How Can AI Be Used to Improve User Experience in Mobile Apps?

Beginning Your Journey to Implementing Artificial Intelligence | SoftwareONE Blog

Imagining Artificial Intelligence in situations and use cases where there are a massive number of data in picture makes perfect sense. But what happens when the situation is entirely based on human discretion? Will an artificial intelligence user experience design would also be able to do what AI did to several other industry verticals?

Designing, almost in all its different forms is driven by keeping the human part of process at a much higher ground than the analytical and data driven side. While there are some domains like CAD design or Product Design that leaves some space open for machine learning to enter, when the design form in question is mobile app design, the gap seems to become negligible.

However, Artificial Intelligence, like a number of other industries have found a place in the Mobile App Design vertical as well, giving birth to the concept of artificial intelligence user interface design. A concept that is ought to bring a new level to the relationship between artificial intelligence and customer experience.

While, the answer to whether machine would replace designers is next to impossible, there are ways that the designer community has started taking AI user experience together in their journey to designing memorable mobile apps in multiple ways, like –

  • Getting time-taking manual works like image resizing automated
  • Making designs localized by taking help of AI based translation
  • Bring system consistency between users and products
  • Give insights into which elements are users interacting with, which needs attention

This participation that the deisgning industry is witnessing coming in from the AI driven UI domain is something that is showing to have a huge impact on the industry’s present, while paving the way to a world where AI and the future of design is much better linked.

Now that we have seen the impact that AI carries on Mobile app Design and how it is soon becoming one of the proven tips to enhance mobile app design, the next step is to look at the principles that guide their unison in the domain of designing AI experiences

The Guiding Principles that Combine Mobile App Design with Machine Learning

Develop a Shared Language

Shared Language in Software Development ⋆ Geneca

Elements like user experience review, product vision, and business goals are something that needs to be understood and shared by the complete team. You would only be able to create a meaningful and truly intelligent user experience if the mobile app design and machine learning development methods complement each other through shared concepts and common language. The machine learning experts and user experience designers should come together to develop a common blueprint which includes data pipelines and user interfaces, with the aim to set a blueprint that grounds the team’s product planning with the users’ reality.

Focus on Use Case

Case - Free business icons

The important thing when developing a consumer facing app, as the top software designers would tell you, is not the technology that backs it but the business goal and the user experience that you plan on achieving. And so, it is extremely important that you crystallize the use case. With a separate focus on the use case, you can then put your intricate attention on the user flow, which then allows the team to identify the main points where machine learning can be added to enhance the experience.

A clear understanding of the use case also enable teams of the mobile app design company to determine the right KPI for the development of user experience program, which in turn is aligned with machine learning metrics.

Mix Quantitative and Qualitative Data

Mixed methods in design research. Combining qualitative and quantitative… | by Alison Berent-Spillson | UX Collective

In order to understand the true impact of combining the machine learning solution and user experience design, it is important that both qualitative and quantitative data is considered. You should make use of qualitative research methods like questionnaires, interviews, etc to measure how the users are experiencing your app.

The reason why we are emphasizing on using a combination of quantitative and qualitative data is because when designing a new app, it is possible that you meet unexpected factors that affect machine learning developmant and user experience. Factors like: Effectiveness of feedback loop, ability of data point capturing intention and user behaviour, which are must to know parts of Artificial Intelligence app design can best be answered only after a deep consideration of both the data types.

Bring Your Combined Data to Real Life Setting

How do you make sure that machine learning is actually used to develop comprehensible and fluent user experience? By setting up an end to end solution that shows how machine learning and user experience fit together in real world. An MVP that includes the working data pipeline along with the machine learning models makes it easy to iterate the AI assisted design together and helps in getting a direct feedback from the users via beta or user testing.

When both UX designers and Machine Learning experts of your partnered AI app development company share the understanding of product design issues, iteration is productive and fast. While on the other hand, user experience designers become aware of possibilities that surrounds machine learning: when it can be used to improve the user experience and how.

Be Transparent About Collecting Data

Graph Clipart Statistical Data - Data Collecting Clip Art Png Transparent Png (#113079) - PinClipart

Designing for AI and with it, needs a constant effort and for it to be absolutely on point, it is important that you give a special focus to the data you have collected. It is very important to consider the end user side in this cycle of collect data – convert data into information – iterate design. Tell users that their data is being used to feed the AI and give them the option to alter the collected information in a way that the best context comes through. In addition to giving users the option to change what data is collected by the AI, you should also give them the option to change what the AI learns – to ensure that the predictions are what the users desire.

While these principles that we just saw help in giving some clarity into how the combined AI and UX design should function, let us look at how some of the famous designing and editing tools that are backed by the developers community across the globe are using the technology to offer better mobile app user experience.

Tools That Use Artificial Intelligence for Design

Tailor Brands

Official Brand Guidelines | Tailor Brands

The Tailor Brands logo maker is a famous product used by businesses to get professional logo in a small budget. The AI designs are built upon with your input coming in form of information that would be entered in logo.

Adobe Photoshop

Adobe Photoshop on iPad | Adobe Wiki | Fandom

The Select Subject functionality that Photoshop offers make use of AI for memorizing the shape, and then shifting, changing, and editing them with much ease. The tool works on an internal AI system known as Sensei that enables changing backgroungds by recognizing the different subjects in the image.

Prisma and Deepart

Prisma Photo Editor - Apps on Google Play

Both the famous image editing tools/AI design software make use of artificial intelligence for identify the different aspects of your video and photo and transforming them in a style of your choosing. They give you the option to work around filters and colours among other things.

Let’s Enhance

Image Upscaling with Color & Tone Correction: Let's Enhance 2.0

One of the most frequently arising issues in the designing industry is low quality images. Let’s enhance, powered by AI improves the quality of images using three filters. Anti-JPEF filter converts image to high quality PNG while Boring filter scales up image to around 4 times without any compromise on the image quality. Magic, the third filter allows you to add detailing inside the image. Making Artificial Intelligence a primary part of the Mobile App Design process is something that comes packaged with several add on factors that have to be considered to ensure that that User Interface and User Experience is intact.

And this in turn is not an easy process.

Packaging your app’s user experience with Artificial Intelligence in a way that the whole process gets translated into Artificial Intelligence design patterns calls for a lot of homework, which in itself is heavily dependent on the information that the users provide with consent.

If you are just starting with making your designs smarter, there are some UI patterns that would help you start on the intelligent journey.

A. Criteria Sliders

A number of apps use machine learning algorithms to predict an outcome or pass recommendations. A criteria slider comes in handy here for it helps userss adjust and then fine tune recommendations on the basis of criteria that is meaningful to them. Here, you will have to ensure that the criteria that the users are manipulating with is mapped correctly to data which the machine is using in algorithms.

B. Like and Dislike Button

How to Add Like and Dislike Functionality to Your WordPress Comments | Elegant Themes Blog

A simple like and dislike button help better the user experience that someone shares inside the application. Wwhen you ask users to feed in their experience even through a simple like and dislike button, you give them the option to not just build upon the recommendation system but also give feedback on what they don’t like and why.

C. Confidence Inducing Tips

More often than not, users not just not know how the whole prediction and artificial system works, but also they don’t know how much confidence they can place in the system. When you ask users to feed in their data or answer questions in return of something – better matched clothes choice, next show to follow option, etc. The confidence quotient increases even more when you give users the result and let them approve or disapprove it. Doing this makes your users in charge of the charge – something that automatically instills confidence in the app.

D. Give them an In and Out Option

Not all users would want to feed in data for you to fetch and feed in the artificial intelligent system or even want to take the smart route. So, give them the option to opt in and out of the smart options as and when it suits them. Doing this, they would not just have a more positive outlook towards your app but also, knowing that they have an out option, they will be more willing to add in their data in the future.

Now that you have seen the ways AI powered UX is impacting the app design industry, the guiding principles of designing for AI, tools that are already using AI, and the UI patterns that you should add in your design manifesto to make your users open to the idea of AI, there is only one last thing left to do.

And that last thing is to make AI an active part of your mobile app design process. Let our team of UI/UX designers help you with that.

Improve AI Customer Experience Strategy [2019-2020 Guide]

ai in travel | How Artificial Intelligence is Reforming The Travel Industry

Artificial Intelligence is no longer science fiction. More and more businesses are showing interest in understanding the basic mechanisms of AI and ways to use the technology for enhancing customer engagement and experience.

But, is the technology really effective? And can it really make a difference in upgrading your customer experience strategy?

Let’s find answers in this article – starting from the very basic, i.e, why you should pay attention to Customer experience.

Table of Content

  1. Why Should Businesses Focus on Customer Experience?
  2. Role of AI In Customer Experience
  3. Different Industries Delivering Higher Customer Experience with AI
  4. Future of Artificial Intelligence in Customer Experience
  5. Steps to Use AI for Delivering Better Customer Experience
  6. Other Technologies that are Innovating Customer Experience in 2019 & Beyond
  7. Frequently Asked Questions (FAQs) about AI in Customer Experience

Why Should Businesses Focus on Customer Experience?

How AI Improves Customer Experience: 6 Benefits - Acquire

“Customer Experience is the new battlefield” –  Chris Pemberton, Gartner

With people understanding the difference between User Experience and Customer Experience, the latter term is becoming the key to unlock unparalleled opportunities in the business market. It has become imperative to the process of understanding your customers and planning a marketing strategy using these insights to give a personalized experience. Thus becoming imperative to gain higher success in the marketplace.

And this can be clearly proven from the following statistics:-

Now as we have taken a glance of why to focus on customer experience, let’s jump directly into where AI stands in all of this. What does AI means to the CX world in 2019. Or better say, what are the advantages of using Artificial Intelligence in your Customer Experience strategy.

Role of Artificial Intelligence (AI) in Customer Experience

1. Know Your Customer

5 ways to KYC your customer | Veri5Digital

One of the foremost reasons why you should use AI to improve customer experience strategy is that it serves you with ample real-time user data. It helps you gather and analyze user data in real-time and in this way, enable you to remain familiar with the change in their behavior and expectations.

2. Simplicity, Efficiency, and Productivity

Benefits of Simplicity to Productivity

Another reason for using AI to improve customer experience is that it adds simplicity, efficiency, and productivity to the business processes.

The technology, in the form of Chatbots and self-driving software, automates repetitive processes which means the efforts and time required for performing repetitive tasks cut down to a half.

It also gathers and analyzes the user data in real-time to help you introduce the features and concepts that they want and in the way, they wish to interact with. Moreover, the inclusion of AI in quality assurance helps you to design an innovative mobile application with a higher scope of efficiency and simple structure.

Besides, these AI-powered bots and platforms perform most of the routine work and give the workforce an opportunity to perform other productive tasks.

3. Better Decision Making

Article: Backchannelling leads to better decision-making: Research — People Matters

Artificial Intelligence is also acting as the right companion for business in terms of the decision-making process. The technology looks into the user interaction history as well as the current market trends, which makes it easier for businesses to predict the future. This eventually provides them with clarity of what feature/functionality to introduce in their business solution for gaining huge momentum in the market.

4. Streamline Purchase Process

Streamline your Procurement Process | A Complete Guide - frevvo Blog

In the present scenario, various customers add products into their cart but never proceed due to slow loading, complicated check out process, and more. Artificial Intelligence, in this context, helps in understanding the challenges faced by the customers and deliver a seamless purchase experience – something that helps businesses to lower down app cart abandonment rate.

5. Fraud Detection

4 ways government program managers can solve the fraud Catch-22 -- GCN

One of the prime uses of Artificial intelligence in finance, retail, and other industries, in terms of customer experience, is that it helps in detecting fraud. The technology, using its potential to gather, store and compare user data in real-time, is making it easier to identify any change in the actions of users, and thus, helping with taking a timely preventive measures against frauds.

6. Customer Analytics

Developing a Comprehensive Customer Analytics Strategy - Wharton@Work

Artificial Intelligence is also showing a remarkable significance in the customer data analytics process. The AI-enabled tools and platforms are simplifying the process to gather a heap of user data from different sources and arrange them effectively as per the key factors.

Furthermore, Artificial Intelligence is making it possible to predict the context of user interactions and build better customer engagement strategies using the right use cases of the technology and insights gained from the data quickly and precisely.

7. Self-Service

An A – Z of IT Self-Service Success Tips | Joe The IT Guy

Many customers these days prefer doing everything on their own rather than hiring an agent or taking help from any machine. This is yet another reason why investing in AI is becoming the need of the hour.

Artificial Intelligence, as we already know, provides you with valuable insights about where customers get stuck and what doubts/queries make them connect with your support team. Using these insights, you can provide users with some options or FAQs that give them a feeling that they have found out the solution to their problem without any interaction, or better say, on their own.

8. Visual, Text, and Voice engagement

How to Use Visuals & Imagery to Improve Content Engagement — Setka Editor

AI-powered platforms are also providing the opportunity to deliver optimal customer experience to the targeted audience based upon their voice or facial expressions.

The technology, using Facial recognition and Virtual assistants, is making it easier to get an idea of the users’ emotions and sentiments at any particular time, and identify ways to deliver an instant positive effect to them through offers or refunds, etc. such that businesses gain long-term profits.

9. Predictive Personalized Experience

How Adobe Experience Platform Predictive Audiences Improves Personalized Experiences | by Jaemi Bremner | Adobe Tech Blog | Medium

Last but not least, AI is making it easier for startups and established brands to analyze the user interaction history and predict their next move and hence, use the information gained to provide them with a perfect marketing offer. And in this way, gaining higher customer engagement and profits.

While this is all about how Artificial Intelligence (AI) improves Customer experience in general, let’s figure out what the technology mean to different business verticals and their customer experience efforts in 2020 & beyond.

Different Industries Delivering Higher Customer Experience With AI

1. Retail

Disruption in Retail — AI, Machine Learning & Big Data | by Prannoiy Chandran | Towards Data Science

When talking about industries that AI is transforming, the very first business domain that comes into the limelight is Retail.

The technology, using a heap of transactional data and machine learning, is making it possible to track and analyze purchase history and behavior of customers, which in turn is helping with determining when and what promotional offer/message to be delivered for getting attention of customers and thus, gain higher ROI.

A clear evidence of the impact of AI in retail is that, as per a survey of 400 retail executives by Capgemini, it was highlighted that the technology will save around $340B annually for retailers by the year 2022.

The survey also revealed that the use of Artificial Intelligence in Retailing customer experience has resulted in a 9.4% increase in customer satisfaction and a 5.0% decrease in user churn rate. An example of how brands are focusing on the usage of AI for bettering customer experience can be seen in Nike’s acquisition of Celect for predicting users’ shopping behaviour.

2. Healthcare

10 Top Healthcare IT Certifications - Healthcare Management Degree Guide

AI is transforming healthcare in different ways – with customer experience being on the top.

The technology is proving to be the nervous system of the healthcare user experience ecosystem by making it easier to analyze the patient health history and come up with medical treatment (or surgery) that offers higher chances of success.

It is also helping healthcare organizations in providing the best assistance to every patient in the form of Virtual Nursing assistants and thus, taking care of everything – right form notifying about the medicine intake timings to sharing real-time health data with the corresponding doctors.

An impact of this is that the AI health market is predicted to cross $6.6B by the year 2021, with a CAGR of 40%.

3. Entertainment

At-home & indoor entertainment ideas - The Keyword

AI and its subset, Machine Learning are also leaving no stone unturned in delivering exemplary customer experience in the Entertainment domain. Clear evidence of which is Netflix.

The Entertainment platform is able to get a clear idea of the user behavior, needs, and expectations, and thus, showcase personalized options onto the screen. This is improving the customer retention rate as well as boosting customer loyalty – eventually resulting in higher profits.

To know further about the use of Artificial Intelligence in delivering impeccable customer experience on the Netflix platform, check out this video:-

4. Mobile Banking and Finance

Mobile Banking & Financial App Development Service Provider

Artificial Intelligence is also revamping user experience in mobile banking and finance apps. The technology, in the form of Chatbots, is providing 24×7 assistance to users and helping them in determining the right financial plan for themselves. It is also detecting and lowering down the risk of fraud in the processes – ultimately resulting in better customer engagement and retention rate.

As we have covered in this article so far, Artificial Intelligence is helping industries in revamping customer experience one way or the other. But, will this continue to happen in the future also? Will AI be a part of customer experience in upcoming years?

Let’s look into what is the future of AI in the field of Customer Experience to find definite answers to these questions.

Future of Artificial Intelligence in Customer Experience

Oracle Digital Assistant Version 18.4.3 Introduces Skill Chatbot Capability | The Oracle Mobile Platform Blog

The AI market has grown exponentially in the past few years. Over 1,500 companies including Microsoft, Google, IBM, and Amazon have invested their efforts into developing next gen apps for delivering higher customer experience and it is expected that many more will join the bandwagon. Many more companies will trust the AI’s ability to boost productivity and reduce the time and cost involved – something that can be predicted from the statistics shared below.

The technology will revolutionize the future of the business world and the customer experience in numerous ways, such as:-

  1. It will automate routine work and encourage humans to focus on creative things. It will help pay attention to their vision and not on every minor detail of production.
  2. It will make the business-customer interactions go from ‘one click’ to ‘zero click’ – giving a seamless and timeless experience to the target user base.
  3. AI will also leave a significant impact on connectivity networks. It will encourage the idea of pattern analysis to troubleshoot any problem, pull out important user information from multiple channels to quickly and effectively get an idea of what users need.
  4. Above all, Artificial Intelligence will also put the practice of gaining biased data to an end, eventually resulting in a better quality of information gained.

Now as we have covered what, when and how Artificial Intelligence drives customer experience, it’s the best time to head towards how businesses can integrate this technology to gain better insights and improve customer experience in 2020 and beyond.

Steps to Use AI for Delivering Better Customer Experience

1. Design a Customer Experience (CX) Strategy.

How to Build Customer Experience (CX) Strategy in 2021

Before looking into how AI improves customer experience, it is necessary to have a clear understanding of your CX vision and strategy. So, bring your team on board to discuss your ‘CX-based’ expectations and ways you follow to meet those expectations. And, based on the insights gained, create/update a robust Customer Experience strategy.

2. Plan and Analyze User Journeys

A Beginner's Guide To User Journey Mapping | by Nick Babich | UX Planet

Right from discovery to pre-sales, sales, customer support, and beyond, a user connects with your brand at different touchpoints and platforms. So, invest your time and effort into getting a comprehensive knowledge of all those connecting points, and deliver an AI-based omni-channel customer experience.

3. Have a Clear Understanding of AI solutions

We know ethics should inform AI. But which ethics? | World Economic Forum

The first step of AI project management lies in understanding that the technology can be used in different forms to improve customer experience strategy, such as Recommendation engines, Virtual assistants, Predictive search engines, Computer vision, Sentimental analyzing tools, etc. However, not all can be the right fit for your business needs and expectations.

So, the next step to employ AI in your Customer experience strategy is to determine what all forms of technology can be integrated into your business model.

4. Decide Whether to Create/Buy AI solutions

When Should You Not Invest in AI?

When talking about how to improve customer experience using AI, the next step to consider is to determine whether to integrate AI in your existing application or invest in a pre-made CX/AI solution.

Here, the former one will be the right option for your business, if you have a well-qualified AI expert team in-house or have a partnership with the right AI specialized mobile application development agency. Whereas going with the latter option can be a profitable deal when you have less time to develop an application and the vendor understands your customer issues and has the caliber to focus on critical points.

5. Track and Measure Success

Track these key metrics to measure success | by Deepshikha Yadav | Medium

Lastly, taking the backseat just after incorporating Artificial Intelligence in your CX strategy is not enough. It is imperative to keep a watch on key performance indicators (KPIs) and metrics to track the success ratio of combining Artificial Intelligence (AI) and customer experience. And hence, improve your strategy for a better future.

ALSO READ: Key Metrics to Evaluate Your Chatbot’s Performance

While this is all about how the use of Artificial Intelligence in Customer Experience can bring better outcomes and what steps to consider for implementing it in your strategy, let’s take this conversation further by exploring other possibilities.

Or better say, let’s look into what all other technologies can aid in the process to improve customer experience strategy in 2019-2020 and beyond.

Other Technologies That Are Innovating Customer Experience in 2019-2010 & Beyond

1. Internet of Things (IoT)

Internet Of Things (IoT) Security

In 2019-2020, the number of connected IoT devices will reach 26 billion. Besides, the 5G technology will become more significant in the market with high-speed, lower latency, and other such features.

This will open new doors for universal connectivity – making it possible for the companies to find better insights to understand customer behavior and lifestyle and thus, come with valuable data points and strategies to deliver memorable customer experience.

Or better say, it will help companies to work with facts and not just assumptions about customer needs and expectations, and eventually redefine their Customer experience strategy.

2. Machine Learning

What is the Definition of Machine Learning? | |

With a rise in IoT-based solutions, the volume of data points will also increase gradually. Clear evidence of which is that there will be around 45,000 Exabytes of data volume in the market the year 2020.

Now, with an increase in data volume, the process of gathering, optimizing, and operating data will become a challenge – something that Machine Learning will help with.

Machine learning, with its self-learning algorithms, will enable companies to perform better actions on the data and find new approaches to improve customer experience.

3. Blockchain

Why the Public Versus Private Blockchain Debate Is the Wrong Conversation -

Blockchain is also acting as a catalyst in the process of improving customer experience. The technology, with its key features like decentralization, transparency, and immutability, is making it possible for companies to store user behavioral and demographic data on blocks securely, make them portable and letting users decide with whom to share their immutable details with. The technology enables users to know what exactly is happening with their personal information and thus, experience a sense of security and trustability throughout the process.

4. Voice Technology

Voice Technology Is Not a Trend, But the New Shift of IT Paradigm | by | Chatbots Life

Not only Artificial Intelligence, but Voice technology will also be seen playing an indispensable role in improving customer experience.

The technology, in the form of Voice search and Digital assistants, will continue to help businesses in delivering a faster, seamless and flexible experience to their target audience. It will enable businesses to engage users in a profitable manner and facilitate them with better actions.

And this can be proven by a study by Pindrop, which states that around 28% of companies have already embraced voice technology in their CX strategy while 57% are planning to deploy in the next one year. Also, another 88% believe that voice technology will give a competitive advantage in enhancing user experience.

5. AR/VR

VR vs. AR Face-off | NextReality

Lastly, AR/VR is also one of the technologies that are reshaping the world of customer experience.

The technology takes users to the virtual world and enhance their customer journey effectively. It presents feedback form in different ways and increases the chances of getting a positive reply. And above all, it helps in product testing by exposing user/product to different situations and places.

With this, we have covered all about the process and use of Artificial Intelligence in Customer Experience. We have also unveiled what is the future of AI in the CX world as well as what all other technologies will disrupt the world of Customer Experience.

If you still have any doubts, feel free to check the FAQs shared below or directly get in touch with our AI mobility experts.

Frequently Asked Questions about AI in Customer Experience

1. What is the Role of AI in Customer Experience?

AI plays a crucial role in improving customer experience in the business domain in terms of automating repetitive tasks, streamlining processes, reducing the risk of fraud, and above all, delivering personalized options to every individual.

2. Why use AI to improve Customer Experience?

Artificial Intelligence, with its power to gather and analyze customer data in real-time, is helping in getting a better understanding of customer behavior and needs, and eventually creating a personalized customer experience strategy.

3. How AI and Machine Learning are improving Customer Experience?

AI and Machine learning are enhancing customer experience in multiple ways, including streamlining shopping experience, reducing the risk of fraud, and delivering personalized marketing schemes.

4. How to Start using AI to improve Customer Experience?

There are four steps to start using AI to improve customer experience:-

  • Design a Customer Experience (CX) Strategy
  • Plan and Analyze User Journeys
  • Have a Clear Understanding of AI solutions
  • Decide Whether to Create/Buy AI Solutions
  • Track and Measure Success

5. How AI will shift Customer Experience to the Next Level?

AI will bring a drastic shift in Customer experience in the future in the following ways:-

  • It will encourage users to focus more on their vision and creativity, rather than looking into minor details of production.
  • It will turn ‘One Click’ experience to ‘Zero Click’, providing target audience with a quick and seamless experience.
  • It will improve connectivity networks.
  • It will encourage the idea of gathering and employing unbiased society data and deliver quality to all.
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