Can ML really help deliver exceptional customer experience?

Customer experience (CX) is a fervently discussed term among businesses in recent years. And there is a quite valid reason for that. Every activity, project and process in your company has one common ultimate goal – to make acquire, retain and make customers happy.

But, what exactly is customer experience and why it has become a priority for many organisations?

It refers to the customer’s perception of the interaction with your brand. From the very moment that a customer hears about your company, buys from you, until the moment when they complained or praised you on their social media accounts. To this, ad the fact that customer expectations are higher than ever and you come close to understanding why brands put so CX at the top of their priority list.

CX refers to the customer’s perception of the interaction with your brand. From the very moment that a customer hears about your company, buys from you, until the moment when they complained or praised you on their social media accounts.

Customer experience and the Digital and AI Economy

As digitalisation impacts every aspect of the business, you can bet that it is changing the relationship between the customer and the brand.

Digitalization is changing customers’ habit. The customer of the digital era is a modern, more informed, digitally-literate buyer. Modern customers are used to getting what they want at the moment they want it. This shift forces businesses to rethink and reshape the way they interact with their customers.

What customers focus on when they assess a brand is its digital customer experience. For businesses, this means several changes:

• Social selling – Building communities and relationships with your customers on social media where they feel comfortable interacting. Relevant and engaging content is a far more effective strategy then pushy sales strategy.

• Data-driven marketing strategy – More and more companies are using Artificial Intelligence (AI) to build their data-driven marketing strategies. Marketing and sales activities continually generate customer data that can be used to form accurate insights about them. These insights can be harnessed to deliver a personalized, laser-targeted experience.

• Proactive customer service – Customer service in the digital-first world doesn’t only present waiting by the phone to receive complaints. Customer service teams have a whole array of channels where they can gather feedback and help out customers – social media, forums, blog comment sections, community groups, etc.

Modern customers are used to getting what they want at the moment they want it.

Put simply, to be able to serve digital native customers, organisations should jump in their buyers’ shoes and think digital first.

But what does Machine Learning has to do with customer experience at all?

A lot actually. Artificial intelligence and machine learning (ML) are revolutionising the way customers interact with brands.

All data that is gathered through touchpoints on disparate digital channels, is processed so that conclusions can be drawn and appropriate decisions made. And all this is done thanks to ML. Machine learning employs complex algorithms to learn from previous experience and mimic human decision-making.

By producing data-driven customer insights and continuously improving them based on the newly added data to the modules, machine learning supports companies in anticipating customer preferences and needs and gaining competitive advantage.

Global brands are using AI and machine learning on a large scale to deliver an exceptional customer experience. Here are some of them:

1. Netflix recommends shows based on viewer’s preferences, history and demographics.
2. Disney gives guests MagicBand wristbands to use for identification, room keys and buying tickets. The wristbands provide Disney with a wealth of data they use to provide personalized customer experience.
3. Burberry uses ML and image recognition to tackle counterfeit bags. They scan a portion of the purse to determine it is authentic and thus making sure their customers get the original product.
4. Instagram provides targeted advertising, deletes offensive comments, and recommends relevant images which are all enabled by machine learning.
5. Starbucks’s app remembers their customers’ coffee preferences and they can order their favourite drink via their mobile phone.

One of the world-leading brands that offer services built on data is Uber. We are going to look at their story in more detail.

Machine learning has found a significant role in advancing CX in the digital era.

What can we learn from Uber?

Uber is one of the most successful startups in the world, and a great part of their success is attributed to machine learning. They know how to put ML to work to delight their customers.

In order to understand what exactly Uber does to delight it’s customers, we caught up with Ritesh Agarwal, Uber’s Senior Data Scientist.

Ritesh highlights that Uber functions are data-driven to that extent that every aspect of the app has some model behind it.

Some of Uber’s app ML-based features that help to enhance riders’ experience are:

• Personalized destination suggestions based on ride history and frequently travelled destinations.

• One-Click chat – a smart reply system which allows riders and drivers to communicate easily with in-app messaging. The system uses machine learning and NLP to anticipate responses to common riders’ questions. Drivers can reply back with just one click of a button.

• Bridging the supply-demand gap – Uber’s system predicts time periods and area are going to have increased demand and alerts drivers accordingly. Meeting the demand in pick hours helps Uber keep customers happy and increase its customer retention rate.

Additionally, in order to make sure that such a widely used app can be reliable all the time, it relies entirely on AI and machine learning, explains Ritesh Agarwal. “We are using machine learning and data science to detect any kind of incidents and resolve them as soon as possible”, he adds.

The time to detect and resolve an incident should be among the main company’s KPIs.

When a brand is serving the global market as Uber does, it must act extremely fast and adapt to the ever-changing scenery. The same proactiveness applies to detecting incidents with your product/service, resolving them and rolling out the updates. Uber has understood the correlation between the speed with which a company delivers changes and the product/service reliability to the customers. 

“The time to detect and resolve an incident should be among the main company’s KPIs”, advises Anando Sen, Uber’s Senior Product Manager. However, solely recognizing the issue is not enough. The ability to attribute code and configuration to the incidents, fix them and roll out the updates to the globally distributed market as fast as possible, with a special emphasis on fast – this is what counts and draws the image in your customers’ eyes.

Companies that have found ways of deploying ML to enhance their CX are enjoying a boost in their customer retention rate.

Conclusion

Customer experience is crucial for business existence. And machine learning has found a significant role in advancing CX in the digital era. Companies that have found ways of deploying ML to enhance their CX are enjoying a boost in their customer retention rate. And as businesses gain even greater in-depth knowledge of their customers’ needs, they will be able not to just fulfil them, but also anticipate future needs, tastes, moods and desires.