Enhancing CX/UX Research with Synthetic Users: The Future of Design Testing

Today, user research is a fundamental part of designing digital experiences. It helps us better understand users’ needs, behaviors, and expectations to create more intuitive and functional products. However, traditional research methods, such as interviews and usability testing, are often costly, time-consuming, and difficult to scale. This is where synthetic user research comes into play, an innovation that uses artificial intelligence and autonomous agents to create virtual user profiles and simulate their interactions.

In this article, we explore how synthetic users are changing the way we conduct CX/UX research, their current limitations, and how Making Science is addressing these challenges with its own advanced synthetic user model.

What Are Synthetic Users?

Synthetic users are profiles generated by AI that simulate the characteristics, needs, and behaviors of real users. These profiles can be created automatically, using data and AI algorithms that mimic the diversity and complexity of a real audience. Tools like Delve AI and Synthetic Users allow anyone to generate detailed personas with information about their background, frustrations, goals, and psychological characteristics. Through these platforms, design teams can quickly create profiles representing a diverse sample of users without the need to recruit real individuals.

Advantages of Research with Synthetic Users

Scalability and Efficiency The main advantage of synthetic users is their ability to simulate multiple profiles in a short period. By eliminating the need to manage and coordinate groups of real users, design teams can quickly obtain relevant data from a wide variety of people. This makes research much more scalable and efficient, especially when fast results are needed.

Cost Reduction Recruiting real users, conducting interviews, and performing usability testing can be costly and logistically challenging. With synthetic users, these costs are significantly reduced, as there is no need to compensate participants or manage the logistical aspects of research sessions.

Simulating Controlled Scenarios With synthetic users, teams can simulate very specific scenarios and observe how virtual users interact with a product or service. This flexibility allows for usability testing with different types of users in controlled contexts, making it easier to identify problems before launching a product to the market.

Limitations of Synthetic Users

While synthetic users offer great advantages, they are not a complete solution. There are some important limitations to consider:

Lack of Real Empathy Although synthetic profiles can be incredibly detailed, they cannot replace genuine interaction with real users. Interviews and usability testing provide an emotional connection that helps designers deeply understand the motivations, friction points, and emotions behind user behavior. Synthetic users, no matter how sophisticated, lack the human complexity necessary to simulate authentic emotional experiences.

Superficially Accurate Simulations Synthetic users can provide valuable feedback, but they often lack the complexity that real users can provide. The insights generated by AI may be overly optimistic or simplistic, making it necessary to complement them with real-world research to obtain a more comprehensive view.

Reliance on Previous Data Synthetic users rely on previous data to create profiles, meaning their accuracy depends on the quality of that data. If this information is limited or outdated, the resulting profiles and insights may not reflect actual user behavior.

How Making Science is Redefining Synthetic Users

Understanding these limitations, at Making Science we have developed our own advanced synthetic user model designed to overcome many of these challenges. Unlike conventional solutions that focus mainly on demographic data, our model integrates multiple layers of information, including:

Market behavior
Technological context
Socioeconomic aspects
Behavioral trends
Customer journey insights

Additionally, we enrich our model with sectorial and brand insights—incorporating information about the sector, competitive landscape, and brand-specific elements such as product offerings, pricing strategies, and positioning. This approach allows us to simulate more realistic user experiences that account for industry-specific dynamics and brand perception.

But what truly sets our model apart is its ability to incorporate real data from various sources, such as user interviews, focus groups, and client reports. It can even be enriched with call center data, ensuring a deeper and more authentic understanding of user behavior.

Moreover, our model excels in early-stage validation. It can test redesign proposals at the sketch or wireframe stage, providing actionable insights to determine whether the new approach improves the user experience. This capability accelerates decision-making and enhances design outcomes, helping teams iterate with greater confidence.

Use Cases in CX/UX Research

While synthetic users should not fully replace real-user research, they have an important role in the lifecycle of CX/UX research. Some of the most relevant use cases include:

Exploratory Research: Synthetic users are ideal for the early stages of research, where the goal is to explore potential issues and generate hypotheses. By creating synthetic personas based on demographic and behavioral data, designers can gain an initial understanding of their audience before diving into more costly and complex studies.

Concept and Prototype Testing: Before conducting tests with real users, design teams can use synthetic users to evaluate design ideas, prototypes, and features. This allows for quick validation of concepts and adjustments before rolling out prototypes to real users.

Feature Validation: Synthetic users can be used to validate new features or changes in a product. Through simulations, designers can observe how different user segments interact with the product and whether the new features meet their needs.

AI and the Validation of Interface Affordance One of the most exciting advancements that AI already enables is the validation of the affordance of our interfaces. Simply put, affordance refers to an interface’s ability to indicate how an element should be used intuitively. AI can analyse and predict how users will interact with certain interface elements, helping us improve accessibility, clarity, and usability in our designs. Thanks to simulations with synthetic users, we can observe and adjust interactions before implementing changes in a real product, allowing us to optimise the user experience more efficiently.

The Future of Synthetic Users in CX/UX Research

The field of synthetic user research continues to evolve. At Making Science, our advanced synthetic user model not only integrates complex layers of demographic and behavioral data but also enriches profiles with real user feedback from interviews, focus groups, client reports, call center interactions, and sector-specific insights. This unique approach allows for more nuanced and realistic simulations.

Additionally, our model’s ability to test wireframes and sketches sets it apart, enabling early detection of design challenges and quicker iteration cycles.

However, it is essential to remember that research with real users should always be the foundation of any design strategy. Synthetic users are a powerful tool to complement research, but they should not replace a deep analysis of users’ needs, expectations, and emotions.

TL;DR

Synthetic user research is opening up new opportunities for design and product development teams. While it doesn’t replace real-user work, it provides a scalable and cost-effective alternative to obtain preliminary insights and validate ideas quickly. The key is knowing when and how to use this technology effectively, integrating it into a broader and balanced research approach.

At Making Science, we support our clients in implementing these innovative technologies to improve their user research processes. Our proprietary synthetic user model stands out by integrating both demographic insights and real user data, even from call centers, and enriching the analysis with sector-specific and brand insights. Additionally, we validate redesign concepts at the wireframe stage, optimsing user experiences from the earliest phases. The future of CX/UX research is promising, and we are ready to lead this change.

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Trends that are (already) revolutionising interaction with mobile devices

It is clear that with the constant technological evolution we are experiencing and the vast options that exist today (and those to come), there are significant challenges for user experience and user interface designers in the immediate future. There is a clear tendency to simplify traditional graphical interfaces more and more. But, with this commitment to a simple design, there has come the point where we cannot simplify them any further.

On the other hand, with today’s fast pace of life, there is a tendency to make interaction with devices more and more organic, without the need to take your mobile out of your pocket.

Although some of these technologies have already been around for some time and are well known to everyone, today I will tell you in this post about the trends in mobile interaction that will explode in the coming years.

Voice interaction

It is the most widely known and applied and is currently the primary trend because it allows users to interact while performing other tasks, improving productivity. Voice interaction will enable us to search and obtain information, make notes, and even play audiovisual content through interfaces such as Siri, Cortana, and Alexa. However, there are still many options to explore!

Most smartphones and new generation devices include the technology necessary for their use. It becomes a unique challenge for UX designers because it is essential to design a user-friendly, intuitive and practical experience that is not based on “classic” visual and touch interfaces.

The adoption rate of this technology is expected to reach 80% of users in the next five years.

Gesture recognition

Anyone who watches futuristic action or science fiction films can find characters interacting through gestures with holographic devices, operating interfaces and interacting futuristic devices. Well, although perhaps not in such an eye-catching way, this technology is already on its way.

Gesture recognition technology can achieve much more natural interactions than classic text and touchscreen interaction, in a very intuitive way, with reduced hardware requirements (one integrated video camera) and fully customisable to associate actions or tasks with static and dynamic gestures.

Gaze recognition

This technology is also based on recognising movements, in this case, and opens the door to interfaces outside a conventional screen, moving into virtual reality (VR) or augmented reality (AR).

Although this change will not happen in a short time, and the transition will be gradual, interface designers need to be familiar with new 3D imaging techniques to drive the evolution toward augmented and virtual reality increasingly. It shares excellent advantages with voice interaction, as it is also customisable, user-friendly, convenient in situations where hands are busy, and highly useful for users with specific disabilities.

This technology will be available “on the street” in the medium term. However, these interactions require additional hardware, such as head-mounted devices like Oculus and HoloLens, glasses, or even contact lenses. “Smart” lenses, such as Mojo Vision lenses, can recognise all eye movements required for interaction, using movement patterns pre-set customisations. Still, they may face limitations for the time being.

Wearables

These devices, whose implementation is advancing by leaps and bounds, offer an increasing variety of types of interaction without the need to take your mobile phone out of your pocket. In the coming years, these devices will become cheaper, more functional and more independent of the smartphone so that they will multiply.

According to reports from Statista, between 2019 and 2022, the number of these devices is expected to triple to one billion. These devices will base their interaction on all the technologies we have just discussed.

The trends focused on interaction with CONTACTLESS interfaces, to which users will be very attracted; in which it seems that mobile devices will be relegated to the pocket, and designers and developers have to be attentive and adapt to these new needs.

Undoubtedly, brands betting on these trends will be vital in defining and delivering better experiences for their users. Do you want to know more about these trends and how to use them for your users? Email us at info@makingscience.com, and we will help you in your specific case.

The importance of On-boarding in the design of mobile applications

There are currently 3.8 million apps available in the Google Play Store and another 2 million in the Apple Store. Undoubtedly, the creation of mobile applications is clearly an extremely competitive market. In addition to this infinite offer, another even bigger challenge is presented when designing a new app. An average smartphone user uses about 9 apps a day and about 30 a month. Which is equivalent to one third of the apps you have installed on your phone. So most users accumulate applications they do not use at all. In fact, some 25% does not reopen many of their applications after the first time. There are several reasons why one easily loses interest in a mobile application.

That the app does not attract enough interest after its first or second use.
A bad user experience. (With a little intuitive navigation, technical failures, errors, etc.)
The creation of expectations that are not met.
An On-boarding that is too long and complicated.

Designing an application with a high rate of downloads is not enough. The goal is in creating an app that is used on a regular basis. The first step to do this is to put special effort into the design of the application’s Onboarding process.

What is the Onboarding of a mobile application? Onboarding is the key process for the incorporation of a new user to our app. We can find several similarities between an Onboarding and a first date. Both can end in 5 minutes if one transmits a bad impression or crosses a given line, although in the case of applications this can happen after 20 seconds. The consumers of apps nowadays are more impatient and they look for to get hooked from the first moment. With an incessant growth of competition between applications, when creating a new app, it will be crucial for a design and development team to be up to date with user demands. These are some of the practices that a team must carry out when designing the Onboarding of a mobile application:

Get out of the ordinary with animations in the introduction. The period of attention of the user when opening an app for the first time lasts between 5 and 8 seconds so it is important to start with an introduction that goes beyond the normal. A good illustration can help to achieve this and if it is animated, it increases the chances of engaging the user by showing clearly and visually what the app is for and offering a general idea of how it works. It is best to include explanatory text in the animation to improve the understanding for the new user.
Give the user the possibility to learn as they go. The user learns before interacting directly with the app, instead of watching an explanatory video or reading a set of instructions. For more complex apps we can use the approach to include some instructions integrated in the on-boarding process in which the user briefly explores the application.
Make the tutorials optional. There are users who want to know more information about the functions of the application, while others already know the functionality or feel they can learn it on-the-fly. It is convenient to keep both types of users happy by making the Onboarding tutorials optional. For example, including buttons to “start” or “skip” the tutorial.
Do not overdo the coaching marks. Often used to let users quickly know how to navigate through the application, coach marks can help to know how to move better within an application. Even so, its use requires careful consideration to avoid an overloading or confusing screen. You should avoid using these marks for functions that have common sense.
Let the elements breathe. The empty spaces are allies. The apps are seen on small screens. Therefore, it is logical to think that too many elements, either an image or a welcome statement, will create confusion. It is important to effectively use empty spaces and distribute the explanations on several screens. This will make it easier for users to assimilate the instructions.
Offer a demo version of the app if it requires a subscription. Apps consumers today are willing to share personal information, but only if they know what they will get in return. When the app implies that the user creates an account and shares their personal data it is convenient to offer them a demo version to give them a “trial” option before asking them to commit to something else.
Make the tutorials small games. If the application inevitably requires a tutorial, it must be avoided to impede the Onboarding process. One way to do that is to turn it into a mini game, with “rewards.” That the tutorial is a “treasure hunt”, using congratulations at the end, motivates the user to continue with the process if feeling frustrated.

In short, first impressions matter. Especially if it is intended that the designed application does not end up being one of many that are downloaded to be used only once. In a good Onboarding the simplicity and the protagonism of the brand must not be lacking. These are the basic pillars to keep the user connected to our app.

Psychology in digital product design

Design of user experience and Psychology

Nowadays, psychology is a fundamental factor when we talk about Design of user experience, since for product designers, knowing the cognitive and behavioral processes of users allows us to design recognizable, usable and differentiating contexts. Different psychological foundations are included in a digital hyperconnection era in which designers seek differential value by knowing direct and indirect factors related to our discipline. In this sense, psychology plays a fundamental role in the perception and behavior of the user. One of the maxims of user experience design is that the design passes from subjectivity to objectivity and this is achieved thanks to the endorsement of the data, of working with results and of the full knowledge of the behavior of the users to make decisions of design. Next, we show you different psychological foundations that allow users to perceive sensations such as ease of use, recognition, simplicity, usability, differentiation, etc.

Von Restorff Effect

The Von Restorff effect determines how, compared to several similar objects, the one that differs from the rest will suppose a greater degree of latency with the user. In other words: the different components generate an isolation effect by which it tends to be remembered. Techniques such as making an aesthetic treatment differentiating between components of the same type, isolating those with a greater degree of strategic importance and providing them with a design aspect.

Here we see one of the many examples that we have today at Apple.

Serial position effect Also known as the effect of primacy and recent effect, determines how the user is prone to store in the long-term memory (episodic memory) those elements that lead or culminate a series, remembering them better and for longer. This principle is basic for the ordering of navigation menus: it reserves the first and last positions for the sections with the greatest strategic importance.

Instagram is a good example. The first element is Home (People) and the last element is Profile (You). The most important and core parts of the use of the application.

Hick’s Law: “The time it takes to make a decision increases as the number of options increases” So the time it takes a user to make a decision increases the more options you have included, the user tries to contemplate all the possible options and what it entails and then takes the one that they consider the best option.

Another of the real examples is the Airbnb website, where the cognitive load is reduced to limits to facilitate the decision-making process, helping and guiding the user in the process so as not to work on the memory of actions but in the recognition of the actions.

How to do UX design driven by DATA

Today the consumption of digital products is growing exponentially, requiring companies to meet user demands is a priority task. This is one of the big reasons why design processes are changing; Design is no longer understood as a discipline subject to mere aesthetic criteria, since the functional and experience principles prevail over it. The first steps when designing a digital product begin with deepening the knowledge and understanding of our users, to finally empathize with the user and anticipate their needs and motivations.

Almost all the analysis tools (Google Analytics, Webtrends, Clicktale, etc.) provide quantitative data: where does your traffic come from? What did they visit? What information is relevant? In what process did they fall? ? Are they new or repeat users? What is the conversion rate? Much more complicated is obtaining information from the qualitative data that will give us information on how and why something happens. To obtain a qualified analysis, we will have to study both types of data and relate them in order to interpret them and thus obtain the broadest possible perspective.

How do we measure the behavior of users? There are two kinds of data that we can use:

The quantitative data, which are obtained by a deductive method and are characterized by being objective and numerical in nature. In practice, it is based on quantifying attitudes, opinions and behaviors.
On the other hand, the qualitative data come from inductive techniques, and their nature is subjective and descriptive. It consists of understanding the reasons and motivations of the users from their particular interactions with the website.

A very specific example, for a specific need, is the use of Card sorting, which will help us to validate the understanding of the terminology used in the navigation of a product; these data are usually represented in “similarity matrices” or in “dendrograms” they show how the users tested relate content.

Regarding the quantitative data part, we can look at the traffic of a page, the bounce rate, the route that a user follows to find the information or what type of information a user or another seeks to detect content problems of the page. When structuring the content of a page, it is necessary to analyze which is the most relevant information for the users and which are the interaction data of the users with the elements. This interaction data provides help to understand the movement of these users by a page (scroll maps, hover maps and click maps)

Another of the most used methods for analyzing the structure of a web are the so-called “eye-tracking” though this technique is currently being replaced by AI tools; these tools generate hypotheses of vision patterns that users follow when entering a web. Observing this data we can decide where and how to place each element according to the desired objective. Designing from data strengthens innovative thinking, allows us to take the leap to the next level from solid pillars that backup our design decision making. There is no single model or methodology since each starting point is different and that leads us to use different techniques and resources depending on the particular nature of the website.All this is a small part of the ways in which we use the data when designing to achieve an increase in empathy with the user.