison table. On one hand, we have "Monitor",which, according to a recent study from 2019, could no longer be found. However, we firmly doubt that this category is irrelevant today. Especially in the modern era, we are practically conditioned to monitor information. One thinks of the news feeds featuring the most recent Covid-19 statistics. Or the tracking of stock prices. Therefore, it is without a doubt that we will look more closely at this category in the future. 

On the other hand, we have “Notified”, which made its debut in the new study as a new category. Our analysis indicates, however, that this does not represent a conventional intention of use. This is due to the fact that, unlike the other categories, it serves more as an activation mechanism and does not permit us to attribute an intention. Instead, the context of this activation is what shapes the intention. For instance, a push notification may alert us that additional tickets are available for a concert that has already sold out. We are much more likely to have the intention of use “Act” or“Understand” if we click on this push notification to purchase a ticket. The displaying, or even clicking, of the push notification clearly falls outside the definition for an intention of use.

Metal-framed glasses with round lenses are flipped upside down on an open notebook with black handwritten notes that span the entire double-page spread.

Our collection of broad categories for intentions of use isn't exhaustive, though. This is already evident in the fact that the“information-seeking” behavior has been the central focus of all three studies. We must assume that our system of categories still has gaps, because there are other “information behaviors”, such as the use of tools, information sharing, and others. However, we have found that these three categories have worked well in practice thus far, and we therefore urge you to consider using them. 

Can you think of an application that doesn't fit into any of the three intention of use categories?

The categories provide the framework for your information architecture

With these three categories, we provide you with a way to classify the intentions and goals of your users. Once everything has been elaborated and clustered, it becomes possible to make specific recommendations for action. To achieve this, we'll explain how you can can specifically address these various intentions of use and their dimensions.

Our insights straight to your inbox