Partners  |  Career  |  Support

EN  |  IT  |  PT

EN     |     IT         PT

How a fast automated discovery of user intent helps the whole customer service chain

How a fast automated discovery of user intent helps the whole customer service chain

How a fast automated discovery of user intent helps the whole customer service chain

May 6, 2021

If you read literature about customer support, especially as it relates with self-service support, you frequently find the expression “user intent”. But what is a user intent? We define it as the objective that a consumer wants to achieve when performing a search on the internet, browsing a website, or contacting a company service department. With the rise of automatic systems to let users self-serve in their relationship with companies, how intents are discovered by the system and managed has become paramount.

There is no doubt that having oneself understood quickly when looking for something is important, but typically there are many ways to express a need, a complaint or a desire and people will use them all (even assuming they know exactly what they are looking for, which is not always the case).

So, one of the biggest challenges for automation services is to map these expressions and identify the real motivation behind them.

Of course, when calling a company, users could be directed to speak with a human agent who will quicky determine the user’s need, but this is expensive and does not scale, so automated systems have been available for decades to “qualify the call”, discovering the user intent, and route the call to the most appropriate service. For many years this meant menu-based systems interacting with users through tones, but more recently Artificial Intelligence systems have become more and more able to converse with people, reducing the steps necessary and delivering a much more pleasant, agile, and accurate customer experience.

So, interest and investments in Conversational AI able to discover the user’s intent are increasing significantly in the various sectors in which it operates: from the development of algorithms and intelligent systems to advertising and Inbound Marketing strategies. But how, in fact, does the intent discovery work, how can this technology contribute to serving your company? This is what we discuss here.

Other Articles

How do intelligent systems identify intents?

When a user reaches an intelligent conversational virtual agent, the experience is very different from an old IVR, although the objective of the first part of the call is the same – identifying the caller’s intent. A conversational AI Virtual Agent will start the conversation with an open question, something like “Good morning, you have reached Company X, how can we help you?”. Users are thus free to express their need in any way they like.

When they speak, their sentence is first transcribed from voice to text by the Virtual Agent, then sent to a conversation engine for analysis. Engines can be of different types, but all of them compare the sentence with a knowledge base of possible requests, related to the capability of the service. Of course, the number of possible intents is not infinite and in fact they are the same that can be served by an older IVR system. So, the “domain” on which the Virtual Agent searches for the intent is limited, and this facilitates the search.

It is possible that the caller has already specified all that the system needs to know to correctly identify the intent, but very often this is not the case. For instance, a system to automatically book an appointment will need to know the name of the user, the type of appointment, the location, the date, and the time. No-one would say all this in the initial sentence. But a well-designed Virtual Agent will be able to narrow down the possibilities gradually to get to completely identify the users’ intent and service their need.

One advantage of Virtual Agents over old IVR systems is that the pieces of information can come on any order. So, continuing with the appointment booking example, the user may say “I would like to reserve an eye doctor appointment”, and the Virtual Agent can then ask them what day they want it, where, and what is the preferred time (assuming that the user’s phone number is already in the database and so the system knows who it is talking with). But the user could also say: “I need an appointment tomorrow”. In this case the Virtual Agent would reply: “what type of appointment? We cover ophthalmology, dermatology and radiology”, and then proceed to collect the rest of the information.

The conversation will continue until the Virtual Agent has collected all the information necessary to provide the service, or if there are complications, at least the Virtual Agent will be able to forward the call to the correct human agents – in this case, the ones serving the Ophthalmology department.

The advantages of an autonomous voice service

The ability of Virtual Agents to identify intents quickly and precisely provide several advantages for companies, especially ones with a high volume of customer interactions and several departments. To start with, it is not only the intent that the Virtual Agent identifies, but also what it is called “entities”: the pieces of information that make providing the service possible. In the example above, the intent is the type of appointment that the user seeks. Entities are instead the date and time, and location. Having the complete set of information often enables the Virtual Agent to complete the service without contacting a human agent, thus saving time and money.

Even when the service is not provided completely by the Virtual Agent, interactions are routed to the correct human agent queue with a much higher precision, greatly reducing the percentage of calls that have to be transferred to another department. This also saves money and time, not to mention providing a better customer experience.

Finally, the ability of Virtual Agent to collect most of not all the information necessary and transfer it to human agents together with the call also helps keeping the duration of calls shorter and save money.

Other advantages include the ability of the service to scale to meet demand, much faster than what a human agents-based contact center can scale. If a service peak is coming, due to the season or a scheduled event, or even in emergencies, it is easy to just increase the number of Virtual Agents that come in perfectly prepared and trained as the ones already in use. This will buffer the traffic increase on the “real” contact center, as a high percentage of the peak calls will be resolved in self-service mode and the peak on human agents will them be smoothed.

Virtual Agents also remove the limitations of day and time, since they work 24 hours a day, 7 days a week. Continuous service prevents demands from being “dammed” at the ends of the week and contributes to customer satisfaction, as most of their needs are met at any time and without waiting on the phone.

Virtual agents acceptance

Virtual Agents of all types are becoming more and more common, and thus accepted by the general public. People are increasingly used to controlling computer services by voice, from smart speakers to search engine searches to interactions with virtual agents over the phone. So, Virtual Agents are accepted by the public immediately, and gladly. A conversational experience not only contribute to a more human service, but also make the consumer’s routine more practical. Many problems can be solved without the customer having to click on a single button.

Understanding of the customer journey

For a company to be able to provide an excellent customer service, it needs to know its customers and their journey, while seeking support – the path taken from the first contact to when their need is met. This understanding allows organizations to deliver exactly what their customers are looking for at each stage of the journey.

Until the recent past, it was not possible to obtain this knowledge with satisfactory precision since the available data was very limited, especially on the telephone channel. The best companies could was to record calls and then select a sample to analyze, which was expensive if they wanted a more complete picture or necessarily incomplete.

A Virtual Agent however works on text, and so all calls are transcribed. This allows to use text analysis tools, also based on Artificial Intelligence, to monitor consumer behavior in detail and gain valuable insights.

About Interactive Media

Founded in Italy over 20 years ago, and with offices in Brazil and the USA, Interactive Media is at the forefront of Conversational AI technology and processes hundreds of millions of customer service conversations a year with its Virtual Agents, in different countries and languages.

Now that you understand the importance of the user’s intent, it is time to see up close how Virtual Agents interpret and use it in service. Get in touch with us and get to know OMNIA, our complete solution for the development, deployment, training, management and monitoring of Omnichannel Virtual Agents.

Other Articles

How PhoneMyBot adds value to your chatbot

How PhoneMyBot adds value to your chatbot

Using robots to streamline business processes is no longer science fiction. The field of Robotic Process Automation (RPA) is in full development and more business processes are handled by bots every day. The customer service flow is also participating in this trend,...

read more

Interact with us

Subscription

Receive our exclusive content:

How PhoneMyBot adds value to your chatbot

How PhoneMyBot adds value to your chatbot

How PhoneMyBot adds value to your chatbot

April 12, 2021

Using robots to streamline business processes is no longer science fiction. The field of Robotic Process Automation (RPA) is in full development and more business processes are handled by bots every day. The customer service flow is also participating in this trend, as chatbots are becoming an integral part of it and gain more and more space in companies that seek to optimize resources and leverage AI to increase their performance.

But don’t think that technological evolution is over. In addition to text inputs, voice bots promise an even better and more productive experience. In this post, we will elaborate a little more about how this works.

First, we will explore the chatbots development journey, detailing how chatbots are being adopted at an explosive pace. Next, we will introduce PhoneMyBot, Interactive Media’s intelligent voice enablement solution for chatbots. Finally, you will learn about the differentials and advantages of the technology that is revolutionizing corporate service.

Other Articles

The chatbots journey: how they conquer the market

The digitalization of businesses has had, and continues to have, profound impacts on their operation processes. Tasks that, just a few years ago, demanded printing dozens of reports and many hours of analysis are now carried out in a few minutes – thanks to the support of innovative technologies, such as Artificial Intelligence (AI) and Machine Learning (ML).

Chatbots are another great example of a tool that is gaining acceptance and scale during this Digital Transformation. The focus of chatbots as a solution is very specific, as well as important: automating and optimizing service tasks, enabling a leaner and more efficient operation, while providing an excellent experience to customers using them. The proliferation of chatbots is not only due to their usefulness for businesses: they have become much more proficient in conversing with the users in a natural way, understanding the users’ requests and providing useful services to the public.

A Salesforce study, published in 2018, found that 53% of corporations expected to deploy chatbots within 18 months. And in fact, usage of chatbots is skyrocketing. It is estimated that 1.4 Billion people are using chatbots on a regular basis now, and by the end of 2021, 85% of chat-based user interactions will be handled without the intervention of a human agent. The investment in new chatbots in 2021 will be $5B.

PhoneMyBot: what is the technology and how it works

Currently most chatbots only understand text and cannot be used with voice.

PhoneMyBot provides an instant enhancement to the new generation of corporate chatbots. The solution is hosted in the cloud and efficiently expands the reach of chatbot to include voice channels. This includes the telephone channel which, according to surveys, is still the most used channel for consumers who need to solve problems, but it also encompasses channels – such as WhatsApp, that can send recorded voice as messages.

Livio Pugliese, CEO for North America at Interactive Media, points out that the solution integrates different services: it receives calls from the telephone network, transcribes speech into text, sends the text to the chatbot, receives the response from the system and transforms it into speech, transmitting it to the user. The process sounds natural: the whole flow – from voice to text and from text to voice, with the support of Artificial Intelligence – feels like a common conversation over the phone, for the comfort and good customer experience of those on the other end of the line.

 “PhoneMyBot can be used by companies that have already implemented a chatbot or by software vendors that offer chatbot platforms to their customers”, adds the executive. Most organizations that have a chatbot in operation continue to receive voice calls and answer them with human agents. Most of these calls would be manageable with the existing self-service operation as delivered by the chatbot: not doing so burdens the process and hinders the speed of service.

Interactive Media’s solution is therefore the best alternative for these organization to expand their self-service capabilities to the voice channel, while ensuring customer satisfaction. “PhoneMyBot derives from a unique combination of skills: we are experts in conversational AI but we also have a strong background in telephony and in speech technologies,” says Pugliese.

PhoneMyBot advantages

PhoneMyBot can greatly contribute to resource optimization – whether physical, financial or human. In the financial sector, for example, it is estimated that the deployment of chatbots and voicebots will generate savings of US $ 7.3 billion by 2023, channeling investments to other equally strategic areas of the companies.

In addition to the high potential for return – in the short, medium and long term – one of the biggest differentiations of the Interactive Media solution concerns usability: from the technological infrastructure to the management and monitoring portal to the commercial functions, everything works in order to provide a smooth integration with the existing applications and operation of the system. Text and voice complement each other to generate an incredible experience from end to end.

“Technically, the API to connect to the chatbot is very simple and easy to integrate. Commercially, Interactive Media offers a free trial version and a pay-as-you-go model, so businesses can start small and grow organically, as they see the value in the service. In technology and cost-benefit, there is no similar offer available on the market today “, reinforces the CEO for North America.

Conclusion

In the highly volatile technology sector, change is the only certainty – and chatbots are an engine of change. With the popularization of machine learning and Artificial Intelligence, robots are gaining ever more space in the corporate world; now bots have also gained a voice.

The use of conversation AI for customer service has democratized the advantages of technology: while companies accelerate their processes and reduces operating costs, customers are gaining excellent contact experiences. The old IVRs (Interactive Voice Response), which required user to listen to a long menu of options, have finally become obsolete.

“Based on the Interactive Media’s experience, virtual agents are able to solve up to 80% of the problems, which ends up releasing human agents from a considerable number of telephone contacts, and especially the most repetitive, dull ones” explains Pugliese. “For the remaining 20%, those responsible receive information that allows for a shorter, more empathic calls, in line with customer expectations. The net result: everyone wins. And with PhoneMyBot, companies can use the chatbot they have already deployed to provide a phone-enabled virtual agent service” concludes the CEO. The initiative could not be better suited to a world that values ​​the disruptive and demands competitiveness – without neglecting the experience.

Was the content useful and helped you to rethink the service strategy – by text and voice – of your business? Excellent! Remember that it is essential to have modern, reliable, and efficient tools. Get in touch with us and find out how Interactive Media and PhoneMyBot can help you face new market challenges.

Other Articles

How PhoneMyBot adds value to your chatbot

How PhoneMyBot adds value to your chatbot

Using robots to streamline business processes is no longer science fiction. The field of Robotic Process Automation (RPA) is in full development and more business processes are handled by bots every day. The customer service flow is also participating in this trend,...

read more

Interact with us

Subscription

Receive our exclusive content:

OMNIA – the Interactive Media platform for Conversational AI Virtual Agents

OMNIA – the Interactive Media platform for Conversational AI Virtual Agents

OMNIA – the Interactive Media platform for Conversational AI Virtual Agents

March 12, 2021

Interactive Media has long operated in several related areas of the telecommunications field. We started out with computer telephony applications, interacting with the public via tones and delivering audio content on the telephone. This necessitated the development of a platform that excelled in flexibility and reliability towards the edge of the telephone network. Later, as our software was adopted more and more by carriers (especially Telecom Italia), it migrated to the core of the network, delivering services from a more central architectural location. For this, our platform gained robustness, high availability, and advanced integrations towards core network nodes. We also added the most recent version of protocols to control media and call control functions in other nodes – VXML and CCXML. As a package, this software has become one of the most advanced carrier-grade Media Servers available.

Meanwhile, the world of telecommunications and contact centers was evolving, looking for better customer experience. We were among the first to provide conversational Virtual Agents using natural language processing to allow our customers to have a natural conversation with their customers, substituting the old tone-based interactions with an open voice dialog. Our first Virtual Agents were operational 10 years ago and since then we have constantly enhanced and updated our offer. The result today is a platform to create Conversational AI Virtual Agents quickly and reliably, defining their workflow and semantic domain, training them for the task at hand, deploying and continuously enhancing them – on all channels. We call this platform MIND, which stands for Multimodal Interactions through Natural Dialog.

The combination of both technologies provides all that is needed for successful omnichannel AI Virtual Agent implementations allowing consumers to interact with companies conversationally, in any language and on any channel. This is why we call the whole platform OMNIA – Latin for “all things”, but also because it provides Omnichannel Artificial Intelligence.

Other Articles

OMNIA architecture

OMNIA plays in the customer experience / contact center arena. Clearly, it is only a component of the whole solution that companies use to ensure the best experience to their customers and it has to play nice with many other systems: contact center suites, IVRs, CRMs, corporate directories and authentication systems. Integrations are thus an essential part of OMNIA and we have worked hard to ensure that they are easy to implement.

For starter, OMNIA comes pre-integrated with several of the most common contact centers technologies in the market: as we encountered contact center software suites from different vendors being used by our customers, we integrated with them and optimized the integration in OMNIA. It also supports the protocols to connect with IVR systems and with several CRM platforms.

Interactive Media decided long ago that it did not make sense to implement speech services or our own. Text-to-speech and speech-to-text (TTS and STT) used by OMNIA for its Virtual Agents are becoming completely commoditized, with quality rising rapidly and more and more offers on the market. So, OMNIA integrates with several of the main players, with the ability to use different services for multiple use cases. In this way, it is possible to understand the answer to an open question to the customer (eg How can I help you?) and a more specific answer (such as telephone number), because of the ability to switch to the most appropriate service task during a call. Consequently, we have a higher percentage of speech recognition and less need for referrals to human agents, resulting in an impressive ROI in operation.

In addition to the Media Server and MIND, OMNIA comes with several useful tools and modules. These are shown in the figure below as part of the overall architecture, together with the main integrations with Channels, Speech services and Contact Centers. New integrations are being added all the time.

The Media Server is OMNIA’s front-end service. It streams all media content and implements all the integrations to manage the services of third-party modules. It is also a web server and provides dynamic HTTP pages for multimodal interactions.

MIND acts as an application server to the Media Server, controlling both the call setup and the media that is played in the calls. The MIND environment is where the Virtual Agents live: the MIND AI engine evaluates the utterances from the caller (that have been transcribed into text) and decides what the Virtual Agents says next, identifies intents and provides the self-service answers.

Developers use the MIND Studio and MIND Skill modules to create and train Virtual Agents. The MIND Studio is a web GUI to create the Virtual Agents flow and manage all aspects of their deployment. The MIND Skill focuses on the Virtual Agents domain knowledge: the semantic elements that allow the AI engine to understand the users’ utterances.

OMNIA also provides a Business Intelligence module, which allows non-technical personnel to monitor the Virtual Agents KPIs and change some aspects of its service – for instance if a product has been discontinued and the Virtual Agent should change the way it talks about it. Finally, the OMNIA OAM module is for administrators to monitor and control low-level aspects of the services, receive and react to alarms and reconfigure the service if needed.

OMNIA projects: reliability, performance and high intents recognition

At Interactive Media, we have a long experience in using OMNIA (and its predecessors) to build the conversational experience that our customers want for their customers. Many factors come into play: the customer’s organization, the service they provide, the number of intents that have to be recognized, the figure of the customers calling in, and the lingo that the company uses.

We have become experts in analyzing all these factors and building the correct structures for a quick and effective implementation and we have codified the project strategy in a master plan, that we use over and over. It is not an automatic pilot for reaching perfect Virtual Agents, but it makes for a fast and predictable deployment – in a matter of weeks instead of months, and with well-defined milestones and activities.

We realize that we are not the only company offering a platform and services to implement, deploy and run Conversational AI Virtual Agents. In fact, the field is rather crowded: in the past few years many have joined us. But we believe that OMNIA gives us an advantage, in terms of ease of use, reliability, performance in recognizing the callers’ intent and in scaling up to millions of calls successfully served per month.

We can’t wait to train OMNIA to provide a delightful experience to your customers too: give us a call! 

Other Articles

How PhoneMyBot adds value to your chatbot

How PhoneMyBot adds value to your chatbot

Using robots to streamline business processes is no longer science fiction. The field of Robotic Process Automation (RPA) is in full development and more business processes are handled by bots every day. The customer service flow is also participating in this trend,...

read more

Interact with us

Subscription

Receive our exclusive content:

The history of call qualification – a perspective

The history of call qualification – a perspective

The history of call qualification – a perspective

November 3, 2020

Someone was asking me about the techniques that in time have been used to qualify contact center calls – to understand what the caller wants and so route the call to the best group of agents in the contact center operation. I must say I wasn’t there for the beginning of this story, but certainly I am there now, so here it goes… 

One can say that call centers got started with the widespread availability of touch-tone enabled handsets. DTMF (dual tone multi-frequency) was invented by Bell Systems for signaling in the early ‘60s and the first DTMF enabled handsets were sold to the public in 1963. But it took many years before touch-tones telephones were widespread enough for use in applications other than calling. It also took many years for computers to become powerful enough to run software able to distinguish the tones, while also managing other aspects of the calls and the database queries and screen pops that allow the agents to be productive, at a manageable cost.

All these technologies converged in the 1990s. Several companies started to develop PC boards that could connect with the telephone network, using analog or time-division multiplexing (TDM) adaptors to talk with a switch. These boards communicated with other boards were packed with digital signal processors (DSP), programmable chips that could independently detect signals like DTMFs on the telephone line and provide the relative events to the software running on the host. At the time, I was working with Natural Microsystems, a Massachusetts company that was a pioneer in computer telephony.

Other Articles

Since this architecture was geared towards PCs, whose cost was falling while their power was raising fast (following Moore’s law), companies were able to set up contact centers at a reasonable cost. It was the dawn of industrial customer service: people started to be able to use their phone to try and resolve issues or set up services that previously needed an in-person visit to an office, or sometimes writing letters with no guarantee of a response.

However, while technology certainly enabled the birth of call centers, the humans work to make them function was also completely new. Agents had to be recruited and trained, a new organization geared to make answering calls as efficient as possible had to be developed. As with other sectors of industrial work, there was a need for specialization: agents could not be experts of everything and so a need arose to qualify calls for routing to the groups of agents in charge of specific topics.

The Automatic Call Distributor (ACD) was born, fronted by an Interactive Voice Response system (IVR). This was the beginning of the new century, the golden age for companies like Avaya and Genesys, innovators in the call center software field: every airline, every bank, every telephone carrier suddenly wanted a call center and business was booming.

(Call center is now an old term. Successive generations of marketing lingo have changed the name of the thing, first to contact center – with the addition of messaging and chat to the voice channel – then to customer experience (CX). We’ll change terminology as appropriate…)

So, companies wanted a call center, but to do what? This was a new capability and initially it was driven by technology (because we can) and by competition (because our competitor is doing it). Consumers were probably pleased but the ability to call a company was not seen by the public as a reason to buy its products or services more. Since calls were mostly to complain about a troubled offer, it was rather a double negative: mitigating problems, try not to lose customers. This does not bring in new money, so for companies, the call center was a cost, not an investment.

But they couldn’t go back: the genie was out of the bottle and the public was used to it. And so, in order to reduce costs, contact centers were operated on a shoestring budget, with the bare minimum of agents. At the same time, callers needed to be filtered: only the most motivated, and persistent, could be allowed in and IVRs were the perfect tool to provide this filter. And so, the menus got longer and more confusing, music on hold was invented (it could be seen as an advance, but for the low bandwidth of telephone lines that are geared to human voice and not music. This is why it sounds horrible.) and the wait and bad experience necessary to reach call center agents became a widespread meme.

Occasionally, there were attempt at improving the situation. In the late 2000s, texting and messaging app started to be used more and more as people switched from fixed phones and mobile “feature phones” to the first smartphones. Call center software vendors incorporated messaging into their product, which became “contact centers”. Also, the first limited voice recognition software started to appear and suddenly people were asked to “press 1 or say “sales”, press 2 or say “support” – not very user-friendly actually since the time it took to read a menu grew substantially. But something was also changing in the companies’ attitude towards their customer support function.

Slowly, customer support was seen as more of a competitive advantage. The first step was the recognition that, with products and services largely equivalent between different players, consumers could switch allegiance quickly and easily. Customer service was an area of possible improvement, and one in direct contact with the public. I was working at Genesys then, and I remember the spiel we adopted in customer conferences: how customers were a lot more likely to churn after a bad experience, so it was imperative to avoid one.

But this was still a negative approach: the real turning point was when companies started to factor in the customer experience not only as a cost, but also as a way to increase revenue, switching the contact center from a pure cost to be a revenue-generating activity. The switch is all in the accounting, but it’s fundamental: now there are reasons to invest more in the contact center and measure the overall revenue brought in by a better customer experience.

Which brings us to the latest development: the rise of conversational AI for customer service. Conversational AI was made possible by advances in natural language processing, understanding, and rendering, and the advent of Cloud architectures and the abundance of data available to “train” the Artificial Intelligence algorithms. Conversational AI changes the paradigm of how calls (or text-based interactions) are qualified, and in many cases allows customers to self-serve. The key is to understand the natural language that people use. This allows the computer program (Virtual Agent) to find out the intent of the call very quickly because the service domain is treated as a flat field and not a tree. Language is much more expressive than tones or single words and so an interaction goes through the qualification phase in 1, 2, rarely 3 question-answer exchanges. At this point, the Virtual Agent has enough information to either engage a computer application to satisfy the customer or forward the call to a human agent.

The customer experience is much better, and costs are also reduced for companies. This is because the biggest cost in contact center operation is the agents. Conversational AI has been proven to help boost agents’ productivity, and increase their job satisfaction: routine, boring interactions are best served by the Virtual Agents, which also collects information for the human agents to use. Agents are left with more interesting and engaging conversations.

But having more productive agents means that fewer agents are needed; happier agents means that turnover is reduced, with less need to train new agents since old hands are more able to solve customers’ problems faster. At the same time, fast, frictionless experience is what customers want when they contact companies: the best customer experience is when problems are services are provided quickly and easily.

Conversational AI is the present of call qualification, and its near future too. In the next few years it is easy to predict that contact center will rely more and more on a mix of humans and bots – the bots dong the grunt work, the humans taking advantage of it to deliver better and better experiences to customers. Beyond that, who knows? Making predictions is hard, especially about the future (Neils Bohr, various attributions).

Other Articles

How PhoneMyBot adds value to your chatbot

How PhoneMyBot adds value to your chatbot

Using robots to streamline business processes is no longer science fiction. The field of Robotic Process Automation (RPA) is in full development and more business processes are handled by bots every day. The customer service flow is also participating in this trend,...

read more

Interact with us

Subscription

Receive our exclusive content:

My take on Omnichannel digital transformation

My take on Omnichannel digital transformation

My take on Omnichannel digital transformation

September 1, 2020

Every contact center offer is Omnichannel these days. Companies operating in the space of contact center software – like everyone else – follow trends, and having Omnichannel operation, the ability to save and retain context gathered on a channel to then use it the next time a customer starts an interaction, potentially on a different channel, was the big trend of the ‘10s.

The promise of Omnichannel is a lower customer effort. When I call a company, it’s because I have a question about a service or a product. Maybe I am angry because the service was bad, or I was overbilled. The first time I call, of course I expect to explain what the problem is. But if I get interrupted or the agent tells me to check back in a couple of days, I don’t want to have to repeat the whole performance a second time, even if I am using another channel (say: chatting on the website).

An Omnichannel contact center solves this problem by identifying the customer and attaching the context of the interaction to a record in a database. When an agent receives the interaction, ideally, she also receives the context and can see immediately who’s calling, what the issue is, and how far the resolution has progressed. This, irrespective of how the customer contacts the company: by phone, text message, email, social media, (any kind of) chat. It’s the Holy Grail!

Or at least, it should be. But in many cases, it’s not: while the contact center software has the capability for Omnichannel communication, implementing this on the field and especially in the company organization is a whole different story. And so, while 93% of companies agree that consumers expect companies to offer an uninterrupted experience when migrating between the different available channels, only 24% of companies worldwide would give themselves an excellent rating when it comes to allowing consumers to do so. But why is that?

Of course, there is always a delay between a feature being available in the market and widespread adoption. What Omnichannel is now was Multichannel in the ‘00s (the ability for the contact center to manage more than one channel). This is commonplace now, but it took 15 years for a Multichannel contact center to be a given.

New channels are popping up all the time. There is a plethora of messaging platform that appeared only in the past few years for instance. They support chat, voice, and video, but people use it mostly to chat and so these are new channels in the chat arena.

Social media channels for customer service – mostly Twitter and Facebook – have arrived last on the scene and only gained importance in the past few years. Adding them to contact center suites is easy, training the personnel to use them for customer service is harder. Sometimes, personnel using different channels belongs to different organizations: for instance, social media started up being managed mostly by Marketing in big corporations and not by Customer Service. This means a different software platform, different priorities, disconnected orgs. Integrating all this is a big project, so no wonder things are still far from ideal.

How can we make Omnichannel interactions easier to implement? One answer comes from AI. Conversational Virtual Agents offer customers a type of self-service that is pleasant, natural, and effective. Customers type, or speak, as if they were communicating with a person, with the Virtual Agent conducting a dialog in natural language. The channel served can be many: chat of course, but also voice in many flavors, even telephone calls. Social media conversations are also possible. The Virtual Agent can be Omnichannel by storing the context information of each interaction, and retrieving it when it identifies the customer again, on another channel. Conversational Virtual Agents act on text and so the speech is converted into text by specialized software. This allows to treat voice as a digital channel among many, both easing digital transformation activities and providing more homogeneous Omnichannel functions.

Putting one of these systems in front of the Contact Center greatly helps increase efficiency by solving the more straightforward interactions, and categorizing the more complex ones, that need a human touch, before they reach the human agents. This allows to route the interactions more efficiently to the right agent queue. Even more importantly, the Virtual Agent acts as a gateway that harmonizes the various channels and transfers the interactions not by channel, but by category or intent, irrespective from how they came in. So, the Customer Service organization finds it easier to “own” all the channels, since the Virtual Agent can forward the support interaction to the contact center, and other contacts, maybe more sales-oriented, to the appropriate organization in the company.

Not all Conversational AI platforms serve all the channels though: many are only text-based. While chat channels make up a good percentage of the interactions reaching contact centers, telephone calls are still important, accounting for about half of the total. So, an Omnichannel Virtual Agent true to its name should include the telephone channel. However, telephone access is still not common with Conversational Virtual Agents: there technical challenges, integration requirements, specialized expertise needs that keep many vendors from offering it.

Interactive Media has developed a true Omnichannel platform for the development, deployment, and operation of Conversational, telephone-enabled Virtual Agents. With several large customers and an ever-increasing installed base, we are in a perfect position to use our experience to facilitate your Omnichannel digital migration. We look forward to hearing about your challenges and discuss how we can help.

Other Articles

Other Articles

How PhoneMyBot adds value to your chatbot

How PhoneMyBot adds value to your chatbot

Using robots to streamline business processes is no longer science fiction. The field of Robotic Process Automation (RPA) is in full development and more business processes are handled by bots every day. The customer service flow is also participating in this trend,...

read more

Interact with us

Subscription

Receive our exclusive content: