Using Machine Learning to improve customer service

By: John Flower
Tag(s): GCP
Published: Jun 27, 2017
Using Machine Learning to improve customer service

You might think Machine Learning is only for organisations with large amounts of complex data who are looking for deep, strategic insights – but that's not the whole picture. Machine Learning also has a role to play in helping organisations like yours deliver better customer service right now, sometimes using relatively small amounts of data.


Online grocer Ocado uses Google's natural language API

Take online grocer Ocado. Its contact centre is using Google's natural language API and a Machine Learning model developed in TensorFlow to automatically tag incoming emails based on their content. Ocado can then determine from the tags how urgent each email is and prioritise it in the queue, rather than handling everything on a “first in, first out” basis. This is helping it to deal with spikes in email traffic, which can double or triple when deliveries are affected by external factors such as bad weather or traffic jams, and allowing it to respond more quickly to customers who have an urgent request or are unhappy. Urgent emails are now dealt with four times as quickly as less urgent ones, and three times as quickly compared with the previous approach. Ocado has also been able to redeploy 4 FTE staff because it no longer has to review every email manually before processing it.

Global bank ING uses Google API.AI

Another company looking to use ML to improve customer interactions is global bank ING, which has developed a Facebook Messenger bot using the Google API.AI conversational user interface and Google’s natural language API. Called Marie, the bot allows the bank's customers to get help as if they were chatting naturally with a human customer service agent, without having to wait for an agent to become available.

Online marketplace eBay uses machine learning

Meanwhile, online marketplace eBay is using ML to improve the customer experience for both shoppers and sellers. For example, the eBay Shopbot provides a personalised shopping assistant that can learn shoppers' preferences, expressed using natural language, and recommend items from its catalogue of around one billion live listings. For sellers, eBay has created an application that allows them find out the value of items they might want to sell, simply by talking with their Google Home device and answering a series of questions about the item's make, model, condition and so on.

These are just a few examples of how machine learning is changing the way companies interact with customers - but the possibilities really are endless.

Working with a Google Cloud Platform Premier Partner

As a leading Google Cloud Service Partner, we have considerable experience with Google Cloud Platform, both assisting clients to future proof their business with cloud infrastructure.

Cloud adoption is not just about agility and cost optimisation — it’s about building the very foundations you need to continuously innovate and stay ahead. A cloud-first architecture using Google Cloud Platform not only modernises your infrastructure but unlocks a whole new world of digital freedom and opportunity.

Our onboarding methodology will help you realise value in weeks, not months so you can save costs and increase agility.

If you’d like to find out more about how we can help you, why not take a look at some of our customer success stories or talk to the experts in our Google Cloud Platform team.

6 ways to enhance customer experience with Google Cloud

< Back to resources

Think big. Start now.

We don’t believe in Innovation, we live it. Innovation combined with pragmatism is what runs through our veins. We ask ourselves the same question over and over again: Does it deliver value? And how quickly? Your big ambitions can start now.