AI-Driven UX Goes Beyond Automation

AI plays a significant role in automating business processes and workflow operations. However, there is much more to that story when it comes to an AI-powered user experience.

One of the conventional approaches to testing usability and user satisfaction on E-commerce platforms has always been A/B testing. A/B tests or split tests involve creating two or more versions of the same web page and showing each version to different groups of visitors. The versions are then critically analyzed and compared to find which design model gives the optimal results.

The problem with such an approach is that it gives you a very static user experience model. In other words, you are only meeting the majority of customers’ demands without considering individual preferences and anticipating behavioral changes. There is nothing to reflect that each customer and visit is unique.

Automated UX solves these problems by creating a dynamic user experience that actively adjusts to the needs of each customer. The AI-driven design of ntelligent UX “knows” what products and services to recommend, which content to show, which emails to send, and even the greeting message to show each visitor or customer. Personalization is a critical factor in the success of modern marketing techniques; in fact, 90% of leading marketers agree that personalization contributes profoundly to profitability.

Automated Analytics Through Intelligent UX

Besides personalization, intelligent UX also provides the business with powerful insights into the market dynamics and the brand’s performance. You’re probably already familiar with the concept of Big Data and robust analytics systems. These systems entail collecting and thoroughly analyzing vast volumes of data to draw meaningful conclusions from data patterns.

Data collected from customer interactions can be integrated into automated KPIs – for example, an experienced user who is more familiar with the application might use a complex user interface. In contrast, a less-experienced user will require a simple and intuitive interface to allow him to learn how to use the application without frustration.

Intelligent UX provides a greater scope of data from a multitude of unique customer engagement scenarios. Marketing automation involves three crucial strategies – generating qualified leads, converting those leads, and extending the lifetime value of the customers. There are four significant indicators to consider when automating your marketing process:

•  Acquisition indicators
•  Engagement indicators
•  Conversion indicators
•  Retention indicators

Automated KPIs rate leads generation, their conversion rates, and the value of qualified leads through intelligent scoring metrics. The most attractive benefit of using AI-powered marketing tools is making predictive analysis. You can leverage the power of AI-driven UX and data analytics to adjusts your business model and marketing efforts based on precise predictions of consumer behavior and market trends. A case in point is a chatbox experience, where the use of AI-driven UX would allow us to anticipate erroneous or unwarranted responses to ensure a smoother user experience.

Anticipating customer frustration or pain points can be the difference between retaining a customer and losing one completely. You can harness AI to identify when certain user behaviors would indicate that a customer is about to drop off, and surface proactive messaging that can cue the user with customer service support.

AI analytics may soon replace the conventional KPI dashboards. Smart analytics provide the businesses with so much more besides basic information. It’s about creating insights that companies can act on in real-time. AI companies such as Amplero, Gumgum, and many others are already offering marketers with state of the art AI-powered marketing insights and metrics. Such companies provide advertisers with more effective ways of reaching their target audiences and judging their marketing performance through intelligent personalization.

What The Future Holds

Just about every software developer, especially in the E-commerce field, is keen on implementing AI features to improve product usability and UX. And this is not restricted to webpages either, as AI-driven UX is also growing popular in mobile development, particularly in mobile services and apps. Considering that more than half of all internet users access the web via smartphones, focusing on mobile users makes a lot of sense.

Combined with other similar technologies like augmented reality, machine learning, and deep learning, AI algorithms are growing more sophisticated and powerful, leading to faster, more accurate, and more useful, AI-based tools. Web pages, apps, and digital enterprise resources can now identify and support human needs (at least to some degree), which is the core purpose of AI-driven UX.

It’s safe to say that you should expect a lot more from AI-powered UX in the coming years. Intelligent UX will continue to reduce the cognitive load on consumers and ease E-commerce marking efforts.

Creating a Value Statement

Many clients aren’t concerned with the specific features and functionality of software at this stage. It’s more important for them to nail down the business requirements that should be based on their vision or goals for the project.

source: scrum.org

One value statement may not cover the needs to be addressed and the business solution for every customer the client wants to serve. If this is the case, they should develop a value statement to target each group of customers. The final set of value statements will describe the functionality and business solution that are required to meet the needs of all users.

Developing the Value Statement into a Business Outcome Hypothesis

The value statement should capture the major goals and functional requirements of the project, but we then go into more detail by using it to create a business outcome hypothesis. This hypothesis has several important functions:

• It states the quantitative and qualitative benefits that the business can expect if the hypothesis is proven to be correct. These benefits may be in terms of users affected, the expected impact on processes, products, services and costs, sales, revenues, etc.
• It defines leading indicators that can be used to help predict the eventual business outcomes. Some examples of leading indicators include the number of users, subscriptions, costs per user, etc.
• It determines nonfunctional requirements, which are features of the software solution not related to its functionality, such as which architecture and infrastructure it uses, how the software is built and updated, network usage and bandwidth, performance, availability, security, backup, stability, capacity, regulatory details, usability, interoperability, costs, configuration, documentation etc.

If you’re new to the idea of using hypotheses in software development, the concept is not so different from the hypotheses you were probably asked to develop as part of high school science class. You’d then carry out an experiment to test this hypothesis.

You can think of a hypothesis as a “prediction” or “best guess” of what the project will achieve.

An example of a basic hypothesis for software development might be something like: “We believe we can reduce our support requests by implementing a chatbot that will instantly answer frequently asked questions. We’ll know this is true when the number of support requests is reduced by X amount.”

We then test this hypothesis in the leanest and quickest way possible to find out early in the development process if the solution currently in development is fit for purpose.

source: scaledagileframework.com

By using this method to define the scope of the project, we avoid adding unnecessary features or focusing on the features themselves rather than the business outcomes.

Other Information Needed Before Development Starts

Developing a business outcome hypothesis is a key concept in agile software development, and it helps us to make sure we’ve defined the full scope of the project before any work starts.

In addition to this formal process, we also capture and discuss other business-related information with the client that may be necessary or helpful for planning development. This may include:

• A detailed description of business process steps
• Definition of user stories and use cases in general
• User personas (with roles in the system)
• Minimal viable product features (the must-have features of the final solution)
• Additional potential features (the nice-to-have features of the final solution)
• Major milestones and deadlines.

By establishing the groundwork and expected business outcomes of your software development project in the beginning, you won’t just have a more seamless experience. This is how you’ll get the results you want to see. 

What is a User Persona?

User personas are an integral part of agile development and user-centered design. They enable the development team to think about the needs of the actual end users of their product rather than focusing on a set of features without considering if they’re actually wanted and needed.

Creating user personas for your app development company puts a human face on your users, making it easier to create software that suits their needs. Rather than trying to think about how to design for your users as a generic group, you can think about how you can make your app easier for “Bob” to use, or what features will be useful for “Sarah”.

source: Dribble.com

How Creating User Stories Helps the Software Design Process

Your user stories build on your user personas to describe what each user wants from the product so it fulfills their needs.

These user requirements become a list of features that form the basics of your app design and development. Each user story is a short sentence focusing on one aspect of functionality and usually has a “who + what + why” structure. For example: “Anna wants to organize her time so she can be more productive”.

source: Knowledge TRAIN

How to Create User Personas and Stories

As a mobile- and web app development company, we just cannot emphasize this enough: Start by researching your market – the end users who will actually be using your software or app. If there’s an app with similar functionality already out there, look at who is using it and what they’re saying in feedback on app stores.

If you’re developing something completely new, interviews with real people are the best way to gather this kind of intelligence. Concentrate on their needs and challenges rather than your proposed solution. If you work for a web development company, information from analytics and social media is useful too.

This research will give you a good basis for creating user personas based on real people. Some information you might want to include in your personas include:

• • • Name

    • Background (career, educational experience, interests etc.)

    • Job title and responsibilities

    • Knowledge level (about the concept of the app)

    • Context (what are they using the app for?)

    • Environment (where are they using it? E.g. at work or at home)

    • Pain points and challenges

    • Goals and Motivations (what do they want to achieve by using the app?)

Based on our decade of experience with mobile apps, three to five personas are sufficient for most apps and software projects. Once your team is familiar with the personas, you can create user stories based on your earlier research.

The Risks of Not Using Personas

Skipping the important step of creating user personas and stories is a huge risk. Without a clear picture in your mind of who you’re designing and developing for, there is a significant chance you’ll end up creating something that’s not suitable for your users.

Even worse, you could create an app that might work well for you but doesn’t really meet the needs of anyone else.

Using personas and user stories helps to position your product better in the marketplace and ensures you’re creating software that your audience wants and needs.

Google Wave (2009)

In 2009, Google was hot on the need for a new kind of project management with collaboration at its heart. 

But the design was not so hot.

Let’s say that this was the first wave of its attempt to improve collaboration across teams. The result not only bombed, it totally languished. 

This is what the first iteration looked like. 

Never mind the dated design; the problem was that Google failed to “Keep It Simple Stupid.” The platform was much too busy and felt complex — too complex for an individual to even want to try and navigate. 

This unnecessary complexity popped up again in the fact that Google was focusing on too many projects at once. It decided to launch Google Buzz before Google Wave was fully integrated. 

Coupled with its limited user adoption strategy, the project gained zero traction and was an unmitigated disaster. 

Live and learn, right?

Windows 8 (2012)

Three years later, the Windows 8 debacle proved to mobile development companies the power and importance of continuity and consistency. 

One of the prime principles of UI/UX design is to keep a user’s expectations alive. What a user expects, a user should receive — not least because, through your previous iterations, you’ve likely spent time and money educating your users about how your interface works. 

When Microsoft first released Windows 8, it was a clear shot at Apple who was quickly eating up market share. 

First big mistake: Trying to ape another platform’s functionality. 

From here, things got worse. Because Microsoft abandoned their initial interfaces entirely, users were completely unable to find the most basic functions. 

Navigation was a nightmare and these major changes came at the expense of their users’ expectations. 

Anyone using a Windows PC knows that the desktop and the Start menu are the main points from which to operate tasks and access the file system. 

Instead, Windows 8 users were subjected to an OS that was trying to fulfill the duty of two: It was intended to be both click and touch-friendly

The problem was that, in trying to accomplish both, it did neither well. 

First, Windows 8 removed the Start menu and the default Desktop screen, completely pulling the rug out from under users who, over years of loyal and expected use, now had ingrained expectations. 

After the ensuing chaos and uproar, the customer experience was completely diluted. Sure, Microsoft re-introduced the Start button in version 8.1 — but not before many chose to downgrade to Windows 7.

Now, does this mean that interfaces shouldn’t evolve or that visual identity shouldn’t keep up with modern design standards? No. Certainly not. 

But that’s why changes in UI/UX design need to…

• Be incremental
• Keep the main functionality alive, even if the look and feel changes
• Be based on the results of tangible user testing 

The USB

It’s not scientifically proven or anything but, about 50% of the time, USBs are inserted incorrectly. The user sighs, frustrated, then pops it in again, fingers crossed, hoping and praying to the powers that be that this time, it’ll actually stay in. 

We all know how this story ends. 

The USB is a very common tool and we still rely on USB connected devices every single day. 

To this day, we’re never quite sure whether we’ve inserted it right.

This serious design flaw has a pretty simple fix. To understand it, just look to its predecessor: the plug. Sockets and outlets have their own configurations that are visible to the user, neatly indicating how plugs should be inserted. 

Or you could completely eliminate the USB connector once and for all and opt for a design that doesn’t depend on the orientation of the plug. 

Apparently, designers for Apple and Android phones agree: the latter introduced the lightning connector, while Android phones have developed the C-type USB. 

Source: Dignited

Conclusion

UI/UX’s power is the fact that anything, given enough time and thought, is ultimately changeable. 

Sometimes, all it takes is for UX designers to put themselves in their users’ shoes and look at it from their perspective. It’s why the stages of design — such as prototyping or running sprints — is so crucial to the process of good design. 

Avoiding pitfalls is a collaborative process and it calls for iteration. This iteration shouldn’t be avoided. But there is definitely a way to do prototyping right — prototyping for pros. 

Learn more about how to rapidly prototype for software development and bring a sense of business value to your design team.