In this fast-moving digital world, providing outstanding user experience is the best way to set your business apart. But improving UX while maintaining brand integrity is often tricky. Modern brands, however, seemed to have unlocked the secret with the help of machine learning.
It’s no secret that artificial intelligence is the bread and butter of tech firms in the 21st century. Yet, businesses are only just beginning to realize the true potential of AI when it comes to user experience. AI backs over 85% of all customer interactions.
In any case, users now expect businesses to be smarter in their approach to interacting with them. In turn, brands rely on machine learning capabilities to fulfill consumer expectations. This trend has given rise to predictive modeling as the basis of improving user experience.
But this modeling has to be based on sound data and assumptions about consumer behavior. That’s why AI is so crucial in data-driven marketing analysis as well. Brands that use AI to understand what consumers want and deliver it as UX are dominant today.
We look at how some businesses have made better use of machine learning to predict user behavior than others. Starting with a basic understanding of how machine learning works, we discuss 14 brands that have perfected user experience.
The Science Behind Machine Learning
If you’ve ever wondered how predictive modeling works, all you need to do is observe social media feeds. Social media platforms use predictive modeling for everything, from the posts you see to sponsored ads and everything in between. Even though the outcome seems sophisticated and straightforward, the process behind predictive modeling is often complicated.
‘Predicting results‘ is the easiest way to understand predictive modeling or predictive analytics. This approach uses machine learning algorithms to analyze large volumes of data to predict future results. The ability to predict future outcomes is often useful for all kinds of businesses. But when it comes to consumer-driven marketing, it’s even more valuable.
The beauty of machine learning algorithms is their ability to learn as more data is collected. The algorithm re-calibrates to account for the latest data and makes predictions accordingly. As a result, businesses can design predictive models for anything, from financial models to customer lifecycles.
This feature is particularly useful, considering how consumer trends are ever-changing. Artificial intelligence detects changes in consumer patterns, updates machine learning algorithms, and creates new prediction models all in one go. Despite this sophistication, however, it’s essential to include a human agent in the system to adjust for unforeseen circumstances (*coughs* pandemic *coughs*).
So let’s look at how 21st-century businesses base their UX approach on these machine learning algorithms.
Exploring Brands’ Machine Learning Based UX Approach
Before we dive in, it’s important to note this list isn’t exhaustive. There are plenty of brands and apps that use ML algorithms for UX improvement, but these are the most noteworthy.
1. Google & YouTube
No list about user experience would be complete without Google. From self-driving cars to search ranking updates, Google is the master of optimizing UX using machine learning. Every search that users enter into the search engine is stored and analyzed by AI systems. The machine learning algorithms then formulate a user persona.
This persona updates continually according to the searches entered into Google. As a result, users often find themselves impressed with how Google was able to predict their needs so accurately.
YouTube users experience quite a similar feeling. That’s because machine learning algorithms base future predictions on the average watch time of users. The type of videos users spend most of their time on are the type of videos YouTube predictive modeling suggests.
Netflix is the king of user experience with its spot-on content suggestions and micro-classification. The company is so good at personalizing content using machine learning algorithms that it has created ‘taste communities‘ of users based on their viewing habits.
The streaming platform uses an obscene amount of consumer data to its advantage to improve UX. The streaming platform analyzes user preference with machine learning algorithms and groups them into clusters. It then offers similar content to users in the same cluster. As a result, users often end up coming across content they would like to watch.
We’ve already discussed briefly how social media platforms use artificial intelligence and machine learning algorithms to determine user preferences. Facebook takes this to the next level with it’s AI neural networks and predictive modeling that analyzes consumer content preferences.
The most vital utilization of machine learning by Facebook is its Deeptext feature. By using AI mechanisms, Deeptext analyzes user-generated content with almost human-level accuracy. This feature helps to catch fake news and hate speech. One of the best-known UX features of Facebook is to organize raw data and utilize it for sponsored ads.
Apple is all about optimizing user experience, and it designs its products with that priority. After all, who doesn’t know about the facial recognition tech of the new iPhone X? That is made possible with the magic of AI. IOS uses machine learning algorithms to detect unauthorized activity and keep users safe from cyber attacks.
AI algorithms also recommend songs and music on Apple Music. Apple’s use of machine learning has increased substantially in the past decade to focus on improving user experience.
You might be surprised to find Disney on this list, but AI plays a vital role in its dominance. The help of AI engineers the excellence of Disney’s content. The company uses AI neural networks to mimic the working of the human mind. It tests new content and movies through these AI neural networks to see if audiences will like it.
This is just one example of how Disney uses AI to put themselves ahead of the competition. The content tested through AI neural networks often also proves well with human audiences. The more testing Disney does, the smarter the ML algorithms become, and better is the UX.
Spotify utilizes AI and ML for predictive modeling. Millions of users search for music through Spotify, and it uses this to its advantage. Natural language processing and smart filtering algorithms suggest the most relevant music for consumers. As more and more users give feedback, AI can perfect its prediction algorithm. This feature results in enhanced UX for Spotify users.
From its Amazon Go stores to the AI-based Alexa, Amazon has taken UX to the next level. The e-commerce giant uses ML algorithms to predict what its users prefer and in its warehouses as well. By using AI programmed item retrieving robots, Amazon significantly increases efficiency. This feature shows the widespread applicability of AI in the years to come.
Amazon even uses machine learning in its chatbots to improve user experience. These chatbots have a speech to text options and also translate languages accurately.
Speaking of Amazon, Starbucks improves UX for its users by allowing them to place orders through Alexa. The orders are automatically placed at the nearest Starbucks outlet (that is tracked by AI, of course). AI-based ‘My Starbucks Barista’ takes orders and remembers users’ preferences for the future. This makes Starbucks a premium choice for coffee lovers.
Think a video calling platform can’t use AI? Think again.
Skype uses artificial intelligence for its background blur feature. The AI software tracks movement of arms, hands, and facial features during a call. It then blurs the background to give the best experience to its users.
Skype also needs accurate language translation capabilities because of its global use. It uses AI to listen to the spoken word and translates it into different languages. This feature improves user experience substantially.
BMW uses artificial intelligence in its cars for navigation and automatic braking systems. The cameras mounted at the front and back of the vehicles are equipped with AI technology to analyze road conditions. Whenever the system detects a proximity alert, it automatically engages brakes to avoid a collision. This road condition detecting system improves the driving experience for consumers and saves lives in the process.
TikTok, the hottest video platform in the world right now, uses AI to stay on top. The machine-learning algorithm predicts the type of content users would like to see. These predictions rely on past user behavior and interaction with the platform.
TikTok also offers enhanced experience for marketers. AI tech analyzes trending videos to see how much time consumers spend on each video. The more time spent by consumers, the more interest it generates over time.
Uber uses AI to differentiate itself for over a decade. That’s why it’s an AI-first company instead of a mobile-first company. No wonder it uses AI for just about everything, but since we’re talking about UX, let’s focus on customer service.
AI-based customer service has resulted in a 10% increase in efficiency for Uber. Since Uber uses AI to handle customer complaints, so the machines already know all the pain points. So when a customer comes with a support problem, Uber uses AI to handle the complaint. With all the customer info on record, the machines do a much better job handling consumer support problems than human agents.
Unsurprisingly, Microsoft assistant ‘Cortana’ is AI-based. This assistant helps users with all types of daily tasks, from sending emails to using applications. But the real advantage of AI is displayed by Microsoft AI Platform, which includes Microsoft Cognitive Services, Microsoft Cognitive Toolkit, and Microsoft Bot Framework.
By allowing other organizations to host their digital infrastructure on its Azure Cloud platform, Microsoft has utilized AI to its maximum potential. Other organizations save costs, but thanks to the Microsoft AI platform, they get things done faster.
Alibaba is using AI and machine learning in interacting with customers, integrating information, and organizing backends. The AI-based chatbots interact with over 3 million users a day and prioritize users based on their emotions. This capability is made possible due to the sentiment analysis features of artificial intelligence.
Much like Amazon, Alibaba uses AI to turn physical stores into smart shops that run cashless and counter-less. The company is speeding up digitization of the retail industry, thanks to AI-based processes.
We could go on and on, but there’s no end to AI and machine learning to improve UX. Businesses are rapidly shifting their approach to include machine learning since it’s the only way to meet modern consumer expectations.