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The history of call qualification – a perspective

The history of call qualification – a perspective

The history of call qualification – a perspective

Written by Interactive Media

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.

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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).

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My take on Omnichannel digital transformation

My take on Omnichannel digital transformation

My take on Omnichannel digital transformation

Written by Interactive Media

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.

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Better customer experience in Telecom – an effective solution

Better customer experience in Telecom – an effective solution

Better customer experience in Telecom – an effective solution

Written by Interactive Media

August 10, 2020

In recent years, the value of customer experience for businesses has gained substantial attention. The concern with user satisfaction, which is crucial for high performance companies, is giving renewed impetus to the search for better tools for telephone operators and the telecommunications sector in general. The business practices in this industry are complex and require highly integrated tools.

For this, the new technologies to incorporate into the service routines must be flexible and efficient, making a measurable impact in the customer relationships.

In this post, we want to highlight the importance of a great customer experience in the telecommunications industry, and how AI (artificial intelligence) used end-to-end, can greatly increase the user satisfaction.

Finally, we introduce Interactive Media. With more than ten years of experience in conversational virtual agents and artificial intelligence, the company’s solutions are at the forefront of the new wave of offerings to optimize processes and enhance the customer experience.

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The importance of customer experience in Telecommunications

Telecom companies, and especially mobile carriers, are completely dependent on their relationship with customers. Competition is intense and regulations make it easy to switch from one carrier to another. Since most carriers are equivalent for their device offering and network coverage, growing the business comes down to price, and customer experience.

Pricing is an internal strategic matter, but for customer experience, it needs to be agile, effective and, whenever possible, delightful, to keep the existing customers and attract new ones.

Customer experience means every (and any) contact between the company and the user, regardless of the channel. To compete effectively in this area, building customer loyalty, it is important to invest in strategies that personalize messages, streamline processes, and build an experience that will surprise and delight users.

Unfortunately, the telecom sector has a long history of poor performance in managing complaints. Precisely for this reason, carriers need to meet the growing consumers demand for better service and adopt robust and updated tools.

We at Interactive Media have seen this first-hand, due to our long experience with fixed and mobile carriers. For example Davide Arici, pre-sales manager, notes that “technology in itself is not enough: you need to have the support of vendors experienced not only in technology, but also in how to apply it intelligently to remodel the service processes“.

With an experienced partner that shares the common goal of a better customer service process, telecommunications companies can use disruptive technologies – always leveraging in full the supplier’s know-how – to launch a continuous improvement process in the short, medium and long term.

The power of artificial intelligence in customer experience

Artificial Intelligence is one of the most important corporate bets today. Companies in all sectors are investing in AI, often in a haphazard and unfocused way – “see what sticks and go with it” seems to be the attitude. In the telecommunications sector, this premise is confirmed: for Arici, “the visible implementation of AI becomes almost a market necessity, since, in the eyes of the public, it is a standard segment”.

In fact, users are now quite familiar with the convenience provided by artificial intelligence. In smartphones, for example, AI is directly or indirectly involved in a large part of everyday activities, from vocal commands to online shopping recommendations to navigation through traffic.

In telecommunications companies, one of the main areas where AI can make a difference is in customer service. Simplified and lean interactions, without wasting time, is what makes the consumer experience positive and Conversational AI is key to provide it.

“From this perspective, artificial intelligence enables fast and pleasant service based on features such as an open dialog for self-service, approaching human conversation“, points out the Arici. This way, it is possible to interpret the customer’s request and address it quickly in an automated way, without requiring the branching of static menus.

The key is simplification. The services offered by virtual agents powered by artificial intelligence need to be formulated and adapted on an individual scale, meeting the demands of each type of operation. Interactive Media, which has focused on customer service technological evolution for more than twenty years, has the necessary expertise to support companies in strategic choices – including the application of AI.

In addition to engineering, the deployment of conversational AI is like a recipe: the final system mixes diverse and complementary ingredients, technological, linguistic and psychological. “When it comes to customer service, the focus is on cutting the domain over the application’s target audience, shaping the dialogue to make it efficient in a specific relationship ecosystem”, emphasizes the pre-sales manager at Interactive Media.

So, the added value of the company that provides the artificial intelligence devices is not only in the robustness of the technology, but also in the ability to understand the operational details, reviewing the service flow and customizing the model according to the usage environment. To guarantee the effectiveness of the solution and the quality of the results obtained throughout the process – during and after the deployment of virtual agents in the telecommunications environment -, make sure you know the products and services of potential partners, and choose wisely what to deploy.

The Interactive Media solution for Telecom

Interactive Media’s mission is to develop, deploy and improve conversational virtual customer service agents, boosting the customer experience and, consequently, the overall results of its customers.

In the telecommunications sector, Interactive Media’s technology has a sizable installed base. “We developed a Conversational AI project for a huge mobile carrier. They have now 180 virtual agents, that perform multiple tasks typical of a telecom call center, such as: register users, gather their personal data (account numbers, date of birth, addresses, etc.); block a SIM card from a phone that has been stolen; enable or disable additional services; schedule installment payments and changes of how the invoice is received.”, says Arici. “This saves users time, since they don’t need to wait in a queue, and our customer substantial amount of money.”

By automating simple tasks, deploying virtual agents to perform them, it is possible to optimize resources and standardize the service flow, ensuring a more uniform experience for the customer. “In this way, 85% of the calls are executed automatically”, points out Arici.

Interactive Media’s tools are flexible and modular, facilitating integration with third parties – such as data networks, RDBMS, telephone centre and provisioning systems, avoiding additional investments. This way, managers gain autonomy to incorporate and adapt the technology according to the availability of mechanisms and resources, getting the most out of the disruptive power of artificial intelligence in customer experience.

The message, therefore, is clear: the solution for telecom operators must be flexible without losing in efficiency. “Interactive Media strives to be at the forefront of technology, while backing up our technical expertise with a strong organizational experience.“, concludes Davide Arici.

If you want to learn more about what’s possible with conversational AI in customer service, contact us and find out how we can help you enhance your customers’ experience and lower operational costs.

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Everything You Always Wanted to Know About Voicebots* (*But Were Afraid to Ask)

Everything You Always Wanted to Know About Voicebots* (*But Were Afraid to Ask)

Everything You Always Wanted to Know About Voicebots* (*But Were Afraid to Ask)

Written by Interactive Media

August 6, 2020

Voice is undoubtedly the most used communication channel – among people, but not only. Voice is increasingly being used to interact with machines. There is a body of research indicating that a majority of people uses voice to search for information on their smartphone. In the area of Customer Care, interacting with bots using spoken natural language is the most striking new development of the past few years. The systems that make it possible are called Voicebots.

Voicebots are a modern and highly effective addition to the customer experience function in companies. Not only Voicebots make the customer experience better on first contact, they also help human agents in their job, by relieving them of the most repetitive and boring tasks and allowing them to serve customers more creatively and engagingly.

In this article we will explain the main concepts around Voicebots. First, we will talk about technical matters: how voicebots work. Then, we will go into the advantages of this type of solution. Our goal is to demonstrate how voicebots can play the role of key elements to optimize Customer Care.

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Voicebots in customer service

Voicebots are conversational AI applications, that conduct a voice dialog with humans. The application we describe in this article is to automate customer service – using their natural language capability to substitute the old IVR systems and saving customers from having to press keys to generate tones and slowly reach the desired service (if they are lucky).

With older IVR systems, still quite common today, users waste substantial time listening to menus and waiting for the option that seems the best fit for their need. Unfortunately, besides customer frustration, this originates many errors that causes calls to be routed to the wrong queue. The best outcome in this case is that the agent taking the call will transfer it to the right department, but often the call simply does not complete, and the user must call again – maybe a different number.

A well-designed Voicebot is instead an excellent tool to solve the problem of understanding the users’ intents. “Voicebots are a fusion of several technologies, some very new and other more traditional, like AI, computational linguistics on the one hand, and old-fashioned Information & Communication Technology on the other.” says Roberto Valente, Interactive Media’s CEO.

Users can interact with Voicebots in a natural way, answering open questions like “What is the reason for your call” Not necessarily the Voicebot will understand what the user wants immediately to the point that the service can be provided, but in this case it can ask disambiguation questions that restrict the field of possibilities, to make sure the intent is understood correctly: for example “would you like to fly in the morning or the afternoon?” It all comes down to the Voicebot design, and with 10 years of experience and many successful deployments, Interactive Media guarantees excellent customer experience results and a high percentage of interactions handled by Voicebots.

How Voicebots work

Voicebots are extraordinarily complex software applications. They must be able to listen, understand, talk, solve problems, look for information within the company’s knowledge base. They must do this with a high degree of security and for many users concurrently – hundreds, or like in some of the services deployed by Interactive Media, thousands.

One of the most important of the technologies involved is the Speech-to-text engine. Its function is to transcribe the voice from the user into the corresponding text. According to Mr. Valente, for better performance the Speech-to-text engine should be primed with information regarding the spoken language to be expected in the specific application domain. This could be for example financial services, or air travel, or telephony services provided by a mobile carrier. Each sector has its own specific set of terms that appear more frequently than in normal speech. There is then specific customer information that is very hard to understand, like names, alphanumeric codes (license plates for instance), addresses. In this case the system cannot use the context to narrow down the number of terms to recognize. As an example, if the conversation is about animals (for instance, at a veterinary clinic), the system may initially understand a word as “vow” but it can quickly correct it to “cow” – a far more likely interpretation. But for surnames, that are all unique, no such correction is possible.

The semantic engine is another fundamental technology for Voicebots. It is not enough to isolate words; the system must also understand their meaning – this is where the semantic engine comes in. As an example, “a ticket” could be many things, but a traffic ticket is different from a customer service ticket or a concert ticket. The role of the semantic engine is to distinguish these different tickets, and other more complex constructs.

Mr. Valente also highlights how important it is for Voicebots to be able to integrate with the telephone networks, and the numerous Contact Center software suites. This is an aspect that is often underestimated while implementing a Voicebot project but is often essential.

In addition to the ASR engine, the semantic engine and the telephony and Contact Center integration platform, there are other important parts to a Voicebot environment, such as a graphical environment for designing and managing the application flow, the management of alerts, reporting and service provisioning. All this is needed for a reasonable ease of implementation and operation of the Voicebot application.

Voicebots advantages

A properly implemented Voicebot offers many different advantages. It is clearly easier and faster to interact with a system using your voice than typing. A fast typist can enter up to 45 words a minute, but a normal person says at least 110 words during the same time. This speaks in favor of voice-based engagements with Customer Service, while maintaining the digital channels advantages as the speech is converted into text which is easy to manage and analyze.

Voicebots represent a technological quantum leap for initial engagement with customers. Gone is the need to listen to IVR menus and send tones. With open questions and the use of natural language, the customer experience becomes much better, while the time it takes to qualify the intent of the call is dramatically reduced.

Another advantage is the better use of human resources within the company. Agents are freed from the most repetitive and frustrating parts of their job – which are mostly simple tasks that Voicebots can accomplish very well – and can be reallocated at least in part to more productive and strategic activities. There is less turnover among the agents, who find their job more rewarding, and data entry errors, rather common with humans, are greatly reduced.

In summary, Voicebots:
• provide a better customer experience compared with the current IVRs
• reduce the cost of customer service, since human agents are expensive especially when they perform routine tasks
• provide a standard service, with always the same answers to the same questions
• continuously improve, with feedback coming from report analysis driving cycles of tuning

Mr. Valente adds: “companies that employ only human agents have obvious problems rightsizing their workforce for the number of contacts they receive, that changes by day and hour. Especially in times of uncertainty and during emergency, there can be enormous peaks. For instance now with the COVID epidemics, there are services that are completely swamped, like government organizations in charge of providing subsidies.”

“Organizations that operate Voicebots can instead scale the service up and down quickly, with no wait time for customers and with much simple service management.”

If you have reached this point, it is likely that you have some interest in investigating deploying a Voicebot in your organization. Interactive Media has more than 10 years of experience in Voicebots, we would love to talk to you.

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Giving chatbots the gift of voice

Giving chatbots the gift of voice

Giving chatbots the gift of voice

Written by Interactive Media

July 14, 2020

A battle of the bots

Chatbots are everywhere. According to Gartner, at the moment of writing between 1500 and 2000 companies worldwide have in the past couple of years developed a chatbot platform that they offer their customers as the base for applications. Of course, not all of them are good and the one-shot question-answer bots abound. But many are able to sustain a real dialog and use a well-designed knowledge base and semantic / learning infrastructure based on AI to really recognize and understand what people type, keeping the context, and following up with more questions if the initial meaning is unclear.

But even these “good chatbots” are mostly text-based. While chat usually refers to text (embedded in a website, over a dedicated chat platform like Facebook Messenger or WhatsApp or even via text messages), it’s important to recognize that voice — and in particular voice over the telephone network — is still a big part of how customers interact with businesses.

Voice-enabled bots are still the exception and not the rule. But the time is fast approaching when omni-bots (which can manage equally well voice and text conversations) are the ones that will emerge victorious from this “battle of the bots”. This in turn will be a factor in deciding the winners in the inevitable shake-out that the conversational interactions industry will experience in the next couple of years.

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Why voice?

People like to text and type short messages from their devices. It is a very convenient way to communicate on most occasions, but as a habit it’s fairly new, sparked by the availability of devices that let people text and type to communicate. If we focus on customer service, until 10 years ago it was only over voice. There many more channels on which to contact companies now, but telephone calls are still the most common way to do that, and certainly the most satisfying.

After all, if you get upset about a service or a product, it’s difficult to yell while typing: you could use ALL CAPS but, somehow, it’s not the same. Putting jokes aside, voice is what people use when they need to have real-time feedback, and voice enables people to convey information much faster than chatting: if you type fast and well you can put in 40 words per minute. But an average talker will speak 150 words in the same time (even excluding from the stats the end of pharmaceutical commercials). Finally, when all else fails people pick up the phone and call, so one could say that while voice calls may be going down as a percentage of the total interactions, their importance is actually going up.

Also, there are occasions when it’s OK to talk, but not to type: don’t text and drive! Although there are also occasions when texting is the only way to communicate, like when you are at a rock concert…

So, voice has a big role, and especially voice over the telephone network: dialing 1–800-SUPPORT is still the easiest way to get you there. Adding voice support to bots is consequently a great way to expand the reach of conversational technology in the customer service domain to the 50% or so of communications that are currently out of reach.

The challenges of voice

For bots, voice is harder that text. While voice can be transcribed into text rather easily by an ASR (automatic speech recognition) and the transcription can be fed to the bot’s AI, this is still an additional step that needs to be integrated into the system. There are also several TTS (text-to-speech) services that can be used to convert the bot’s answers back to voice — still another step.

What’s more, the knowledge base and AI training for text and voice is not completely overlapping: we say things and use turn of phrases while speaking that we wouldn’t use while typing; on the other hand, the ASR will not make typographical mistakes that are common in chat and must be accounted for by chatbot engines. But these are issues that can be overcome with better AI training — we at Interactive Media know this since we support both voice and chat in our conversational Virtual Agents.

More challenging, the system needs to be very responsive for voice: while no-one would object to a 10-seconds pause between typing a message and receiving a response, try that with voice! And so, the integration needs to be architecturally sound and fast. And not all ASR systems are created equal: while recognition performance of the latest ASRs is uniformly quite good, some systems have an advantage for specific tasks: for instance, Google Speech APIs excel in recognizing addresses due to their integration with Google Maps. It makes sense to use different ASR vendors for different parts of an application.

And then, there is the telephone network to deal with. There are certainly RESTful APIs that are easily integrated into a conversational system, but at volume they can be expensive. Also, usually the companies deploying the bot already have their own telephony infrastructure, and it doesn’t make sense to overhaul it for the use of the bot. Be it implemented through a local switch (PBX) or a SIP trunk from a carrier, telephony is more challenging to integrate with than a purely HTTP based interface.

Finally, if the interaction does not complete within the self-service conversational domain it will need to be forwarded to a human agent. This implies not only forwarding the call to a Contact Center suite (usually over SIP), but also passing over the context gathered so far, and for this an integration with the CTI interface of the Contact Center is needed.

So, there are several factors that contribute in making voice and telephony for bots a complex proposition.

An offer to help

Interactive Media knows a lot about voice and integration with other voice platforms. We started with voice applications, telephony and customer experience in 1996, and so we have both a long experience in what it takes to integrate successfully with the telephone network, and a super-solid platform that has evolved to incorporate the latest architectures and protocols into a proven foundation for all voice communication.

We also have a platform for conversational application with several sizable deployments, both for voice and chat. This has helped us understand the most impactful features of the telephony platform and optimize them as they relate to bots.

So the idea is simple: Interactive Media is on a mission to help chatbots add voice to their repertoire. This starts with telephony integration, of course, but continues with speech transcription and generation, and integration with Contact Center platforms — we integrate natively with several of the most common ones. Our software is already in the cloud, and you can try it at Phone my Bot.

We are looking forward to giving all deserving chatbots the gift of voice.

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