Shall we wait or automate?

Intro

Chatbots: it seems that there are those who love them, and those who aren’t so sure. Whilst the rapidly growing presence of AI in customer service functions is incredibly exciting for us at Sentient Machines, the same cannot always be said for some of those who come face to face with automation online and over the phone. In fact, a report from CGS claims that the majority of those surveyed actually prefer to interact with a human to a chatbot. Reasons for this include the fact that chat bots could be less helpful than a human, and also that interaction with a chatbot was too impersonal.

Such claims beg us to pose the question of whether the customer service space is quite ready for chatbots. Is it best to automate, or wait?

Why companies use chatbots

As discussed in our previous post, companies use automation because they can help speed up processes, and save money in doing so. They can provide quick responses to frequently asked questions, which means:

• there is less of a demand to employ human agents

• human agents are free to respond to slightly more complex customer issues

• waiting time for customers can be reduced to zero

• there will be a 247 access line for customers

Chatbots can cut queues and costs. Surely this benefits both the service provider and the customer?

Bots vs Humans

On the surface, bots appear to be the superior option to human:

• Humans are often slower to respond than an automated bot

• Humans are less available to answer a customer call (ie, they are often talking to other customers and cause queues)

• Humans do not often have quick access to customer records, and so can block actions

However, CGS reports that, to those surveyed, bots lost out to humans simply in their lack of, well, humanity:

• Bots’ answers are not as detailed as those of humans

• Bots are less helpful than humans, and tend to redirect customers to FAQ pages on websites

• Customers don’t always feel comfortable sharing their data with a bot

• Complex, and sometimes personal issues, require a person to solve.

So, what would the ideal situation be?

It would appear that customers want speed in fixing their issues, but they are not so open to impersonal responses to complex issues.

Ideally, then, customers should have access to both chatbot answers, and human resource, depending on their needs. If call reason is captured straightaway, and used to determine whether the call should be redirected to a bot or a human, then a happy medium should be reached.

Ease the transition

Whilst the presence of AI in customer service brings with it undeniable benefits to both customer and company, it also brings with it teething problems and uncertainties. The answer to the question may be a gradual and careful transition: neither waiting nor automating everything straightaway!

Instead, the process of introducing automation to customer service can be eased with various steps towards compromise. Primarily, there should always be the possibility of interaction with a human agent. In other words, a chatbot should not be the only option. The call reason must be what determines whether a customer is redirected to a bot or a human agent, with bots handling simple queries (for instance, ‘how can I pay this water bill?’) and humans taking more complex issues. If you want to find out more about how we are doing this please register your interest here by the 28th September.

Secondly, human agents and bots must be able to coexist in customer service. Agents must be trained in order to be able to deal with the more complex issues faced by customers. If automation takes care of the simple requests, extra time must be taken to ensure that call centre agents are upskilled. Companies should take the time to analyse their data and use it to train up their staff in the type of situations they may face. This way, human agents and bots can be of equal use. If you want to find out more about how you can use Sentient Analytics to improve staff training, and how you can benefit from Sentient Automate on top of that analytics, register here by the 28th September!

Finally, transparency and honesty about data protection is paramount. Customers should trust the companies, in the hope that they will learn to trust the chatbots they meet on their customer service line.

Why AI is a loyal friend to customer service

Sentient Machines were interviewed, along with IBM, Barclays and O2, for a recent report on Artificial Intelligence and its role in customer service. The research report, compiled by The Institute of Public Service, explores both how AI is being used at present, and also looks towards its future potential. Questions are asked about how companies are currently deploying AI in customer service, how customers use AI and their attitude towards it, the attitudes of employees towards the use of AI, and finally steps that businesses should take to fully utilise AI to improve customer experience.

How are companies using AI?

It is claimed that around a third of organisations surveyed in the UK are currently making extensive use of AI, and that we are at the exciting stage of ‘test and learn’ with our endeavours. This means that organisations begin using a relatively narrow set of applications to research and then pioneer new systems. It is apparent that companies generally utilise AI in the following:

• process automation

• analytics to enable business decision-making

• analytics to empower employees

• direct customer interactions

• new ways of experiencing products and services.

The benefits of using AI for these purposes are numerous. For example, systems for process automation and direct customer interactions both increase efficiency and cut time and costs. At the same time, detailed analytics can aid business development by providing feedback on performance and forecasting emerging trends and patterns, to name only two of the many advantages highlighted in the report.

At Sentient Machines, we have seen the powerful potential of analytics in aiding both decision-makers and employees to deliver improved customer service and productivity. As well as utilising bots to automate specific processes, we are seizing the opportunity to develop products centred around the capabilities of AI.

We believe that AI used to enhance human potential drives the greatest change.

How can businesses enable the deployment of AI in customer service?

There are approaches that organisations should take when adopting AI, which can help to enhance the business and ensure that new systems are accepted by employees and customers. Primarily, companies should develop a board-level awareness of AI, and determine the business opportunities that arise from its immediate adoption. Business leaders should trial AI with industry experts to determine the unique and increasing commercial benefits in terms of productivity, customer needs and QA. There are also ethical implications of using AI to consider.

AI can be used effectively to complement and empower employees, rather than just replace them. Automating simple processes and interactions means that employees are free to deal with more complex requests. They can receive a higher level of training and develop a larger skillset to help the company. They should be engaged in the process of implementing the new technology, and involved in the testing and even design stages so as to reassure customers who may have some reservations about the use of AI.

In this way, businesses adopting AI can ensure that they are open with their customers about how the technology is being used. They can even be engaged in the testing process, as, above all, communication from the business is paramount to retaining customer trust.  

Overall

The report points to an interesting future for AI’s role in customer service. There are still varied attitudes towards using AI, with customers expressing that they are more open to its use in certain situations than others, and employees experiencing a “mix of fear and excitement” when faced with the capabilities of AI. It is almost imperative that businesses remain transparent to customers and employees about how and why AI will be used in the business, and to involve and engage employees in the ‘test and learn’ stages.

The report closes with the prediction that AI deployment in a customer experience context will be a key differentiator between businesses, undoubtedly providing benefits to various aspects of the organisation and processes. Sentient Analytics and Sentient Automate can be counted among products that can be deployed to facilitate business development, and used to guide decision making, training and increase efficiency.

If you want to learn more about how Sentient Machines can transform your customer service read here.

How can AI improve QA efficiency by 90% and the quality of your customer service by at least 30%?

Discovering how AI can assist with both internal processes and customer service can drive up organisational productivity. Structuring data analytics can provide the insights that businesses need to monitor quality, formulate predictions, and also make crucial decisions, whilst process automation cuts cost and alleviates stress for both customers and employees.  

Sentient Analytics

Organisations are utilising data analytics to extract information that can be focused on enhanced decision-making and customer service. Companies can leverage AI to extract data much more systematically in order to determine a number of things, for example, the reason for a customer filing a complaint. Equally, they may use authentic data to predict when customers might churn to a competitor, or what they are most likely to purchase.

Sentient Analytics listens to all the words of every conversation in call centre interactions and immediately interprets them in order to try and solve customer dissatisfaction. Our cloud solution provides businesses with an in-depth analysis of conversations with customers, labelling lexical and audio features so that customer sentiment can be monitored for change throughout their engagement with call agents.

The insights provided by Sentient Analytics can help improve the quality of customer service. It can flag problematic conversations for finding swift solutions, or for training call centre staff. With the chance to review examples of both negative and positive interactions, staff can be trained in emotional awareness and ‘next-step’ actions. Indeed, organisations have delivered training based on data analysed by the tool, with outstanding results. A telecommunications client recorded an improvement of quality of service by 30% within a week of using Sentient Analytics, whilst one retail client recorded a 40% drop in negative staff sentiment.

Insights provided by the cloud solution can also aid with cost saving, and business development. For instance, a Fintech client was able to identify 7% of lost opportunities, and use the information in business planning. They could also identify the reason for repeat calls, and as a result they were then able to reduce 24% of calls through automation.

Sentient Automate

The automation of simple processes provides companies with numerous benefits. Using AI saves the cost of a manual process, which is favourable to company productivity. It also increases efficiency, which helps both customers and employees. Equally, automating simple processes means that employees are free to deal with more complex situations, such as sensitive requests where emotional-awareness is necessary.

Using advances in machine learning and natural language processing, Sentient Machines have created a bot platform that can redirect and also automate customer interaction where necessary. The bot uses speech and text analytics, and is able to first detect reason for call and then, depending on the type or complexity of the call, either reroute to a human agent or carry out the conversation itself. The chatbot is able to complete the conversation without human aid for a simple transaction, such as updating account details or paying a bill for example.

A bot can speed up processes and deliver systematic results. Our Fintech customer is estimated to achieve a further call cost reduction of 45% through using Sentient Automate. They were able to automate security checks, repetitive calls, and calls concerning process queries. Our retail client achieved a further call cost reduction of 48%, whilst our telecommunications client has been able to start planning for 24/7 customer support, to further enhance their customer service.

If you want to learn more about Sentient Analytics and Sentient Automate, and how they can transform your customer service, please write to us at hello@sentientmachines.tech

Customer Engagement Expert, Eihab Mohamed, joins Sentient Machines adding additional leadership and focus to commercial client engagement and strategy, in support of Sentient Machines’s growth plans.

Eihab (LinkedIn) is a senior professional in his field, and has worked with a diverse range of customer service & sales organisations, including those in the Financial Services, Media, Telecom, Hi-tech, Healthcare and Automotive sectors. He is joining Sentient Machines to bring his leadership skills and focus on commercial client engagement and strategy.

Eihab’s 30-years experience spans:

• Global contact centre outsourcing (14 years) - where he held strategic responsibility for the development of a number of high-profile, pan-European client operations. Including Phillips, American Express and Olivetti many other leading brands on a UK basis.

• Consultancy (12 years) - in 1999 he formed his own consultancy specialising in customer engagement, and later founded Lighthouse Consulting Europe in 2004, providing subject matter expertise across all aspects of customer management, in sales and marketing operations. Including: GSK, Orange, Cendant Europe, eBookers, Nuffield Health and The Economist Group.

• Telegraph Media Group (6 years) – in 2012 he joined the Telegraph’s commercial division as Customer Engagement Director, at a time when it was transforming its digital propositions, devising customer engagement strategies for sales and service performance.

Eihab will be combining his work for Sentient Machines with consultancy, developing commercial opportunities and providing added value through the practical application of the Sentient Machines platform. Most recently he was Customer Engagement Director at the Telegraph Media Group

UK’s innovation agency co-funds a project to revolutionise call centers with disruptive startup, Sentient Machines

Utilising, ‘Sentient Assist and Automate’ technology, Sentient Machines combines empathy analysis and voicebot interaction, with reliable human backup for complex cases.

Sentient Machines, a London-based startup, founded by Natural Language Processing, AI and Big Data Analytics experts, created in September 2016 with support from an award winning accelerator Entrepreneur First (www.joinef.com),  is developing a next-generation self-learning voice-bot technology aiming to cut customer waiting times by 95%, remove the repetition issue for customers, and improve the quality of service of call centres.   

Almost 70% of all customer contact in the UK and globally is voice. During these voice interactions, much frustration is caused by being put on hold for a long time - 84%, dealing with employees who are inefficient or unfriendly - 81%, and having to repeat your issue to several company reps - 80% (Source: Accenture 2013 Global Consumer Pulse Survey Global & U.S. Key Findings).

Sentient Assist and Automate is a self-learning voice-bot platform that aims to revolutionise the service quality and efficiency of the call centres, simultaneously raising the productivity of call centre staff and improving customer happiness. The platform aims to automate 50-90% of repetitive customer voice interactions. The technology immediately passes on remaining calls and assists skilled customer agents, leading to higher customer satisfaction and retention.

Sentient Machines uses the latest advances in deep learning and natural language processing to learn from the existing conversations, in order to build a voice bot that is emphatic and capable of solving issues for customers in real-time, with seamless integration.

This technology is aimed at industries with a large number of calls e.g. more than 30 agents to handle calls daily. It is applicable to all industries seeking immediate productivity improvements, with first case studies currently being trialed in: utilities, media, fintech, telecommunications, government, and retail sectors.

Sentient Machines uses deep learning to bring customer understanding to the call centre industry.

Please get in touch with Danica at 079 5829 6401 or danica@sentientmachines.tech for more info.