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AI In Call Centre

AI in Customer Service

Artificial Intelligence is evolving at an incredible rate, chatbots are giving way to more advanced voicebots and customer service is beginning to experience the many benefits associated with introducing these new technologies.

Artificial intelligence (AI) permeates the technological solutions for almost every area of application. AI applications have also arrived in corporate customer service. With the help of AI chatbots and voicebots, manufacturers, retailers, helpdesks, contact and call centres can all stay in touch with their customers at any point in the dynamic customer journey in times of digitalisation and increase customer satisfaction.

How does AI optimise the customer experience?

Companies that are thinking about optimising their customer service through AI should be helped with decision-making. And it also helps to have insight into the many ways AI can be applied now.

PABX – unified comms – switchboard / routers voicebots can be literally plugged in to where the IVR would site and provide a much better customer experience. In fact, with AI at the current level, IVRs could be eliminated.

The best AI software also works and integrates in a business’s unified communications platform. For more complex systems, using an API to integrate into datasets is invaluable. Think of an API solution that can talk in natural language to the customer while accessing and validating customer data.

Many companies wonder to what extent their customer service or customer experience can be improved using AI and how it may enhance their business. Other companies simply do not know who to contact to establish what criteria might make AI worthwhile for them.

AI and positive customer experience – FAQs

We all know that a fast response time and the right answers to customer enquiries are crucial for a positive customer experience. AI-supported communication in customer service starts right there.

What can AI support do for my customer service?

Here are some answers to common AI questions about customer service and how it can work to benefit businesses.

Question – Which specific processes are suitable for the use of AI in customer service?

Companies which process a large volume of customer service enquiries are a classic use case. Questions such as “How can I change my password?” can tie up a customer service resource for a significant amount of time.

Another example might be situations such as data updates, where personal data must be updated directly in the CRM system. AI is on average faster and more precise than humans and therefore optimal for use. In principle, artificial intelligence can automate such applications at various levels and can route requests, provide service teams with dynamic response suggestions, or even automatically process requests completely.

It looks and offers a solution to a problem. By following dialogues, it can generate a far greater first-time fix rate and lead to a reduction in call wait and duration time. It can handle multiple lines of calls and far greater volumes. As AI can take inbound calls, it can also make outbound ones as well. AI can work in multiple areas such as: –

– Enquiries
– Technical support
– Account updates
– Information requests
– Bookings
– Retention
– Up sales

This is just scratching the surface of today’s intelligent voicebots.

AI In Customer Service

Question – How much time can I save for my company with artificial intelligence in customer service?

To find out, you first need to take a closer look at the type and number of enquiries; how many simple, recurring enquiries such as cancellations, changes of address, questions about returns or opening times, are processed in a certain period?

Based on existing project data, it can be demonstrated that, for example, a fully automated e-mail in response to a standard request saves the employee an average of three minutes, a partially automated one and a half. This can be used to individually calculate how many hours of monotonous work are lost, which can then be used to process more demanding enquiries.
This demonstrably increases the quality in customer service.

Experience has shown that standard enquiries make up around 50 to 60 percent of total enquiries. Add to this that almost 80% of customers still prefer telephone contact and you can see how these figures grow exponentially. AI with Natural Language Processing and unified communications mean every contact point can be accelerated resulting in significantly higher KPI results.

Question – Can AI improve CX?

Yes. First and foremost, AI enhances and improves both CX and EX (employee experience). Yes, employees benefit as they spend less time with the monotonous standard enquiries and instead, can concentrate on more complex questions where the customer or employee wants to speak to people and where personal contact counts, such as in complaint management or induction programs.

In contrast to humans, the AI is also available for customer enquiries 24/7. Overall, customer service is becoming more reactive, faster and more present.

Question – How do I find out what is the best AI strategy for my customer service?

A full review of your current CX – based on existing data, systems, system requirements, service staff, waiting times to name just a few – will allow a good AI company to uncover the quick wins.

An AI expert will use it to explain all the options for automation. In combination with the business strategy and the individual requirements of the company, goals can be created for customer service which can easily be adapted to customer requests. The goals frequently mentioned by companies are the optimisation of the first response time and the cross-channel standardisation of service quality, all aiming for the goal of a holistic customer experience.

Question – What are the technical requirements for use of AI technology?

Depending on where the customer service can be optimised, there is usually a system to which the AI is connected. For example, a ticket system is required for support in the e-mail and telephony channels. If parts of the chatbot / voicebot are to be automated, they are connected to a live chat system and, in the case of natural spoken dialog, to a telephone system (ACD).

Question – How complicated is the AI implementation?

The deployment depends on the degree of flexibility of the software that a company uses in its customer service. Another factor is the specific use cases that are to be automated with the help of AI and these have to be considered in the implementation phase. Cloud technology makes this much simpler.

A status query such as the current location of a parcel for example, is usually far less complex than a master data change that requires a connection to a CRM system. Basically, the more good quality data you have, the easier and faster the implementation.

With NLP hybrid technologies such as Sovran, even complex solutions can be deployed quickly compared to machine learning for example. Timeframes can be as fast as four weeks, but as a guide, with Sovran, most can be deployed in 12 weeks.

Question – How long does it take deploy an AI CX solution?

If we assume optimal conditions, i.e. there is a lot of good quality data from, for example, a ticket system and the system landscape is flexible, then the first automations can go live between 30 and 120 days.

This is usually followed by a final tune phase in which the system is optimised more and the system is ready to deliver across Omnichannels. In order to have the right expectations, it is important to understand that AI is learning and just as with humans, this takes time and the results are continuously optimised. The difference with Sovran Hybrid NLP is the rate of learning is faster and changes are deployed instantly into production environments.

Question – When it comes to scaling – how easy can existing AI-supported channels be supplemented, which one is the best way to start?

It is possible to start individually with each communication channel – email, chat or telephone – and depending on the company, any one of those can be a starting point. For many businesses, the advantages of an omnichannel system and rolling AI across all of them, is a faster overall deployment which results in quicker increases in CX and greater ROI.

Every situation is different, so a consultation to determine the best route for your business is recommended, to ensure the AI solution is specifically designed around your needs. This is 100% tailored to each business for maximum efficiency.

Question is AI Expensive?

The short answer is no; once any initial research is done to plan out the dialogues, integrate the API and deploy the service, then you run AI as a solution on a ‘cost per interaction’ basis. This cost is significantly lower than full time staff, training and all the other HR costs associated with employees.

There is no capex so for most businesses, entry into the new world of AI CX is affordable and justified. The only doubts are usually about the system capabilities and they really have to be seen to be believed. Ask us for a free live demo and see the system in action for yourself.

Companies can use smart digital assistants to reach the next level in customer service.

Sovran is a leading provider of customer experience AI technology; here are three tips on how to find the right AI solution for your enterprise requirements.

1. Pay attention to natural language processing ability
Despite their intelligence, AI chat and voice bots are still technical solutions. It is crucial for a smooth customer experience, that the customer does not have the feeling of communicating with a lifeless machine. Therefore, interactions should be natural dialog-oriented and intelligent. We recommend a solution that understands people’s natural ways of communicating, rather than a non-scalable, scripted bot. To successfully simulate a natural conversation with a chatbot you need experts in language not code for real natural language processing (NLP).

2. AI software should support an individual customer approach
If you personalise the interactions of your AI solution and specifically use data from other systems such as a CRM, you support the bot in engaging and authentic interactions with customers. It also proves useful if the AI uses the data pool of each customer, to provide the customer service staff with individual recommendations for each one, from the information available. As a result, customers feel engaged individually thus leading to higher levels of CX.

3. Ensure seamless cooperation between humans and bots
Bots will not be able to solve all customer questions. Therefore, the transfer from the bot to a human agent should always be seamless. The bot should pass on information from bot communication with the customer, directly to the customer advisor, so that there are no delays and the human agent is up to date at the start of their interaction. Likewise the agent may also need to pass the process back to the bot to continue and complete a journey such as technical support.

By choosing the right AI chatbot, companies can improve their customer experience, bind customers more to their brand and offer good quality, reliable customer service around the clock.

omnichannel CX

CRM and AI: How intelligent is customer relationship management?

Data is a prerequisite for the success of AI projects. These may be available centrally or in disparate data sets in order to be able to process them further. The catch: The number of touchpoints through which customers can contact companies is growing continuously – however, the touchpoints are rarely completely networked, which prevents a holistic customer view.

True Omnichannel where all touchpoints are connected is a focus for many businesses, but most only have multichannel. Customer contact is a personal preference and customers want to have multiple CX access points such as: –

– Social media
– Customer portals
– Mobile apps
– Contact / Call Centres
– WhatsApp / Messenger / Live chat
– Salesforce

AI can be integrated into all of these areas and more. Most businesses are working on their customer journey and moving from multi-channel to omnichannel, as this then stops challenges with customer silos with the purpose of creating a seamless customer experience.

Customer Experience Management

Customer experience management is really thinking about processes from the customer’s perspective. That means that data management, touchpoint management and customer journey management are integral components.

Marketing automation, customer lifecycle management, analytics and personalisation based on individual customer interactions is paramount. Understanding the value that language and personas bring and creating the right structure of the customer journey, create many additional benefits to both the business and customer alike.

Talk to Sovran about generating maximum added value from the customer’s point of view as well as gains in productivity, efficiency and effectiveness for your company.

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