Contact Centre Agent

Being the world’s largest online-only grocery supermarket with over 500,000 active customers means we get the opportunity to interact with people all across the UK on a daily basis. Ocado prides itself on offering the best customer service in the industry which is one of the many reasons why our customers keep coming back.

Since Ocado doesn’t have physical stores, there are mainly two ways our customers and our employees interact directly. The first (and probably most common) is when our drivers deliver the groceries to the customers’ doorsteps; the second is when customers call or email us using our contact center based in the UK.

Today we’re going to tell you a bit more about how a customer contact center works and how Ocado is making it smarter.

The customer contact center

On the surface, Ocado operates the kind of contact center most people are already familiar with; we provide several ways for our customers to get in touch, including social media, a UK landline number, and a contact email.

Contact Centre

Customers can email, tweet or call Ocado

When it comes to emails, we get quite a variety of messages: from general feedback and redelivery requests to refund claims, payment or website issues – and even new product inquiries.

Getting in touch with a company can sometimes feel cumbersome. To make the whole process nice and easy for our customers, we don’t ask them to fill in any forms or self-categorise their emails. Instead, all messages gets delivered into a centralised mailbox no matter what they contain.

Contact Centre

Ocado customer service representatives filtering customer emails

However, a quick analysis of the classes of emails mentioned above reveals that not all of them should be treated with the same priority. In an old-fashioned contact centre, each email would be read and categorised by one of the customer service representatives and then passed on to the relevant department.

This model has a few major flaws: if the business starts scaling up quickly, customer service representatives may find it challenging to keep up, leading to longer delays which will anger customers. In addition, sifting through emails is a very repetitive task that often causes frustration for contact centre workers.

Clearly there must be a better way!

Machine learning to the rescue

Unbeknownst to many, Ocado has a technology division of 1000+ developers, engineers, researchers and scientists working hard to build an optimal technology infrastructure that revolutionises the way people shop online. This division is called Ocado Technology and includes a data science team that constantly finds new ways to apply machine learning and AI techniques to improve the processes related to running retail operations and beyond.

After analysing the latest research on the topic, the data science team discovered that machine learning algorithms can be adapted to help customer centres cope with vast amounts of emails.

The diagram below shows how we created our AI-based software application that helps our customer service team sort through the emails they receive daily.

Cloud computing model

The new AI-enhanced contact centre at Ocado

One of the fields related to machine learning is natural language processing (NLP), a discipline that combines computer science, artificial intelligence, and computational linguistics to create a link between computers and humans. Let’s use an email from a recent customer as an example to understand how we’ve deployed machine learning and NLP in our contact centres:

Example of feedback

The machine learning model identifies that the email contains general feedback and that the customer is happy

The software solution we’ve built parses through the body of the email and creates tags that help contact cenre workers determine the priority of each email. In our example, there is no immediate need for a representative to get in touch; the customer is satisfied with their order and has written a message thanking Ocado for their service.

We strive to deliver the best shopping experience for all our 500,000 + active customers. However, working in an omni channel contact centre can be challenging, with the team receiving thousands of contacts each day via telephone, email, webchat, social media and SMS. The new software developed by the Ocado Technology data science team will help the contact centre filter inbound customer contacts faster, enabling a quicker response to our customers which in turn will increase customer satisfaction levels. – Debbie Wilson, contact centre operations manager

In the case of a customer raising an issue about an order, the system detects that a representative needs to reply to the message urgently and therefore assigns the appropriate tag and colour code.

Data science at Ocado, using Google Cloud Platform and TensorFlow

This new ML-enhanced contact centre demonstrates how Ocado is using the latest technologies to make online shopping better for everyone.

Ocado was able to successfully deploy this new product in record time as a result of the close collaboration between three departments: data science, contact centre systems, and quality and development. Working together allowed us to share data and update models quickly, which we could then deploy in a real-world environment. Unlike a scientific demonstration where you’re usually working with a known set of quantities, the contact centre provided a much more dynamic scenario, with new data arriving constantly. – Pawel Domagala, product owner, last mile systems

Our in-house team of data scientists (check out our job openings here) trained the machine learning model on a large set of past emails. During the research phase, the team compared different architectures to find a suitable solution: convolutional neural networks (CNNs), long short term memory networks (LSTMs) and others. Once the software architecture was created, the model were then implemented using the TensorFlow library and the Python programming language.

TensorFlow and Python logos

Python is the de-facto most popular programming language in the data science community and provides the syntax simplicity and expressiveness capabilities we were looking for.

TensorFlow is a popular open-source machine learning toolkit that scales from research to production. TensorFlow is built around data flow graphs that can easily be constructed in Python, but the underlying computation is handled in C++ which makes it extremely fast.

We’re thrilled that TensorFlow helped Ocado adapt and extend state-of- the-art machine learning techniques to communicate more responsively with their customers. With a combination of open-source TensorFlow and Google Cloud services, Ocado and other leading companies can develop and deploy advanced machine learning solutions more rapidly than ever before. – Zak Stone, Product Manager for TensorFlow on the Google Brain Team

Understanding natural language is a particularly hard problem for computers. To overcome this obstacle, data scientists need access to large amount of computational resources and well-defined APIs for natural language processing. Thanks to the Google Cloud Platform, Ocado was able to use the power of cloud computing and train our models in parallel. Furthermore, Ocado has been an early adopter of Google Cloud Machine Learning (now available to all businesses in public beta) as well as the Cloud Natural Language API.

Google Cloud Platform logo

If you want to learn more about the technologies presented above, check out this presentation from Marcin Druzkowski, senior software engineer at Ocado Technology.

Make sure you also have a look at our Ocado Smart Platform for an overview of how Ocado is changing the game for online shopping and beyond.

October 13th, 2016

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Cloud computing model

World’s largest online-only grocery retailer harnesses the power of AI and the Google Cloud Platform to categorize and prioritize customer emails

Ocado announces the deployment of its machine learning (ML)-enhanced contact center which employs an advanced AI (artificial intelligence) software model to categorize customer emails.

This approach ensures customers are still getting that familiar human touch while also benefiting from the quick response provided by technology automation. From the contact center point of view, the customer service representatives don’t have to spend hours categorizing thousands of emails manually; instead, the AI model parses the email and provides a useful summary and a priority tag. The customer service representative can then focus on solving the customers’ problems in a timely manner.

We strive to deliver the best shopping experience for all our 500,000+ active customers. However, working in an omni channel contact centre can be challenging, with the team receiving thousands of contacts each day via telephone, email, webchat, social media and SMS. The new software developed by the Ocado Technology data science team will help the contact centre filter inbound customer contacts faster, enabling a quicker response to our customers which in turn will increase customer satisfaction levels. – Debbie Wilson, Ocado contact centre operations manager
Thanks to a robust architecture, the software model can process thousands of customer emails per day and has been trained using millions of past messages from customers. In addition, the application respects customers’ privacy by filtering out personal details such as postal or email addresses, telephone numbers and other sensitive information.

The new ML-enhanced contact center application has been built using an in-house AI model and data sets created by Ocado Technology (the technology division of Ocado) as well as TensorFlow and related products from the Google Cloud Platform.

We’re thrilled that TensorFlow helped Ocado adapt and extend state-of- the-art machine learning techniques to communicate more responsively with their customers. With a combination of open-source TensorFlow and Google Cloud services, Ocado and other leading companies can develop and deploy advanced machine learning solutions more rapidly than ever before. – Zak Stone, Product Manager for TensorFlow on the Google Brain Team
Ocado is also one of the leading partners for the Google Cloud Platform and its Cloud Natural Language API.

About Ocado
Established in 2000, Ocado is a UK-based company admitted to trading on the London Stock Exchange (OCDO), and is the world’s largest dedicated online grocery retailer, operating its own grocery and general merchandise retail businesses under the Ocado.com and other specialist shop banners. For more information about the Ocado Group, visit www.ocadogroup.com

About Ocado Technology
Ocado Technology is a division of Ocado developing world-class systems and solutions in the areas of robotics, machine learning, simulation, data science, forecasting and routing, inference engines, big data, real-time control, and more. The fusion between the Ocado retail and Ocado Technology divisions creates a virtuous circle of innovation that leads to disruptive thinking. For more information about Ocado Technology, visit www.ocadotechnology.com

October 13th, 2016

Posted In: Press releases

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Alex speaking on stage

Earlier this month I took part in a panel discussion on robotics at Stuff Innovators 2015.

I shared the stage with Patrick Levy Rosenthal CEO of EmoShape, they produce a microchip for robots aimed at producing emotional responses, and Nicolas Boudot from Aldebaran, the company that developed a companion robot called Pepper (seen in the picture above).

Initially I was asked about robotics at Ocado and why there was a need, so I talked about Ocado being much more than a webshop with some delivery vans. I explained our CFCs and the over 700 technologists needed to develop such sophisticated systems, and that part of this work revolves around robotics, the difficulties in picking the entire 45,000 SKU range, and in the design, construction and maintenance of the automation.

The questions and discussion were really aimed at identifying the key challenge when developing robots that interact with people in an intuitive manner. All the panel agreed in pinpointing AI.

Learning knowledge is currently beyond state-of the-art, and the challenges with the physical elements of the robots are being improved all the time, but the required AI to allow robots to exhibit even a basic set of skills with a degree of competence needed for really intuitive human interaction is the most significant challenge.

We then discussed whether humans have anything to fear from the rise of robots. The panel agreed not for the foreseeable future, and not until there is some radical change in state-of-the-art AI.

The Ocado Technology view was that robots will be employed to assist the human workforce and to reduce the environmental challenges they face (for example lifting heavy, awkward SKUs like packs of bottled water ot cat litter). Also, that the customer might see many potential improvements as a result, such as: better quality (pick to tessellation algorithm); shorter delivery windows; reduced minimum order sizes.

At the end, the chair asked us how long it would be before the types of robots we see on screen (Ex-Machina, Humans etc) will be available to buy. Again the panel was unanimous: not within the next ten years. However, Nicolas thought it would be commonplace to have less intelligent robots sooner than that.

While at the conference I listened to a panel discussing wearables, and while the majority of the discussion was very much focused on the consumer side (smartwatches and health/fitness apps), the representative from Intel alluded to some industrial wearables they were involved in that were really interesting to us. Take a look:

      • Vuzix produces smart glasses for commercial/warehouse use, they had a 30% investment from Intel in 2015
      • Munich-based, Intel partner Workaround UG (set up by ex-BMW employees) produces the ProGlove, an intelligent glove that uses chips to power a simple display on the wrist telling the person wearing it whether they completed the assembly task correctly. Here’s a company demo of it:

 

Alex Harvey, Head of Reseach and Project Management

November 11th, 2015

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Matt Whelan

My team builds simulations of physical systems. Our work falls into 3 categories: experimental, tactical, and operational.

At the experimental end, we build simulations and design tools for new technologies and warehouse layouts, along with prototype control algorithms.

Tactically, we try out proposed changes to our warehouse topologies in silico and perform ROI analysis. We create and mine large data sets so we can spot and remove risk from our growth strategy.

Operationally, we pipe streams of production data into 3D visualisations, originally developed for playing back simulations, allowing real-time monitoring of our live control systems.

We get to work on some pretty bold conceptual projects because, when working at such a massive scale (last year our operation turned over £1billion), even seemingly small percentage efficiency savings mean serious money to the business.

I read a lot about how the more theoretical aspects of computing – things that interested me in the subject in the first place – aren’t as important in the ‘real world’ of enterprise software development. There are big players in all kinds of industries getting left behind because they shy away from AI, robotics, and large scale automation. I think we’re really lucky that we get to spend our time creating novel path searches, travelling salesman solvers, discrete optimisers and the like, and it gives us an edge over our competitors in a fierce market.

The team is a real mixed bag of interests and hobbies. We have a physics doctor, a swing dancer, and a gaming software expert for starters. One thing we all have in common is that we’re unfazed by scale – an attitude which pervades Ocado Technology – and all looking to be the person with the big idea.

The beauty of the environment we’re in is that we can prove how big that idea is before millions are spent on building it.

If that sounds like a team you want to be a part of, these are the positions we’re recruiting for now:

Full Stack Django/Celery Software Engineer

Java Software Engineer (SE2) – Simulation

Senior Java Software Engineer – Simulation

Matt Whelan, Simulation Research Team Leader

September 16th, 2015

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SecondHands

Recently we kicked off an exciting project to develop an autonomous humanoid robot. It will use artificial intelligence, machine learning and advanced vision systems to understand what human workers want, in order to offer assistance.

For example, it will be able to hand tools to maintenance technicians, and manipulate objects like ladders, pneumatic cylinders and bolts.

The ultimate aim is for humans to end up relying on collaborative robots because they have become an active participant in their daily tasks. In essence, the robot will know what to do, when to do it, and do it in a manner that a human can depend on.

The project is called SecondHands as it will literally provide a second pair of hands, and is part of the European Union’s Horizon 2020 Research and Innovation programme. We are leading the research, working with four other European institutions.

The tasks our robot will carry out will increase safety and efficiency, and require us to focus on key areas of robotics including:

Proactive assistance – the robot will have cognitive and perceptive ability to understand when and what help its operator needs, and then to provide it.

Artificial intelligence – to anticipate the needs of its operator and execute tasks without prompting, the robot will need to progressively acquire skills and knowledge.

3D perception – advanced 3D vision systems will allow the robot to estimate the 3D articulated pose of humans.

Humanoid form and flexibility – SecondHands will feature an active sensor head, two redundant torque controlled arms, two anthropomorphic hands, a bendable and extendable torso, and a wheeled mobile platform.

For more information, see the project’s website.

Dr Graham Deacon

Robotics Research Team Leader

UPDATE: If you think that sounds interesting, we’re looking for a talented Robotics Research Software Engineer to join the team. Take a look at the role now.

July 1st, 2015

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