Year: 2021

Future of AI Voice Assistants — BotPenguin

The constant technological advancement transformed the way people perceive voice assistants in their day to day lives. When voice assistants began to appear with the introduction of Siri, no one could have predicted that we can even communicate with voice inputs without even typing out. Also, it has been amongst the new technologies used in chatbot platforms, enhancing user experience. Now nearly after years, it’s estimated that every one in 6 Americans prefer using a bot or smart speaker (Google Home, Siri, and Amazon echo). Even, e-marketer report suggests that nearly 100 million users will be using voice bots.

Indeed, AI voice assistants will soar means, the tools and technologies behind these devices like AI (artificial intelligence) are shaping the industries and making them more technologically friendly. These are the parts of the next generation tool kit to spark growth in retail, healthcare, etc. And with the entrance of brands such as Amazon, Google is helping people make it a part of their day-to-day life and leverage it more precisely.

It quite obvious and seen voice bots are getting better at an exponential rate and racing the ways of communication among people and brands. Thus, people are having a significant question that what caused this paradigm shift towards voice ai. So let’s find out fast! But before moving forward, let’s discuss some basics!

“Voice bots or assistants are software or computer-based program powered by AI (artificial intelligence) that allow the user to navigate an interactive voice response system (IVR) and helps in giving input without typing. It mainly uses natural language processing (NLP). — to go deeper, know What are voice bots? Difference between chatbots and voice bots.

These voice assistants also make it possible for prospects to accomplish two things at once- instant responses, seamless browsing without even giving much effort to it, and all happens by just the voice! Even there are many benefits it offers.

Trending Bot Articles:

1. Case Study: Building Appointment Booking Chatbot

2. IBM Watson Assistant provides better intent classification than other commercial products according to published study

3. Testing Conversational AI

4. How intelligent and automated conversational systems are driving B2C revenue and growth.

What is causing the shift Towards Voice Assistants?

According to us, the major driver of the change transformation towards voice assistants is the changing user demands and how people are keen to learn better ways of communication with the changing time. Mostly, it is seen majorly because of a higher level of awareness among millennial customers. Having these tools is a must in this ever-evolving world where speed, efficacy, and comfort are major needs of the people.

AI in our lives is also fueling the drive of voice ai and encouraging people to use voice bot applications. With the innovation of products such as conversational UI, smart speakers, thermostats, and other appliances, they let people have comfort and easy execution of the tasks and raise the utility. Whether you need to browse something or book a cab, call your friend, and so on, all can be done via voice assistants. Even numerous industry experts predicted that nearly every application would deploy voice ai in the coming years.
And with this, this technology is seen everywhere so that it will take us in the coming future is no surprise.

So, now let’s give a high-level overview of voice assistants’ potential and how it is raising unstoppably.

Key Statistics of Voice Bots

We can plot an outline of the future of voice assistants by looking at these facts and figures. A recent report from PWC suggest s that ai voice assistants have been used in a multitude of ways during the past decade, and they will continue to support us even later too. Here are some of the figures for you all:

1. Around 90% of people identified voice bot as useful.
2. And, 72% had used ai voice assistants.
3. Around 27% of people faced issues while giving commands.
4. It has been seen, 20% of issue commands for the vehicle navigation process.

Hence, these depict how it is growing for the better and making businesses more automated, and serving customers with more comfort. Let’s move forward with greater predictions and possibilities about voice ai.

Voice bots Offer Streamlined Conversations.

Talking about voice assistants, Google and Amazon recently announced no use in repeatedly saying “wake” words. Earlier, both assistants were initiated with the word “wake” to start with the new conversation. For instance, if you want to know nearby restaurants, you have to say Alexa before requesting any information. And then, Alexa will respond to your query and offer solutions via voice.
Customers use voice bots in specific sorts of queries. It also helps in deciphering these contextual factors making a conversation more effective and convenient. Thus, the way it is supporting human life will become one of the must-haves shortly.

Is It Highly Compatible and Has Greater Integration Scope?

I will say voice assistants are highly compatible and can be integrated into multiple platforms. Even Amazon has been ahead of the game and launched high-end products such as speakers. It has already integrated a vast array of products, including Samsung’s Family Hub refrigerators. And with this, Google also caught up! The idea behind this is to give custom experiences to everyone via specific functions integrated with the assistants.
We will surely see a greater interest in developing voice-enabled devices in the coming years, and adoption rates will increase.

Will Voice Assistants change Browsing Behavior?

Voice technology is one of the hottest topics ever; in every debate, it is being taken out! The major challenge is visibility, as people can’t or see due to not having a visual interface. Users can only get the service if they are connected to Google Home or Alexa application. Thus, search behaviors will undoubtedly change and become relatively fast and swift, as by giving simple voice commands, you can get anything you are looking for. Some reports say voice-based ad revenue could reach $19 billion by 2022, all thanks to the vast part of voice search apps on mobile devices and speakers. This will donate a larger part to the overall growth too.

They are up with Voice Push Notifications.

We already discussed several times chatbots use user-centric push notifications to keep customers updated about the needed information. Similarly, voice assistants use the same as a re-engaging approach with your app or websites. This helps users get timely information or updates regarding the task they are doing. Also, voice presents a unique way of distributing push notifications. It leads to better engagement, retention and reminds users of the app information or upcoming events. Now that we have both Google assistants and Alexa allows the user to enable voice notifications at their fingertips; they can hear them rather than reading them. With this, the future of voice bots extremely brighter.

Conclusion

With the constant advancements in several fields are supporting voice bots and chatbots have become more sophisticated by everyday use. It has now established itself as the ultimate comfort exercise, and even several platforms like BotPenguin also making it sure.

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Future of AI Voice Assistants — BotPenguin was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

Customer service is the most critical factor determining whether a business will grow or suffer from customer apathy. Excellent customer service as a strategy can bring an immense competitive advantage. Keeping customers happy is a challenging endeavor, given the continually changing business environment and customer expectations. The first point of customer contact plays a critical role in customer experience. An Interactive Voice Response (IVR) system often serves as this first point of contact. Given the crucial role that IVR plays in the contact center, it is essential for businesses to be aware of IVR trends for 2021 and beyond, in order to get their customer experience strategy for the near-future right.

Current IVR Challenges

According to , IVR was responsible for over 50% of consumers not completing their business transactions. According to Forrester, about 79% of customers would rather self-serve than use human-assisted support channels. These trends have forced many to wonder if IVR is relevant any more. However, voice is a preferred channel for the younger generation today, as evident from voice assistants’ adoption and popularity. There might also be times when customers prefer voice channels over other text-based channels depending upon the situation. And hence, will remain an integral part of businesses’ customer experience strategies if it can reinvent itself.

There are four primary issues with the current implementation of IVR.

1. Traditional IVR takes a one-size-fits-all approach, without any regard for customer emergencies and the impact of delayed services. There was no way to fast-track more urgent queries. Such inability hurts customer satisfaction. At the same time, agents spent their time on non-critical or time-sensitive issues, thus negatively impacting the internal efficiencies.
2. If there are spikes in the incoming call traffic, it becomes challenging to serve all the customers. Teams either quickly need to increase the number of agents or risk not catering to all the customers.
3. They employ a confusing and lengthy process before a customer can obtain meaningful answers and resolutions to their queries and issues. It forced the customer to select many options and wait for an agent to be available for even simple questions. If the agents are busy handling other customers, it increases the wait time, and this issue is a significant cause of dissatisfaction with IVR.
4. IVR systems had poor integration with other channels of customer interactions. Customers perceive a business as one integrated entity; hence, isolated, disjointed channels provide a sub-par experience. Even with IVR itself, often, the customer had to shift from one agent to another and repeatedly explain the issues.

Learn more: IVR Deflection vs Conversational IVR: How to Improve Customer Satisfaction

Trending Bot Articles:

1. Case Study: Building Appointment Booking Chatbot

2. IBM Watson Assistant provides better intent classification than other commercial products according to published study

3. Testing Conversational AI

4. How intelligent and automated conversational systems are driving B2C revenue and growth.

What Do Customers Want?

What businesses need to keep in mind is that the IVR doesn’t work in isolation. Companies must consider IVR implementation and the overall customer satisfaction strategy together, rather than as independent tools. From that perspective, it is critical to understand what customers want and determine how you can use IVR to fulfill those wants.

Omnichannel Experience

A HubSpot study revealed that 62% of customers want to communicate with companies via email for customer service. 48% want to use the phone, 42% live chat, and 36% “Contact Us” forms.” There is a significant overlap between the numbers. Overall, 89% of customers expect an omnichannel experience.

Consistent Experience Across Channels

Omnichannel experience has different connotations than multichannel experience. A multichannel IVR implementation is disjointed, so it doesn’t maintain the customer experience’s uniformity and consistency. In the absence of such consistent experience, you risk losing 73% of your customers.

That is why well-designed omnichannel IVR implementations have the potential to be consistent across all channels. The consistency means a seamless transfer of information between channels while maintaining the continuity of conversations. If customers switched to text messaging from a voice call, they shouldn’t need to explain themselves or share the same information they already shared on the call.

Immediate Response

The HubSpot study also revealed other interesting statistics. 90% of customers wanted an immediate response to their calls and queries. Such urgency is because customers only call the support center when they cannot solve their issues using self-service options.

The IVR trends for 2021 reflect these four primary customer needs and that the technology and businesses are responding to the drawbacks and challenges consciously.

Here’s an expert guide on how businesses can leverage Conversational AI for IVR deflection and why it is needed

IVR Is Undergoing A Transformation

The emergence of Artificial Intelligence (AI) and Machine Learning (ML) has brought a renaissance for . Instead of going away, it is transforming with these emerging technologies to provide an even better customer service experience by removing traditional IVR shortcomings. The data availability and technological advances allow the IVR to be meaningful again for the companies while reducing the risk of customer dissatisfaction.

The three dimensions of customer needs and the inevitable adoption of AI and ML capabilities are primary drivers of how IVR and customer experience technologies will evolve in 2021 and beyond.

#1: Rise of Conversational IVR

There are slim chances that you are not aware of what Siri or Alexa is. There is an estimation that before 2020 ends, there would be 4.2 billion digital voice assistants globally, and by 2024, the number would be 8.4 billion , more than the world’s population. Thanks to the advances in Natural Language Understanding (NLU) and conversational Artificial Intelligence (AI), voice is becoming the favored mode of interaction across all spheres. Conversational IVR follows this trend as it is becoming the preferred first point of contact for customers.

Conversational IVR removes one of the biggest customer grievances. While they still may be talking to a machine, it is a much more humanized form than the DTMF (Dual Tone Multi-Frequency) technology’s robotic voice asking them to choose numbers mechanically. Instead, conversational IVR understands what they are saying and responds with relevant information without the customer having to solve a puzzle.

#2: Predicting Caller Intent Is The Foundation

One reason for long wait times with IVR was to capture every possible piece of information about the customer. Organizations wanted to capture this information to know about the customer and why the customer was calling. However, such attempts often ended up with the customers having to choose many options when prompted. It increased the wait time and customer frustration.

Instead, the systems are now trying to predict the reasons behind the customer call. Sometimes, it is easy to find such intent. For example, there is a canceled flight, and one of the customers who were to travel in that flight calls up the airline’s IVR. Chances are they are trying to find alternate flights to book. Factoring this knowledge in how the IVR responds to the customer can make the conversations more effective and efficient.

Predicting the intent is much more convenient with conversational IVR . The NLP algorithms at the backend can process the query, in addition to the underlying trained data. It can then respond appropriately.

As conversational IVR continues to collect more data, ML algorithms become more accurate with their predictions.

#3: Breaking Down The Constraints With Omni-Channel Communication

It was 2014 when Apple announced the “Handoff” feature during WWDC. The handoff allows you to continue work seamlessly between your Macs, iPhones, and iPads in continuation. IVR is catching up to similar capabilities to provide friction-less communication across devices, channels, geography, and time. It is also adjusting itself to changing communication preferences as generations change. As day-to-day communication moves from phone calls to text to voice, the IVR follows the trend.

Both conversational interfaces and predictive intent help with omnichannel communication. While the conversational interface may be the initial touchpoint, it can identify the customer’s needs and preferences and suggest moving the interactions to another appropriate channel.

#4: Rise Of Visual IVR & Self-service Capabilities

Smartphones have ensured that no matter where we are, we have various capabilities at our fingertips. New age IVR is utilizing these capabilities to stretch the boundaries of customer service. A customer calls up to understand detailed options of an insurance policy, and the options change based on customer preferences. Instead of explaining choices and asking for preferences over a phone call, the contact center can simultaneously provide those options on the customer’s smartphone. A customer can select from those options. Such interactive implementation is a basic example of visual IVR, but the possibilities are endless.

The web already has such self-service capabilities. By combining speech and on-screen interactions, Visual IVR simplifies the navigation experience and expands the possibilities of IVR-based self-service activities. By combining channels, Visual IVR provides much greater engagement and ease of operations. The increased convenience and engagement drive up customer satisfaction.

These capabilities also enhance personalization that again drives satisfaction. The IVR system can present relevant options based on geography, language, previous interactions, and many other details to reduce the customers’ cognitive load.

Check out our latest e-book: Conversational AI: Redefining Contact Center Automation With AI .

#5: Analytics

The underlying ML and AI support for IVR systems is helping companies not only generate better analytical insights but it is also allowing them to convert those insights into action. 2021 and onward, we will see more integrated data across channels, and even better insights, including predictive analysis, will drive the consumer experience (CX). With omnichannel IVR, it is possible to aggregate the data into a single source of truth. Such aggregation will help companies build strategic CX improvement initiatives instead of ad-hoc solutions and take objective decisions.

There are many ways analytics will help companies create efficiencies in their processes. From reducing the Average Call Handling Time (ACHT) to reducing the call volume, analytics can help companies develop practical strategies that improve the customer experience while reducing the cost and time of serving them.

#6: Optimization Based on Customer Journey

One of the issues with how businesses utilize IVR is that it treats every customer and every situation with the same approach. Some cases demand faster response than others, and some business processes are inherently more complex than others. The customer experience strategy must take into account the scope of optimization for such operations.

One way to do it is to imagine the customer journey for critical scenarios and optimize those response strategies. For example, if a customer calls for an issue that involves the breakdown of equipment or some such pressing problems, it wouldn’t make sense for the IVR to send them to other channels to find solutions. The best option would be to connect them to a human agent. The agent can then divert the customer to other channels if appropriate.

However, to do that, you need to understand both the company as well as the customer. The journey should also be flexible so that the IVR system can determine those variables dynamically, and the journey map can change optimally. While the journey maps must have predefined handover points between the digital tools and humans, flexibility to alter them for unique circumstances optimizes the experience.

#7: Personalization Is The Pinnacle of Customer Experience

While we have made immense progress in breaking down the geographical barriers for doing business and bringing innovative solutions to solve pressing problems, companies still strive for customer loyalty. With many product options available, there are few barriers for customers to switch from one brand to another. In the old days, business people and shopkeepers had a direct connection to the customer. This connection was the biggest driver of customer loyalty.

Personalization offers businesses a chance to create a deep connection with customers. It humanizes digital channels. And that’s why it is one of the most critical factors of a successful digital transformation for businesses.

IVR technology is also adopting personalization. All the trends contribute to enabling businesses to offer a personalized CX to their customers. As the underlying ML and AI algorithms become more accurate with the continuous influx of data, IVRs will have more opportunities to offer personalized experiences. These experiences will drive up customer satisfaction and will reduce customer acquisition costs (CAC).

IVR is one of the most critical touch points between your business and customers. While there was a decline in IVR’s overall effectiveness in the last few years, the emergence of new technologies has started transforming how IVRs are implemented and used. As these new technologies mature, they will open more avenues for companies to make their customers’ lives easier, benefiting from improved customer satisfaction and business growth in return. Companies need to look at the integrated picture where IVR is part of the entire technology stack and utilize them to serve customer expectations and needs.

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7 Remarkable IVR Trends For the Year 2021 And Beyond was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

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“Be careful with your money!”, my mother used to yell at me with a lovely tone, when I ran out of money before my next allowance. “Do you even know on what you have spent it? You should really keep track of your spending!”

And it is a wise piece of advice, right? I bet a good majority of us, responsible millennials attempting to do some proper adulting, sincerely try to do so. Yet there are only a handful of activities that I consider more tedious than writing down every expense I make. I mean it. I don’t think anyone reading this will happily turn down a couple of hours of Netflix to do some exciting accounting instead.

The good news is, my virtual pals, that we live in a world where technology offers the widest variety of possibilities! From filters that transform your face into a cute puppy, to the chance to program your very own minions and make your life easier. Your very own bot fleet! What if you could send a two word message to your digital servant and they would write it down in that dreadful spreadsheet for you?

With this in mind, I programmed a Telegram bot that takes care of this unpleasant but necessary activity for me, and it was far simpler than I had thought. You only need some basic understanding of Python to get your own bot running and accounting. Let me show you how easy it is!

Building your Bookkeeping Bot, step by step

Step 0: Create your Google sheet

I will be using Google Drive to store the spreadsheet. I chose to do that because it allows me to access it from anywhere if I need to. It also keeps your data safe and you do not have to worry about having local files. Therefore, you will need a Google account. If you don’t have that already, you will have to create one.

Step 1: Set up Google API access

In order to connect the Python script to your Google account, you will need to enable the Google Drive/Sheets API. This video in YouTube from Tech With Tim explains the process perfectly, which in summary is:

1. Create a spreadsheet and fill in some cells, we will use that for testing. Give it a proper name.
2. Go to Google Cloud Console and create a new project.
3. Enable Google Drive API, setting web server access, to read application data, with Project>Editor role. Make sure to download your credentials in JSON format and store it in your project folder (keep it safe!).
4. Enable Google Sheets API.

Step 2: Install libraries and test Google sheet access

Now, to make sure the script and your sheet are playing nice, we can do some testing in Python. The first thing you will need to do is install some libraries to interact with you freshly created spreadsheet:

pip install gspread
pip install gspread-dataframe
pip install oauth2client

Now you can already try things like downloading data from your sheet, edit the data, and upload again to update the sheet:

Now you want to put some data in your sheet to test it out:

And then go to your creds.json file, and look for the “client_email”. That is your assigned address in Google Drive API. Share the sheet you created with that email:

Now, you can initialize your client in Python and connect to the sheet:

We are getting the data into a dataframe, since this will help later when we start manipulating rows. The dataframe will look like this:

            Date              Type    Description    Price
0    30/Aug/2020              Food        Takeout     11.0
1    31/Aug/2020    Transportation       Gasoline     42.1
2     1/Sep/2020              Food      Groceries     56.5
3     2/Sep/2020              Food         Burger     13.0
4     3/Sep/2020           Clothes        T Shirt     19.5
5            NaN               NaN            NaN      NaN
6            NaN               NaN            NaN      NaN
7            NaN               NaN            NaN      NaN
8            NaN               NaN            NaN      NaN
..           ...               ...            ...      ...

Now all these columns get imported as strings (dtype: object), so let’s give them the right format:

At this point you can get summaries for your data however you like. I am not going to get into that here, but just to give an example, you could aggregate using pivots and produce things like this:

Type        Clothes     Food     Transportation
Date                                  
2020-08         NaN     11.0               42.1
2020-09        19.5     69.5                NaN

Trending Bot Articles:

1. Case Study: Building Appointment Booking Chatbot

2. IBM Watson Assistant provides better intent classification than other commercial products according to published study

3. Testing Conversational AI

4. How intelligent and automated conversational systems are driving B2C revenue and growth.

Step 3: Create a Telegram Bot

Now it’s time to create your Telegram bot, and a channel where you will send your expenses. To create a bot, you will need to write to Telegram’s BotFather, send the command /start, and follow the instructions to create your bot. You will receive a TOKEN, save it securely!

After creating it, send the command /setprivacy, choose your new bot, and then Disable. This allows your bot to read all messages coming to the channel, instead of just the ones beginning with a “/” (called “commands”).

Now create a Telegram channel, and add your bot’s username.

Step 4: Write your script

We can start now to write the python script that will handle all our expenses. You can begin with the following steps:

• Import all the libraries you will be needing
• Define variables
• Open a connection with your expenses sheet
• Get the data into a formatted dataframe

Next to the functions. We want a simple workflow:

1. We input an expense description and its price, separated with a comma.
2. The bot asks what type does the expense belong to, offering a predefined set of possible types as buttons.
3. We select the type by pressing the button, and the bot saves the expense as a new row in the sheet.

For this we will create 2 methods, one that handles incoming messages and offers “types” of expense to choose from (“input_expense”), and the other that saves the expense in the sheet once we push a button (“callback_query_handler”, you must respect this name):

Finally, create the bot object, add handlers, and start polling:

Step 5: Test your Bot!

By now you should be able to send expenses to the channel (remember to send it in the form: description, price), and the bot will save your expenses in the sheet:

Conclusion

As you can see, getting your own app to handle daily expenses using Telegram and Google Sheets is really easy.

But this is just the beginning. You can use this as a starting point and take your expense tracking to a whole new level! For example, you could add commands to get monthly spending reports per spending type, or to search for expenses by text… You are only limited by your imagination here!

Now, we can both finally tell our parents that we learned how to be careful with our money!

Don’t forget to give us your 👏 !

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Your own Bookkeeping Telegram Bot with Python was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

The customer satisfaction (CSAT) score of the Chatbot is beneficial in this digitalized age where you want to increase sales, reduce handling time and enhance the customer experience.

The very first step of any problem solving is to understand the probable pain areas of the customer.

Choose your method to analyze the situation

A. Root Cause analysis

B. SWOT

The method can be different, what matters is the exhaustive identification of the reasons which are affecting the performance of the chatbot

I like to use the Root cause analysis method as it helps to bifurcate the reasons the inputs received from various teams. Chatbot creation is not an individuals task, it’s a team effort to bring in the best understanding of the customer journey and integrating it through the chatbot.

Primarily the reasons can be

1. Technical

2. Communication

3. Response Time

Collect the data at each level and disseminate the information to the respective stakeholders of the various teams involved.

Trending Bot Articles:

1. Case Study: Building Appointment Booking Chatbot

2. IBM Watson Assistant provides better intent classification than other commercial products according to published study

3. Testing Conversational AI

4. How intelligent and automated conversational systems are driving B2C revenue and growth.

On primary analysis the major reasons could be.

Technical gaps could be

1. The chatbot is slow

2. Chatbot is not opening

3. Not able to redirect it properly to the support team

Communications gaps

1. Less information fed in for the customer to get redirected to the right support expert

2. Interaction points are exhaustive — Customized response based on the set of customer queries

Response/Support gaps

1. The support team is empathetic to the customer

2. Average Handling time(AHT) duration needs to be reduced to reduce customer fatigue

These are the broad categories of errors that might occur with your chatbot which in turn is dropping your customer satisfaction of your chatbot and addressing them in tandem can increase the CSAT gradually.

P.S. Below is the link to a video of a conversational chatbot created by me for a real estate platform a couple of years ago.

ChatBot

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How to improve the dropping customer satisfaction of the ChatBot was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

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