In the last few years, the development of increasingly powerful AI has improved chatbot capabilities and driven the growth of self-serve technologies as a whole. However, the dizzying pace of progress means that organisations hoping to take advantage of these emerging technologies need to have a carefully considered AI strategy in place as soon as possible if they’re to avoid missing out.
In 2020, we see a focus being placed on three key areas of self-serve technology;
- Voice-based communication – this type of communication has already had a big impact on both the marketplace and the public conscious. Voice-based assistants, such as Siri and Alexa, have made their way into homes up and down the country and into virtually every mobile device on the market. While voice-based technology is likely to have an impact on bots, your strategy will also need to reflect its influence on IVR, too.
- Growth of knowledge bases – one of the key benefits of AI is the speed and efficiency with which it can search, sort and analyse vasts amount of data. AI improves self-serve knowledge bases by utilising these qualities to find relevant and accurate answers to customer enquiries with greater speed than ever before.
- Virtual agents – virtual agents are animated, AI characters that are able to hold intelligent conversations with users, respond to prompts and utilise non-verbal actions. Though they have been used for a number of years, AI has the potential to create more fully rounded assistants that more closely resemble human agents and can fulfil a broader range of functions.
The deployment of AI isn’t restricted to the development of self-service tools. In fact, one of its most useful applications is agent automation. This is the process by which tasks typically carried out by agents are automated to free up the agent and allow them to focus their attention on complex tasks that are more worthy of their time and effort. It boasts several key benefits, including improved agent performance and first contact resolution, reduced wait and call handling times and higher morale among contact centre employees.
In 2020, AI strategies relating to this type of automation will likely centre on two pivotal areas;
- Customer information acquisition – when a customer first enters the customer service system, AI can be used to gather relevant information to speed up the agent’s work. This means the agent doesn’t have to complete time-consuming data entry exercises and can get straight to work on delivering a resolution.
- Intelligent routing of enquiries – the future of intelligent routing depends on AI as it’s the best technology for establishing who the right agent is for any given enquiry. To do so, it considers a range of factors. These include agents’ training and skills, as well as customer priority, their previous enquiries, their value to the company and their willingness to wait.
Intelligent routing should be of particular importance to all contact centre AI strategies going forwards. This is because of the way AI is best used to augment highly-skilled human agents, ensuring a balance is maintained between automation and the all-important human touch.
Equipping agents with the skills and abilities required to provide improved services requires investment and the return on this investment will need to be maximised by ensuring your human resources are used to their full potential. In an intelligent routing context, AI ensures that the right agent is matched to individual customer enquiries, improving services and maximising ROI and the benefit to your organisation.
There’s no avoiding the fact that big data and advanced analytics have not only revolutionised commerce but also reshaped the whole of modern society. AI sits at the heart of contemporary analytics and is expected to play a pivotal role in developing increasingly powerful insights into customer behaviour and market trends. As organisations in both the public and private sector deploy digital technologies to gather greater amounts of data, it’s AI that will be instrumental in making sense of what it all means.
In order to ensure that your AI strategy is prepared for the future of analytics, it will need to take the following factors into consideration.
- From predictive analytics to machine learning – whereas predictive analytics involves human attempts to predict what may happen based on patterns in historical data, machine learning removes the human from the equation and puts AI in control of analysing vast amounts of data and developing complex models that can predict future behaviour. This type of analytics is both more reliable and accurate and will be used across the contact centre to forecast customer behaviour and inform key decision making processes.
- Opening channels to the power of analytics – AI also has the power to increase the amount of data available for analysis. A good example of this is telephony-based enquiries. Previously, the only real quantifiable data available from calls were metrics like handling time and wait time. With the development of Natural Language Processing (NLP) and speech analytics, AI will be able to extract far more information relating to caller intention, behaviour and dissatisfaction.
Much of the excitement surrounding AI technology in the contact centre is understandably focused on customer-facing applications. However, it also has a role to play in internal workplace management. As organisations attempt to retain a human touch by investing more in key personnel, you’ll need to ensure that your agents are able to fulfil their potential. As a result, your 2020 AI strategy should consider the ways AI can be implemented to improve their performance.
This will involve looking at three aspects of AI workplace management in particular;
- Skill-usage optimisation – if determining how a multi-skilled employee is best put to use is challenging on an individual basis, coordinating the process across an entire workforce is even more so. AI technology is capable of determining how employees should best divide their time between various workstreams to maximise benefits to the organisation.
- Machine learning and scheduling – one of the key advantages of AI Machine Learning is that it can operate in a closed-loop. This means that it doesn’t require human intervention for it to make improvements. Instead, it acts on a constant feedback loop, using new data to make regular improvements to workplace scheduling.
- Employee engagement and satisfaction – many organisations are now recognising the importance of employee engagement and satisfaction to productivity and performance. Studies show that engaged employees contribute 20% more revenue and are 44% more productive. AI can improve engagement by taking individual employee preferences and availability into account when scheduling, as well as balancing the needs of staff with those of the organisation.
Many of the benefits of AI we’ve mentioned so far can be realised in the short-term. However, AI strategies will also need to consider the mid to long-term if they’re to leave a lasting legacy. One way this can be achieved is by implementing AI in a manner that ensures the entire workplace becomes a learning environment.
This can be achieved by;
- Giving AI access to all contact centre transactions – using various tools, including Natural Language Processing (NLP) and Sentiment Analysis, AI is capable of managing and analysing large unstructured data sets to find patterns and trends that could help improve the customer experience in the future. By ensuring AI is listening in on all contact centre interactions, you’re providing it with information from which human analysts have historically struggled to draw useful, reliable and accurate conclusions.
- Feed satisfactory responses into the Knowledge Management System (KMS) – Every time the contact centre resolves an enquiry or answers a question, the solution should be fed into your KMS. This ensures that your AI technology can use the information to improve its own predictions and analysis, whilst also developing an excellent resource for employees.
Text has made a bit of a comeback in recent years, with an increasing number of organisations returning to rely on text message as an efficient means of communicating with customers.
This may have something to do with the fact that an astounding 97% of consumers are happy to hear from businesses via text. It may also have something to do with the way in which AI is opening up Rich Communication Service (RCS) to a whole host of innovative uses.
RCS is a communication protocol that aims to replace SMS messaging by allowing for multimedia such as videos, GIFs and maps, as well as interactive applications, including polls and menus.
In the near future, we expect to see RCS deployed with AI functionality, creating another customer service channel capable of automating several simple tasks. For instance, retail organisations could use the service to facilitate the return of unwanted products, while local authorities could take advantage of RCS by using it as a means of reporting fly-tipping or to conduct informal polls.
Over the last few years, contact centres have realised the need to adopt an omni-channel approach to customer care. Customers want to access services from a wide range of devices and channels seamlessly and without obstruction.
While this is challenging but feasible when you’re talking about a handful of communication channels, the Internet of Things (IoT) is about to exponentially increase the number of potential inputs and channels. The technology that will make managing all this possible? You guessed it – AI.
Developing an AI strategy that expands the omni-channel approach to encompasses the IoT is vital for several reasons.
- New machine-to-machine communication – in the past, the majority of the customer service system has been dependent on human-human and human-machine communication.
With the growing importance of the IoT, this is changing, with machine-machine communication playing a much more prominent role.
- Generation of vast amounts of data – as more and more of our everyday devices and are connected to the IoT, we’ll generate a remarkable amount of data that can be used to refine customer service provision.
From optimising energy consumption in the home to generating highly-accurate, personalised advertisements, AI will be responsible for the sorting and interpretation of previously unimaginable amounts of data – all of which can be used to improve your organisation’s customer service.
- Reducing the range of issues the customer is forced to deal with – the Internet of Things has the potential to revolutionise the customer service system by automating processes to such a degree that the customer need never know that they took place.
For instance, a washing machine manufacturer may have their intelligent product communicate with AI technology when a particular part or component needs replacing. Without ever troubling a customer service agent, the smart device and AI systems can work together to have the part ordered and delivered, saving the customer valuable time and energy and cutting costs for the manufacturer.
As you can see, AI is being deployed in every part of the contact centre to improve performance in several different ways. This means that your 2020 AI strategy will need to be expansive if it’s to fulfil the technology’s potential.
However, it’s also important to get specific. Realistically, cost and resistance to change will prohibit organisations from launching a full AI revolution in the workplace. Instead, you’ll have to focus on development in those key areas that most benefit your organisation. With this in mind, it’s vital that you join the dots and that your strategy looks at ways different AI applications can work together to maximise benefits.