How can machine learning improve customer experience?

We’ve all heard about the power of machine learning (ML) and the importance of customer experience (CX), but what does that actually mean, and what can we do about it? 

At Sush Labs, through building digital experiences for a wide variety of use cases and businesses, we’ve come to understand the reality of what’s required in putting the customer first, and how ML technologies and solutions can enable this.

‍

Good CX outranks everything

Companies such as Airbnb, Netflix and Deliveroo have re-engineered CX and upped the ante for all businesses everywhere. Customers of today have greater expectations around interactions, ease of use and efficiency. Businesses and specific services that stand out are those that focus on simplifying purchasing, communicate directly with customers and use data analytics to improve operations.

A study by global IT services provider, Dimension Data, shows that 81% of companies view CX as a competitive differentiator, and 84% of companies see that improving CX can result in an uplift in revenue. Microsoft’s State of Global Customer Service report gives insight into the customer point of view, stating 96% of customers say the service they receive directly influences their choice of loyalty to a brand.

Other studies reveal that CX does have a distinct impact on a company’s bottom line. A Qualtrics ROI of Customer Experience report reveals that companies earning $1 billion per year will see an average gain of $700 million within three years of investing in customer experience. Furthermore, Deloitte finds that customers are likely to spend 140% more after a positive experience when compared to customers who report negative experiences.

So where does technology come in? It’s no surprise that increasingly over the last decade, digital solutions have had a huge impact on a company’s ability to serve their customers. We see that companies investing in smart and well-considered digital initiatives or projects have seen a notable improvement in customer interaction and response. Clever investment in technology can also lead to greater profit. The MIT Initiative on the Digital Economy states that companies embracing digital transformation are 26% more profitable than their peers.

‍

Start with understanding your customer

With every digital initiative or transformation project, it’s crucial to begin with your customer and delve into what they actually want - not your assumptions about who they are and the experience they expect.

Let’s take ML and artificial intelligence (AI), for instance. This year Zendesk has released their Customer Experience Trends report, including data from 90,000 businesses across 175 countries. The report shows a distinct age differentiation when it comes to AI.

Those of the baby boomer generation are likely to want human agents over AI counterparts, despite the fact that AI may enable a company to provide support around the clock, make it easier to find answers or personalise a service. 

On the other hand, those of the Gen Z and millennial generations are generally more positive towards AI in CX, and half or more agree the technology can create a more personalised service. On top of this, almost three-quarters of Gen Z respondents (72%) and more than half of millennials (52%) said they start with a search or a company's help centre when using a service. This can include contacting support over chat or social media. 

The Gen Z/millennial group is also more likely to want support teams to offer personalised recommendations and keep track of credit card information. However, this group is also the most wary of data misuse, the Zendesk survey states, with almost a third of each group wanting companies to keep as little information on hand as possible. Meanwhile, older generations are likely to care more about companies keeping track of their order history, order status, and personal details.

Taking a brief look at generational perspectives on CX showcases the nuance of expectations, and the importance of taking the time to understand the best approach for your technology project.

‍

Designing for ML and AI

Today human-centric UX designs distinguish brands from competitors and enable companies to personalise CX to a much greater degree. Moving forward we will need to be designing with purpose, closing the gaps between customer strategy, sales, branding, IT and marketing to create cohesive experiences across all platforms that cater directly to a customer’s needs and desires.

For instance, AI and ML enables computers to shift from having a literal chain of commands to presenting likely options. As a result, the best UX and UI design considers choice architecture to offer a seamless and intuitive process and experience or recommendations.

In addition, ML can add value through providing greater insights and understanding into feasibility, desirability and viability of a project at every stage - from rapid assumptive testing (RAT) right through to the final user experience. However, it’s important to be sensitive and selective about how technology is applied, and focus on the best way to solve a problem and how ML can be used within this, as opposed to simply wanting to include the technology for the sake of it.

For the best CX, at every stage we need to complete user research, ideate and sketch different implementations, prototype and test the ML systems, always coming back to the human element and how we’re going to build trust. In this way we can accomplish the feat of completing an incredible CX project empowered by ML where it counts.