4 Big Brands That Use AI & ML To Improve Customer Experience
We all have experienced how messy today’s Customer Experience has become. Therefore, it has become liable for companies to use AI & ML for business growth by delivering superior customer experience.
“Companies which are mining insights and using those to drive their business will witness 27% annual growth in revenues from 2015 to 2020, touching $1.2 trillion in total revenue, and Machine Learning technologies are projected to evolve into a $100 billion market by 2025”. – Forrester Research
Nowadays, businesses are learning from historical customer interaction as and when monitored by Machine learning (ML). And fine-tuning the customer experience in a holistic manner by delivering the right content at the right time via the right channel has become important for customer conversion and retention.
This is the reason that Machine Learning and data science both are growing significantly working on the most compelling developments as Application Programming Interfaces (APIs). These APIs have shown promising potential for improving, facilitating, and managing growth hacking ways.
“Machine Learning as a Service (MLaaS) market supposed to enlarge to $7.6 billion by 2023.”
With Machine Learning as a Service (MLaaS) it looks like the new tech market is coming up. It is simplifying both customer experience and internal processes. MLaaS is providing a speedy system to replace manually coding models.
Examples of Multi-million Dollar Companies leveraging AI & ML to improve their Customer Experiences
Disney uses Machine Learning Algorithm and IoT to power CX
After years of testing Disney launched a MagicBand, a wristband that is integrated with RFID technology and a long-range radio. These MagicBand communicate with thousands of sensors present in the Disney premise, for a smart Customer Experience.
MagicBand act as tickets, FastPasses, credit cards, hotel keys, and a lot more. With the swipe of the band, the giant computer system across the park knows, what you are doing, where you are, and what do you need. Additionally, your favorite Disney cartoon characters can find and greet you and your children wherever you are. Candid photos of your family can be clicked the entire day and then sent to you at night in your hotel rooms.
Machine Learning based Magicband were implemented to weed out the friction within the Disney World Experience. And one of the biggest challenges of Disney was the waiting line. They know when a visitor is at the waiting line, they are not spending money on food or rides. As a result they developed this band to nullify this problem and enhance their customers’ experience.
Disney’s Next-gen tech – Recognizing customers through Shoe Soles
Disney last year had applied for a patent for a system that will recognize customers by their shoe sole. Their aim is to provide a Next-gen experience that aims to offer a more seamless, immersive, and personal experience to every visitor.
With more than 90 million transactions a week in 25000 stores globally, Starbucks uses Machine Learning and big data analytics to help direct marketing, business decisions, and sales. By launching its mobile application and reward program they collected and analyzed their customer’s buying habits. The users themselves have created the data by defining where, what, and when they buy coffee.
Starbucks gathers this information about their customer’s buying habits, so that even when the customer visits an offline store their system is able to identify their preferences through their smartphone. In addition to this, the app can also suggest new treats that might go with the drinks they ordered.
All this is powered by Starbuck’s Digital Flywheel Program. It is a cloud-based Artificial Intelligence engine that recommends food and drinks options to the customers who are not aware but want to try something new.
The technology is so sophisticated that the recommendations will change according to the weather on that particular day, or if it is a holiday or a weekday, or at what location you are.
AI & ML are changing every aspect of Amazon’s Business, from its products, warehouse, to its Echo smart speaker.
Since its earliest days Amazon has used Machine Learning to come up with product recommendations based on the products that the users have already liked. The technology behind those systems has been updated every now and then to make its functionality much better.
These days these recommendations have become more dynamics all thanks to ML.
Another Amazon powered product is Alexa, voice assistant, she gives Amazon Web Service users access to cloud based tools, allowing shoppers to grab items and walk immediately out of Amazon Go stores, guide robots carrying products directly to the fulfillment center, and a lot more.
One of the major reasons why Amazon has risen to a near trillion dollar company is because of its Amazon Web Services, which a cloud storage and server provider. AWS has become a cloud storage standard for a lot of companies and this most because these companies want access to the same technology that powers Amazon’s Alexa, Amazon Prime Videos, and Amazon.com.
AWS is being used across a lot of industries – retail, fashion, entertainment, real estate, health care, and more. Their customers have a variety of AI competence. Some of them are experts having a PhD in Machine Learning, and some of them are developers. Amazon has tailored its Machine Learning and Artificial Intelligence services to match the needs of their customers.
Data Volumes at American Express was not only increasing, but also was changing a lot. More and more of their customers were doing businesses via mobile phones. American Express has seen with the access to big data and ML they can develop models that can help them learn about customer behavior, fraud case detection, new customer acquisition, and recommendation for better customer experience.
In terms of fraud detection American Express have started keeping excellent track record, including their online business transaction using Machine Learning. To do this Machine Learning requires a lot of data sources that will include card membership, merchant information, and spending details.
For new customer acquisition, Amex has up their online presence and website model. Lately they only used to receive leads from their Email Campaigns but as of now, their online engagement has risen by 40%.
One of the most favorite parts of using AI & ML is recommendations. When an Amex user gives permission to track their data, ML can monitor their history and give out recommendations accordingly.
ML Delivering Outstanding Customer Experience
The above examples have shown how Machine Learning consulting services has helped these billion and trillion dollar companies develop personalized customer experience via go-to-market strategies, delighting the buyers in every touch point and eventually make them evangelists.
It has also helped these organizations with predictive analysis, recognizing what issues customers will be facing in the near future, at what point in time, and what could be the pre-emptive measures and approach for the right solution. Delivering a superior experience that can potentially convert a customer into your solution and take care of the retention.
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