New technological improvements are advancing the ecosystems within call centers and business support centers. The emergence of artificial intelligence (AI), data analytics and visual support have each been significant drivers of innovation in this industry. The modern consumer expects their issues to be resolved promptly and effectively.
Due to the ongoing COVID-19 pandemic, customers and businesses alike are more reliant on contact centers than ever to assist when a problem arises. The majority of call centers are now operating on a remote basis; this has been enabled by an increased ability to scale up cloud-based contact centers. It is essential that businesses innovate and respond in order to adapt to these unprecedented times.
The following are all opportunities to help enterprises to revolutionize their business in order to cope with increased demand, along with new and diverse challenges:
1. Omnichannel Communication
Omnichannel or multichannel contact centers deliver a seamless experience for customers across multiple channels – for example, voice, social media, and SMS.
Consumers expect to be able to contact companies through their own preferred communication channels. Some customers may also choose to use a variety of channels when interacting with organizations.
Nowadays, it is expected that agents are aware of all previous communications and that they are up to date with the relevant customer details instantaneously. This includes basic details such as name and address but also covers elements such as the consumer’s preferences and prior reasons for contact.
This 360° view of the consumer empowers call center agents to provide support across multiple channels in a highly personable, intelligent and timely manner.
The goal of omnichannel contact centers is to deliver a consistent service that ensures a high level of accessibility for consumers and increases satisfaction.
2. Intelligent Visual Support
Visual engagement is becoming a much more prominent tool within the customer service industry. Visual support through digital means can include co-browsing, live video or even augmented reality. Visual support enables agents to see exactly what the customer is seeing in real-time and guide the customer in resolving the problem for themselves.
This provides a visual experience for both parties, leading to a deeper and more intimate understanding of the situation, and the result is a quicker time to resolution. Many companies choose to collect this visual information and use it in algorithms for building visual support bots which may become a crucial part of future customer service.
The ubiquitous nature of platforms, devices, and networks has driven the success of intelligent visual support technology. At the moment, this is an exceptionally powerful tool for organizations to utilize as the majority of business operations are now being conducted remotely. Intelligent visual support technology can allow businesses to virtually assist their consumers, instead of having to send a support worker to the individual’s address in order to rectify the problem.
3. Sentiment Recognition
Sentiment analysis can accurately uncover the sentiments being expressed by the customers of a call center. The impact of this is even greater when combined with predictive analysis. AI can capture unrefined data around customer interactions and feed this into an analytical engine which can then translate the information and recognize specific sentiments and emotions.
This process can often identify the sentiment faster and more accurately than a call center representative is capable of doing. Sentiment recognition normally focuses on factors such as tone of voice or specific keywords expressed to accurately pinpoint the emotions experienced by the caller.
This can be used to intelligently route calls to the correct agent and to create an automated ticket prioritization system.
Agents also have the ability to better understand the customer based on an analysis of the information presented to them. This allows them to respond in a more empathetic manner, which can often help to reduce the aggravations that an unhappy customer may be feeling.
4. Automated Messages
Interactive voice response (IVR) systems can be combined with AI to advance problem resolution. Natural language processing and machine learning are used to identify customer requirements and to provide the correct response, instead of presenting the customer with a pre-specified set of options.
Automated responses and simple solutions can then be provided to the customer using voice bots which have significantly lower costs for the business.
The ability of automated messages and voice bots to promptly resolve customer-impacting issues leads to more satisfied customers. The workloads of agents are also reduced and they are instead able to spend more time handling complex customer calls.
5. Blended Agents
An automatic call distributor (ACD) can identify increased volumes of both inbound and outbound calls. When an organization uses blended agents who are trained in both inbound and outbound calls, the ACD can pass the call overflow on to any agent, even if this is not their predominant area of focus.
Where there is no ACD in place, a manager can make the decision to switch some outbound agents to inbound calls and vice versa in times of heavy call volumes. Blended agents are very beneficial in contact centers that have few seats.
This is especially important in these smaller contact centers which are particularly susceptible to low levels of occupancy and therefore lower levels of efficiency. Blended agents may also be able to use a script to assist when handling calls that are not within their primary area of focus.
6. Data Analytics
Technology and the ability of data analytics to accurately analyze workflows and agent responses have ensured that supervisors now have more time to focus on other aspects of the business, such as lead generation and administration.
It also provides for a much more efficient and prompt analysis of agent performance and responses. This allows problems to be resolved faster than they were in previous times. Notably, speech analytics is proving to be a hugely beneficial form of data analysis.
Speech analytics can uncover inefficiencies in current scripts, and make process improvements, such as developing systems for call center agents to utilize in order to achieve the desired call outcome.
7. Smart Desktops
Previously, agents needed to access several different systems in order to acquire all the necessary data on a consumer. Smart desktop solutions remove the need to do so, by using a single sign-on and a more intuitive user interface.
This reduces advisor effort by guiding the agent and providing all necessary query and consumer information instantly. Ultimately, this has been proven to greatly increase productivity, lower wait times and increase customer satisfaction.
Smart desktops also use a more simplified transfer process, making it easier and more seamless to connect the customer with a colleague who may be more skilled in a particular area.
Contact centers should utilize some, if not all, of the aforementioned solutions in order to increase the levels of both first contact resolution and customer satisfaction, as well as lowering call handling time and agent attrition.
These innovative solutions can revolutionize any contact center and help to bring it into the modern world. During this crisis period, they are especially powerful tools and can be very helpful when operating in a remote work environment.
New to Spearline?
If you are new to Spearline and would like to find out more about how you can benefit from our platform, we would love to speak to you. Please send us a brief message, and we will be in touch with you shortly.
Spearline is a technology company that proactively tests toll, toll-free and premium-rate numbers for audio quality and connectivity globally. We support business sectors, such as contact centers, conferencing services, and other applications, in successfully connecting with their customers. If you are interested in benefiting from our platform, .