Artificial intelligence (AI) and machine learning (ML) technology permeate every aspect of our lives, whether we realize it or not. It’s easy to surprise many people with the presence of AI in some areas. They’re baffled to learn that AI helps pollinate crops, brew better-tasting beer, and create new fragrances. Here is how AI revolutionizes business telephony, from Interactive Voice Response (IVR) to sales coaching.
Amazon stores using face recognition to keep track of your shopping basket contents is just a high-profile example of AI. In reality, AI is already everywhere.
The benefits aren’t obvious to most people. Many businesses still happily rely on legacy PBX systems for their communication needs. But in fact, companies using VoIP phone services benefit massively from AI and machine learning tools.
Modern VoIP systems harness the potential of AI in many ways. Interactive Voice Response (IVR), smart assistants, and predictive analytics are just a few examples.
How exactly does this, telephony, work? What are the most common applications of this AI that benefit business? And, come to think of it, what is VoIP in the first place?
The acronym VoIP stands for Voice over Internet Protocol. The technology does exactly what it says on the tin – it routes calls over the internet rather than traditional phone lines.
At its most basic, VoIP – or IP telephony – converts audio signals into digital packages, then transfers them to the VoIP provider. There, they are routed to the recipient of the call and turn back into audio signals.
VoIP, like AI, finds use in more applications than many people think. From WhatsApp calls and Zoom meetings to smart speakers – if you’ve ever made a call via the internet, you’ve used VoIP tech.
However, business-grade VoIP telephony is on a different level. There are dozens of business VoIP services that focus exclusively on meeting the communication needs of companies. All of them are in a tight race to win over customers by providing top functionality and efficiency.
These providers have moved far beyond simple voice calls. Instead, they offer omnichannel communication. Usually, this includes voice and video calls, conferencing, internet fax, email, text messaging, and live chat. And, of course, countless additional features to make users’ lives easier.
This is where AI comes in.
VoIP is the time-and headache-saving-extra offered by business VoIP platforms — VoIP harnesses AI and machine learning.
In fact, VoIP depends on a particular type of AI — natural language processing (NLP).
For the longest time, computers couldn’t understand human language, neither spoken nor written.
Not that people didn’t try.
As early as the 1950s, computer experts attempted to use machines to understand and translate texts. These were pressing efforts during the Cold War. Unfortunately, the technology of the time only allowed for simplistic approaches. Notably, they were often limited to word-for-word processing.
The results could be hilarious. One famous experiment dashed Russian scientists’ hopes for machine translation success. How? Their computer had translated the Biblical, “the spirit is willing, but the flesh is weak” as “the vodka is agreeable, but the meat is spoiled.”
The basic issue: Natural language is fairly unstructured and very context-dependent, even as text. Dealing with voice data is even more difficult. Background noise, unusual speech patterns, individual pronunciation, and regional accents are just some of the problems.
Nonetheless, artificial intelligence has made it possible for humans and machines by voice. Harnessing the computational power of the cloud, AI has become conversational.
We’re not quite ready yet to take on Tony Stark’s JARVIS, but we’re getting close. Siri, Cortana, Alexa, and Google Assistant can attest to that.
AI-based speech recognition already has countless applications, both in the business sphere and beyond. They range from digital PAs that take care of routine tasks to voice-based banking.
The Internet of Things (IoT) is expanding at lightning speed. Fully 50 billion devices are expected to be connected to the Internet by 2020. Increasingly, people can interact with these devices using voice tech. Simply by talking, they can control anything from smartphones and tablets to fridges, ovens, and home security systems.
Much the same is true for VoIP business phone systems. Here, NLP and conversational AI have opened up entirely new avenues for productivity features.
Transcription simply means turning speech into text. It’s one of the most straightforward applications of AI voice processing in VoIP systems.
Voicemail-to-email and voicemail-to-text are now standard business VoIP features. Either will transcribe the messages left when callers didn’t reach the person they were hoping to talk to. Then, they’ll send the transcript to your inbox or chosen messaging platform.
Users save time. Once, after returning from a vacation or business trip, they might have spent an hour listening to the backlog on their answering machines. Today, they can quickly glance through everything in their inbox, prioritize, and file messages away.
What’s more, AI can transcribe entire conversations and file them away for future reference. This virtual paper trail can be incredibly handy in case of disputes or to follow up on individual clients.
Transcribed conversations are also a boon for customer service. Agents can reach back to the details of past interactions with every caller and pick up the issue’s thread. Customers don’t like describing their problems or needs over and over. They strongly appreciate being able to get straight to the point. A 2019 survey found that 96% of customers agreed that “it is important being able to return to and pick up a customer support conversation where it left off.”
Many modern business phone platforms also integrate with Customer Relationship Management (CRM) systems such as Salesforce or HubSpot. This means that all conversations’ AI transcripts can be added to the wealth of other data on every customer.
Data can also flow from CRM to connected AI-powered VoIP features. For fluid, real-time personalization, they can supply agents with the necessary details.
Not only does AI enable sales representatives to make use of past, transcribed conversations. Some applications go as far as to offer sales coaching in real-time.
AI interfaces can transcribe and analyze calls between customers and company representatives even as they happen. These AI interfaces can supply the agent with all the information they need, saving them from having to go rooting around for it.
Past purchase history? Got it. Date of the last customer call. Here it is. The serial number of the device the customer has been having trouble with. There you go.
Every agent basically has a personal assistant handing them important information before they even have to ask for it. The specific information provided can make interactions with callers much smoother and more effective. In turn, this increases satisfaction on both ends of the line.
Plus: These virtual PAs can also take over routine tasks from taking call notes to scheduling follow-ups.
What’s more, AI can analyze the best-performing company agents’ calls, from customer service to the sales team. By looking for patterns that had callers respond positively, it can suggest good responses. Should an agent ever be at a loss for what to say or do during a call, AI can recognize the fact. It’ll then serve up a menu of time-tested phrases and actions to proceed.
Overall, these smart virtual assistants can empower human agents – by giving them tools, boosting their performance, and making their work less monotonous.
Another use of AI-powered business telephony tools is to allow callers to reach who they want to talk to with minimum frustration.
After the fourth round of “Please press 1 for…” anyone calling a business – or rather, trying to contact the company – will be grumpy. Once a company representative finally does pick up, the call representative will have to deal with a customer who is already irritable and short on patience. Not the best of conditions.
Businesses can avoid the initial unhappy customer aggravation condition, thanks to Interactive Voice Response (IVR).
Instead of forcing a caller to listen to a menu of choices, IVR allows them to state their call’s purpose in their own words. Next, AI analyzes the underlying intent. It then transfers the caller to the best-matching company representative currently available.
AI can also make the lives of callers easier in other ways.
Smart auto-attendants can prioritize calls with high urgency, classify them by topic, and even identify people’s dominant emotions from their tone of voice. They can give agents a heads up that they will be dealing with a ballistic caller and equip them with the tools to handle them.
Finally, AI can eliminate the need for human action in the majority of customer service calls. Conversational AI interfaces can take care of common service needs. Examples are FAQ answers, troubleshooting, password resets, making or rescheduling appointments, refund requests, reservation adjustments, and ordering products.
Reducing many of the interactions reduces the call volume human agents have to deal with. This allows them to focus on more complex requests.
A 2019 article in the Wall Street Journal showcased TD Ameritrade’s experience with adding conversational AI ever since the company hasn’t had to hire any new agents to deal with calls. “Chatbots can answer basic questions about trade statuses and resetting passwords,” the WSJ reports, “while humans help with more complex problems related to taxes and beneficiaries.”
Research published in Marketing Science in September 2019 came to similar conclusions. One result was that “undisclosed chatbots are as effective as proficient workers and four times more effective than inexperienced workers in engendering customer purchases.”
Finally, AI can add invaluable analytics features to VoIP business phone systems. This is not really a surprise: AI analytics is everywhere these days, from car park management to automatically personalized content curation on websites.
VoIP phone systems tailor analytics specifically for the communication needs of businesses.
Users can gain in-depth insights into aspects from agent performance to customer satisfaction. A core tool is sentiment analysis, used for objective analysis of customer feedback. Data can be combined from call transcripts, feedback forms, or even reviews posted elsewhere. Sentiment analysis isn’t limited to text, however. The tone of voice and – for video calls – even body language can be mined.
Such analytics can be done regularly. AI systems can automatically generate reports at fixed intervals for supervisors to assess team performance. They can also make them instantly available after each call, such as feedback to company representatives on how well they handled any particular call.
Combined with CRM data, VoIP AI analytics allows deep insights into customer behavior. Grouping them into sub-audiences is just a first step. It can further predict their future engagement with the company, likely buying decisions, and communication patterns.
Artificial Intelligence has become an integral part of numerous functionalities offered by VoIP business phone service providers.
There is little AI involvement in the core VoIP services – voice and video calling. Nonetheless, it strongly affects which providers dominate the market.
Not long ago, features like voicemail-to-text or advanced call analytics set a provider apart. Now, they are practically standard. To stay competitive, VoIP providers are racing to integrate cutting-edge, AI-based tech into their platforms. The stakes are high: VoIP, business phone services, are expected to keep on growing at a CAGR of 13.4% – and to hit $30 billion globally by 2025.
Whoever offers the most advanced features is likely to become a client favorite.
It’s fair to say that AI now shapes how VoIP systems interact with callers just as it changes how customers interact with businesses in general.
Businesses, their agents, and callers all stand to gain. With AI tools, tasks, and issues can be dealt with effectively and efficiently, improving the customer experience all around.
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