Month: August 2021

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Is it possible, or even worth trying?

To answer this question I’ve spent a lot of time thinking and investigating neural science, algorithmic trading, crypto trading and found something really interesting.

Disclaimer: if you are reading this article, I assume that you’re acknowledged about stock/crypto markets and have basic understanding why you need a bot or you’re just interested in their theory. This article won’t contain any code parts and it’s for educational purposes.

About Trading Bots

Let’s start with facts. Trading bots are not new and there are plenty of publications about it, they are used by financial structures, but are they really helpful? I think so, but if you are a programmer or you acknowledged basic concepts of scripting, you are able to write your own bot in few hours. But will it earn enough money for you? Will it have stable earnings? Will it ever hit 100,000$ annual return? I’m going to answer these questions in this post and give you some shots to move forward.

1.What is a trading bot?
A trading bot is an algorithm that turns specific market conditions into order decisions (usually buy, sell or hold). That’s it, nothing special.

2. What types of trading bots exist?
All types that any trader could take, as the bot is an algorithm written by programmers, they could put any logic in it.
In general, we have different types of traders:
• Long-term traders — investors;
• Swing traders — those who place orders on a week, month, or year basis;
• Day traders — those who place few orders through the day without moving them overnight;
• Scalping traders — those who place many orders per day, an hour, or even a minute.
All these trader types could be implemented in a bot.

3. Where trading bot could place orders?
Anywhere you want and could get to broker’s API or through reverse engineering. But you may even simulate your own broker conditions, commissions, taxes, spread, price just by making simple random movements, this simulation won’t contain the psychological part of a market, but it will be a good start for testing a bot. More about designing a great bot I’ll publish separate writing.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

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4. What about bot implementation types?
It’s better to say, types of algorithmic trading. As the bot is a complete program that implements the trading behavior of a trader in an automated way.
• Neural Network or Artificial Intelligence bots — could be simple single-perceptron bots based on few neurons, complex LSTM networks, or even artificial news analysis based on keywords heuristics and ranking.
• Quantitive trading — based on a strategy combining any criteria for making a decision, it could be comparing indicators, price action, finding patterns, etc.
• Semi-automatic bot — will use some algorithms to suggest to traders what to do. Indicators based on some strategy are part of this type.
• Genetic algorithms — it could be put into the machine learning/neural networks part, but it’s not really investigated enough to decide this type of algorithm as a machine learning approach. Genetic algorithm implementations differ from person to person and are investigated by universities throughout the world and are part of a bigger topic than this one (but I’ll discuss it later, stay tuned)

Alright, I’ve answered the above four basic questions you may think about before starting writing any bot. But what’s next? After understanding what is a bot, we may think about measuring their KPI.

Measuring Bots Quality

To measure the bot’s quality we may use the back-testing technique, which assumes any time range on a specific timeframe to execute orders based on previously available data. Let’s take some heuristics to work with, such as available cash, a timeframe it works with, stop loss and take profit ranges. We may use any other based on any trading strategy we want (for example neural network bots could determine their heuristics based on market conditions).

The best way to determine strategy quality is to write your own using TradingView. Using their documentation you’re able to write a strategy on Pine Script (which has really simple syntax).

As you may see in the picture above, I’ve implemented a simple strategy based on entering a long position after each green bar.

It won’t work on Binance or similar crypto brokers as using 0.01% stop loss and 0.5% profit. It’s possible to automate trading on this percentage and even place a stop-limit order in its range, but it won’t be possible to survive with commissions that a broker proposes.

For example, Binance proposes a 0.04% commission for a maker order (any market order) on a basic VIP level. This will execute any stop-loss order in 0.01 + 0.04 * 2 = 0.09% loss for 0.5% profit. This strategy won’t survive with a 1:5 profit ratio, as we have only 2.79% profitable percent (that means only 2% of all placed orders are winning, others are executed with stop loss).

Using full statistics taken from TradingView we are able to design our bot or back-test strategies faster and easier before we will use real market or paper-trading for writing a program.
After you see something like this:

Where you have a good net profit in combination with a profitable percent higher than 60 (at least), you may think about implementing a real trading bot.

But wait, does it mean that bots are effective? Can we answer now on this question? Sure.

Do Trading Bots Help Earning Money?

Of course yes. That’s why many hedge funds, banking structures, and big financial companies hire machine learning and algorithmic specialists. Those people are responsible for implementing automated trading bots to play in the real markets with big money.

So how much money do they make? Can we calculate and answer?

It depends on many factors. At least heuristics programmers put in it. Risk management, market conditions, available cash, etc.
You may find that a good prediction inside a trading day with low volatility could give about 0.6-1% of a stock move. If your bot won’t lose any trade in a trading month, you would earn about 20% each month, for the “all-in” strategy, a 10k$ account will earn 2000$.
We may use margin accounts with leveraged orders, risk managements, or pyramiding, using short stop loss or long take profits or different trading bot types, all of them will work differently.
A bad algorithm will just blow up whole your account if any mistake was written. So make sure you make all unit tests and use your bot on paper trading before starting using it with real money.

So could it make 100k$ in a year? Sure, proper risk management, strategy, and a proportional amount of money could give you this return.

Comparing Machine Learning and Quantitive Algorithms

It’s an important topic to discuss the difference between neural networks and quantitive analysis. What are the reasons to use machine learning or neural network algorithms? They could see patterns based on historical data better than people.

How do they determine patterns? It depends on a neural network type. You may implement an LSTM network or a single-layer perceptron. There are plenty of different investigations for other types of networks, so it depends solely on your choice.

Do they effective? Yes. They really find patterns with a properly written algorithm by using learning with a teacher or without a teacher. I was implementing a single-perceptron neural network and put few indicators in this bot (some of them my own indicators, some of them based on RSI, Bollinger Bands, and Stochastic RSI), I’ve created a function that takes a time range and runs neural network through candles finding a bar after which there’s a constant bullish or bearish movement. The second function was teaching neural networks using bar indicators and put a 1 or 0 as an output neuron (1 is buy prediction and 0 is hold).

Then I took neural weights and wrote a strategy using Pine Script to visually represent the bot’s predictions. And it worked better than I was thinking.

So this approach makes a big sense, but it requires more heuristics to learn, like where to put stop and take limit orders, what risk to use, etc. But this is a good example of using neural networks in practice and it works.

The quantitive approach is similar to neural networks, but instead of using machine learning to determine patterns, the programmer should determine them by himself. This makes it easier to determine the exact strategy, when to leave a position and how to manage risks. More than that, in a quantitive approach it’s possible to make not an automated bot, but a great indicator with a collection of compared conditions, and the trader will make his own decision using this analysis and overall market situation.

Is It Stable?

It depends. It depends on stock and market conditions, chosen strategy, and algorithm type. A bot could make a 2% return for a day and then the market will change its direction and it will blow up day’s profit and make a 3% loss.
Programmers should care about risk management.

For example, simply stop bot for the day if day’s loss or profit reached some mark (like 1% loss for the day and 2% profit is enough). Market conditions are changing between years, months, days, or even minutes. Fundamental news, panic on market, or market movers making big buys or sells (like Tesla on Bitcoin). These moments could break any algorithm including complex neural networks if they don’t implement risk management and proper stops.

Conclusion

Trading bots are an effective way of increasing your income with automated trading, but it should be made in a planned way, well tested before starting it on real money. Make sure you’re well acknowledged about technologies you’re using for making and algorithmic trading, aware of pre-made bots that are offered for some price (many of them are working on patterns for only 1–2 weeks they’re tested for promotion).

Later I’ll write some publications about practical usage of algorithmic bots, how to write proper strategies on Pine Script, also with examples of genetic trading and my investigations, so stay tuned!

Don’t forget to give us your 👏 !

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Get Rich With Trading Bots 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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Chatbot technology has been around for a while now, and it seems to be gaining in popularity and global market value every year, and for a number of reasons. For one, modern chatbots leverage artificial intelligence and machine learning to create truly engaging experiences and handle more complex challenges, which is something that their predecessors couldn’t achieve. In the grand scheme of things, modern, AI-driven chatbot technology can help grow your business in the online world by elevating your marketing, sales, and support processes.

There are numerous chatbots that you can try depending on your needs and long-term goals, but before you start integrating and optimizing this technology, you need to gain a deeper understanding of its potential. Integrating a chatbot into a WordPress site is a relatively straightforward process nowadays, however, it’s important to understand its uses and potential applications in order to leverage it for growth and success in 2021 and beyond.

Let’s talk about the key benefits of chatbot technology for your WP site that you need to know in 2021.

Cut waiting times to zero

A slow loading time can ruin a website’s chances of ranking high in the relevant search results, simply because modern customers won’t wait more than three seconds for your website to load fully and properly. So why would they wait around for you to answer their questions or address their concerns? Your ability to address the needs of your customers immediately can significantly boost your conversions, customer retention, and the lifetime value of the individual — but if your reaction time is slow, you risk losing them for good.

That’s why it’s so important to have a live chat software on your website so that your customer service agents can engage with them quickly. But what happens when people try to reach you when your team is out of the office? Keep in mind that people want answers to their questions now, not later or the next day, which is why it’s so important to have a chatbot that will engage with your customers and cut the wait times to zero.

Nowadays, chatbot technology is advanced enough to provide conversational experiences, and is able to handle more complex customer queries, ensuring that the customer will most likely find a solution to their problem by engaging with your chatbot right there on the spot. If their problem is more complex and requires a human customer success agent, then the chatbot can easily forward the request to your team.

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Create an engaging experience

In the competitive online world, engaging your customers in meaningful conversation across a variety of relevant touchpoints and channels should be one of your top priorities. Fortunately, there are many ways you can elevate customer engagement through proper branding, personalized communication, gamification, social proof and content marketing, and more. But what you might not have known is that you can also leverage your website’s chatbot to deliver personalized, engaging experiences to your users and returning customers.

One of the biggest benefits of conversational AI is its ability to personalize the user experience on your website for the individual according to their browsing behavior, purchase history, and the way they interact with your brand. Most importantly, though, a conversational chatbot will also make the interaction feel natural and organic, moving the conversation towards a solution and a desirable outcome for both you and the user.

Complete your omni-channel support structure

Building omni-channel experiences should be one of your key long-term goals if you want to boost brand awareness and trust, but at the same time reach more potential customers and generate qualified leads. Keep in mind that the modern customer uses numerous digital channels to find relevant information, products, and the solutions to their problems, and it’s important for your brand to have a presence on all those channels in order to provide seamless support and guidance.

Having an omni-channel support structure is one of the key digital marketing trends and sales tactics nowadays, and a website chatbot would help you complete your omni-channel strategy. Installing a chatbot on your WordPress site will allow you to deliver a seamless brand experience when a customer ventures to your site from a social media platform, for example, by offering a consistent brand narrative and a quick fix to their problems.

Use a chatbot to boost your marketing strategy

In recent years, chatbot marketing has been on the rise across platforms and industries because of its ability to guide customers towards different solutions seamlessly and without them having to engage in conversation with a support agent. Not every customer wants or needs to talk to a human representative, as many people simply want a quick answer to their question in order to decide on a product. Whether they have a simple question or want to learn more about your products or services, you can easily guide them down the right path with a conversational chatbot on your site.

This is one of the best ways to use a chatbot in your marketing strategy, as the chatbot can offer different conversation paths based on the customer’s needs. As you might have guessed, this allows you to perfectly align the interaction with the user intent.

For a user who is looking for quality information but is not ready to buy anything, your chatbot can select some high-quality articles or direct them to your learning center. But for the customer who is ready to buy, the chatbot can help improve sales by allowing them to place an order immediately, or provide them with additional information that will prompt them to buy.

Leverage chatbots to drive business intelligence forward

Data science is quickly taking over as a key driver of business success in a world where technology is affecting the future of customer service and marketing. Now that millions of people are using online services and platforms to buy products, educate themselves, and build meaningful connections with their favorite brands, you need to leverage the right tech to collect and organize that valuable data.

The more information you have about your customers and your market, and the prevailing trends in your industry, the more equipped you are to make better strategic decisions and investments.

That said, you can’t capitalize on such vast amounts of data without the help of artificial intelligence, which is why AI-driven big data analysis is the key to the success of data science in your company. As you might have guessed, a conversational chatbot can act as another smart data collection tool that will generate valuable insights from customer interactions on your website.

You can use this data to drive numerous key processes forward, and optimize your approach to sales, marketing, and support based on the data that your chatbot collects automatically. You even take things a step further by using your chatbot to deliver engaging feedback options to your website visitors and inspire them to leave more detailed feedback to help you drive innovation and your entire business forward.

Over to you

Integrating a chatbot into your WordPress site, whether you’re using it as a SaaS site, an Ecommerce store, or a blog, would be a wise business move in 2021 and going forward. There are many benefits to having a conversational chatbot as a key part of your brand experience, and in the long run, you can expect this technology to help you acquire and retain customers with ease.

Don’t forget to give us your 👏 !

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5 Benefits of Chatbot Technology for Your WordPress Site in 2021 was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

“Speech Recognition” August 2021 — summary from Arxiv, Europe PMC and Springer Nature

Arxiv — summary generated by Brevi Assistant

It’s challenging to personalize transducer-based automated speech recognition system with context information which is inaccessible and vibrant during version training. Experiments reveal that the design improves standard ASR model performance with about 50% relative word mistake rate decrease, which also substantially outperforms the baseline approach such as contextual LM biasing. In this paper, we provide AISHELL-4, a sizable real-recorded Mandarin speech dataset gathered by 8-channel round microphone selection for speech processing in conference scenario. Provided most open resource dataset for multi-speaker tasks are in English, AISHELL-4 is the only Mandarin dataset for conversation speech, supplying added worth for information diversity in speech neighborhood.

Subword units are commonly utilized for end-to-end automated speech recognition, while a completely acoustic-oriented subword modeling approach is somewhat missing out on. Experiments on the LibriSpeech corpus show that ADSM plainly surpasses both byte pair encoding and pronunciation-assisted subword modeling in all cases. The task of speech recognition in far-field settings is adversely influenced by the resonant artefacts that evoke as the temporal den….tion of the sub-band envelopes. Further, the series of actions associated with envelope dereverberation, attribute removal and acoustic modeling for ASR can be applied as a solitary neural processing pipeline which enables the joint learning of the dereverberation network and the acoustic design.

As speech-enabled gadgets such as smartphones and smart speakers become increasingly common, there is expanding rate of interest in building automatic speech recognition systems that can run straight on-device; end-to-end speech recognition versions such as frequent neural network transducers and their variants have lately emerged as prime prospects for this task. Automatic speech feeling recognition is a challenging task that plays an important function in all-natural human-computer communication. Among the main challenges in SER is information scarcity, i. e., insufficient quantities of thoroughly labeled information to construct and fully discover intricate deep learning models for emotion classification.

Please keep in mind that the text is machine-generated by the Brevi Technologies’ Natural language Generation model, and we do not bear any responsibility. The text above has not been edited and/or modified in any way.

Source texts:

• https://arxiv.org/abs/2108.07493v1
• https://arxiv.org/abs/2104.03603v4
• https://arxiv.org/abs/2104.09106v3
• https://arxiv.org/abs/2108.05520v2
• https://arxiv.org/abs/2104.02207v3
• https://arxiv.org/abs/2108.02510v4

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1. How Conversational AI can Automate Customer Service

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3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

Europe PMC — summary generated by Brevi Assistant

This work concentrates on durable speech recognition in air traffic control service deliberately a novel processing paradigm to integrate multilingual speech recognition into a solitary structure using three cascaded components: an acoustic model, a pronunciation model, and a language version. We confirm the proposed method utilizing huge quantities of real Chinese and English ATC recordings and attain a 3.95% label mistake rate on English words and chinese characters, surpassing various other prominent strategies. History Clinicians routinely make use of impacts of speech as an element of mental condition examination. Individuals with predominantly positive v. adverse signs and symptoms could be identified with an accuracy of 74.2%. Goal To explore the impact of optimal power output of bone conduction hearing tools on speech recognition in silent and in sound in skilled users of bone transmission hearing gadgets. Outcomes Both speech recognition in quiet and speech recognition in sound improved substantially when using the gadget with high vs. lower maximum power output. Goal To contrast differences in audiologic results between slim modiolar electrode CI532 and slim side wall electrode CI522 cochlear dental implant receivers. Approaches Comparison of postoperative AzBio sentence scores in silent in adult cochlear implant recipients with SME or SLW matched for preoperative AzBio sentence scores in peaceful and helped and alone pure tone standard. Objective Congenital acoustic atresia triggers severe conductive hearing loss disturbing acoustic development. Individuals with aural atresia had fairly high proper response rates for monosyllables with low right response rates by patients with SNHL. Function Knowing target location can enhance grownups’ speech-in-speech recognition in complicated auditory atmospheres, yet it is unidentified whether children listen uniquely in space. This research study reviewed covered up word recognition with and without a pretrial cue to location to characterize the impact of listener age and masker type on the advantage of spatial cues.

Please keep in mind that the text is machine-generated by the Brevi Technologies’ Natural language Generation model, and we do not bear any responsibility. The text above has not been edited and/or modified in any way.

Source texts:

• https://europepmc.org/article/MED/32833649
• https://europepmc.org/article/MED/34344490
• https://europepmc.org/article/MED/34369239
• https://europepmc.org/article/MED/34399646
• https://europepmc.org/article/MED/34370598
• https://europepmc.org/article/MED/34403280

Springer Nature — summary generated by Brevi Assistant

Speech recognition in loud environments is just one of the long-lasting research styles however remains a very essential challenge nowadays. We use the general public Arabic Speech Corpus for Isolated Words, three noise degrees, and 3 noise types. This work proposes an unique stochastic deep resilient network for speech recognition. The novelty of the SDRN network is in making use of NOWOA to acknowledge huge vocabulary separated and constant speech signals. The internal schedule of silent speech offers as a translator for people with aphasia and maintains human — machine/human communications functioning under various disturbances. In the approach, the tattoo-like electronic devices imperceptibly connected on facial skin record high-quality bio-data of numerous quiet speech, and the machine-learning algorithm released on the cloud acknowledges properly the quiet speech and lowers the weight of the cordless procurement module. Automatic speech recognition might potentially improve communication by giving transcriptions of speech in real time. We tested the performance of three cutting edge ASR systems on two groups of people with neurodegenerative condition and healthy and balanced controls. In the field of speech recognition systems, existing work concentrates only on the classification of speech right into a stammering speech or a regular speech. Significant renovations consisted of in this research study contrasted to previous implementations is developing a new deep-learning algorithm, which improves speech recognition for people dealing with stammering. Determining people’s sensations when they talk is relatively simple as a result of the tone and language with which they express themselves. With view analysis formulas in combination with voice recognition and the basic usage of NLP, it is feasible to produce intelligent systems that enable the analysis of people’s sensations based on the audible message that they discharge.

Please keep in mind that the text is machine-generated by the Brevi Technologies’ Natural language Generation model, and we do not bear any responsibility. The text above has not been edited and/or modified in any way.

Source texts:

• https://doi.org/10.1007/s10772-021-09847-7
• https://doi.org/10.1007/s10772-021-09851-x
• https://doi.org/10.1038/s41528-021-00119-7
• https://doi.org/10.1007/s10772-021-09836-w
• https://doi.org/10.1007/s10772-021-09828-w
• https://doi.org/10.1007/978-3-030-68663-5_10

Brief Info about Brevi Assistant

The Brevi assistant is a novel way to automatically summarize, assemble, and consolidate multiple text documents, research papers, articles, publications, reports, reviews, feedback, etc., into one compact abstractive form.

At Brevi Assistant, we integrated the most popular open-source databases to empower Researchers, Teachers, and Students to find relevant Contents/Abstracts and to always be up to date about their fields of interest.

Also, users can automate the topics and sources of interest to receive weekly or monthly summaries.

Don’t forget to give us your 👏 !

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“Speech Recognition” August 2021 — summary from Arxiv, Europe PMC and Springer Nature was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

Where is the next great marketing innovation coming from? The advertising industry has changed drastically over the last decade, especially outdoor advertising. New technologies are pushing the industry forward with artificial intelligence, machine learning, voice search, and digital out of home (DOOH). Also, we need to consider the outdoor advertising advantages when used in collaboration with voice technology.

More and more advertising space is now available online, and digital out-of-home (DOOH) solutions have expanded significantly.

Most recently, COVID-19 has become a major disruptor in the world of outdoor advertising. It has disrupted the ways in which humans interact with the world, but, in non-pandemic years, people spend 70% of their time outside at work or school, commuting to shopping, or doing other activities. Outdoor is where OOH shines as a medium-allowing advertisers to reach those who spend most of their time outdoors.

However, outdoor advertising is again on the rise. There’s a lot to keep an eye on in the space, but marketers need to be ready for what comes next.

The current state of outdoor advertising advantages

Outdoor, or Out-of-Home, advertising is making a comeback. With users becoming more and more tired of being bombarded with advertisements online and on their mobile devices, outdoor advertising is ideal for businesses seeking authentic exposure.

Out-of-home advertising allows consumers to see a brand in their natural environment and contributes heavily to an attractive brand image. It’s effective in creating brand loyalty and remaining consistent through multiple brands, products, and services. It’s also a great way to drive traffic to your business, which can lead to an increase in sales.

Basic outdoor advertising advantages

Creativity

This translates to better methods of attracting the attention of your audience and getting them to see your banner.

People can never avoid seeing one

There is no AdBlock service for outdoor advertising, and people will always have their attention attracted towards banners or billboards.

It is open to new technologies

OOH and DOOH have always been welcoming towards new technologies that can help them perform better and retain more engagement data.

It grants exposure to millions of people

When choosing the right location, a single banner, billboard, or bus-side ads, it can generate millions of views. Also, if it does not reach the desired number of sales, it surely generates a lot of brand exposure.

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1. How Conversational AI can Automate Customer Service

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Budget trends in OOH & DOOH advertising

The total DOOH market in Europe is worth nearly €9.4 billion in 2021. While this is small compared to the €28.5 billion achieved in the traditional OOH market, we expect it to grow to €13 billion by 2024, while conventional OOH will remain relatively flat. DOOH is now the second-fastest-growing advertising medium (trailing only the mobile internet) and is predicted to account for over 30% of OOH revenue in some mature markets.

Outdoor advertising problems and how to solve them

Out-of-home advertising, TV advertising, and other forms of advertising that do not provide a saving option focus on connecting with people while they are on the go or busy-with-hands. It can be while they are outside their homes or home doing “after-work” chores or routines.

According to IAB, Out of Home (OOH) advertising channels lose parts of the budget dedicated to marketing by companies compared to online advertising channels. It happens because outdoor advertising channels have a lower interaction time than online platforms, and there isn’t any precise tracking. Let’s find out some problems marketing teams face when using these channels:

Reduced time of exposure

The OOH & DOOH ads and other similar media need to be assimilated in a short amount of time. In some cases, the audience might not have that short amount of time to evaluate and come to a decision regarding the ad. Targeting media that has a short exposure time is difficult.

Not anyone driving past a billboard is part of the target market. Exposure time is short, so messages are limited to a few words and/or illustrations. What if users want more information?

Difficulty in measuring the audience

It is challenging to measure the audience regarding these forms of publicity. For example, to provide reliable metrics on a (D)OOH system’s audience, you need to use heterogeneous research or technological tools. But, more than challenging, it is not possible to have valuable information for these audiences that you can share with the brand the ad is about.

No Lead generation possibility

One of the strong points of outdoor advertising is the vast audience they target. There is 100% Human traffic, ads are unskippable, no ad blocking option, and people can view the ad every day if they have the same walking routine. Does your company have this data? Who are these people? Is there a way to get their phone, email, or name if they are interested in what they see? The current technology does not provide that.

The outdoor advertising advantages of using Voice Technology as a solution

The solution is hidden in Artificial Intelligence, specifically in Voice Technologies. Voice is the most natural way for people to communicate with each other, and lately with brands. It is natural to ask with voice questions like where to find this or that service.

How is this possible: thanks to voice applications.

Users face every day a call for a link to click. Outdoor advertisements like ads in buses, buildings, and more need to generate awareness and increase numbers on marketing reports. The same happens with an ad displayed on a billboard or a bus station display. However, there is a lot of friction to access these links while in the real world.

Through voice applications, you can enhance the user’s experience from OOH advertisements by sending it to a voice assistant. It can be easily activated via voice on a mobile phone and then let the conversation begin. The experience with the brand is naturally extended.

What is a Voice Application?
A Voice Application is a voice-enabled software application that can respond to spoken commands or queries. Such applications can be used in the home, workplace, in the car, or on mobile devices. In our case, we are referring to voice applications like Alexa Skills and Google Actions.

How can Voice Applications work for Outdoor Advertising

When a brand requests a D/OOH marketing campaign, all your company needs to do is to create and integrate a voice application dedicated to that campaign. Ipervox will help you create the voice application, be it an Alexa Skill or a Google Action. This voice app will be designed to enhance the user experience with the ad and extend the ad’s time of exposure to the user.

Next, your company will take care that the creatives include the wake word of the voice application inside of them. The wake word will serve the customer to easily access the voice app, using a single voice command.

When the user sees the advertising, the only CTA for them is to activate the voice application for further information. Also, they will be able to save the link, access it later, and much more than that.

What are the pros of this methodology (there are no cons)

Voice Applications are the bridge between Outdoor Advertisement and target audiences that, for the moment, can give power to these marketing channels. They can generate a higher number of leads, users & potential clients data, deeper analytics, and more.

An extended time of exposure

Thanks to the voice application dedicated to that campaign for different advertising channels, the user can ask their smartphone with the wake word and get all the information needed without stopping what they are doing. The communication happens in less than a minute; thus, there is no problem if the user is moving or with busy hands. The voice app can inform the user directly or send an SMS/email on their phones with detailed information regarding the offer.

Easy and frictionless way to measure the audience

You can bring back OOH advertising power thanks to the voice applications. The company can easily, through Ipervox, have the data of all interested users that want to know more about the publicity they were exposed to. Once the user activates the voice app, we can get the user’s data, like email or even phone number. This also gives the possibility of distinguishing the users from specific ads, giving valuable data for A/B testing, or even ad location and channel distribution.

Lead generation for each advertisement

Each advertising done through these channels can have the possibility of displaying a call to action with voice. The marketing company can also quickly gather data for each ad. The users that will activate the voice app to know more about the product can now be converted into identifiable leads. This is compared to previously, where there was no tracking of the users that gained interest from the ads.

You have to consider that, without the use of Voice Applications, the user needs to act immediately, either because the ad moves too fast or because they have to keep going. They need to memorize something from the ad, be it the company’s name, some link URL that invites them to go and visit it, or price, product logo, and more. A lot of information, little time.

Using Voice Applications instead, can really enhance the existing Outdoor Advertising Advantages and much more. In this case, the user does not need to stop what they are doing. Since the ad will lead the user to the voice app’s activation, they can ask their smartphone by voice to activate the app that gives more information regarding the advertisement. They can also ask for more information to be sent to their emails or phones as a text message and learn more about it later. There is no need to take notes, remember anything, or leave it for later (and probably forget about it).

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Outdoor Advertising Advantages When Combined With Voice Technology 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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The advancement of the Internet has brought changes in almost every field. One of those changes is the shift of customer support to the Internet. Email support, live chat, chatbots, and conversations on social media are just some of the countless examples of virtual customer service.

With a bit of help from artificial intelligence, companies are skyrocketing their customer support to a whole new level. Artificial intelligence helps place various customer support channels on one single platform, and it easily automates the tasks that traditionally consumed a lot of human time. Managing customer support has become very easy for companies, and as far as the customers are concerned, they get a seamless user experience at every support channel.

Does this automation mean that we should move on from using traditional customer support channels, such as VoIP (Voice over Internet Protocol)? The answer to this question is NO. A lot of users value human contact more than any conversation with robots or AI bots.

Fortunately, you don’t have to pick between AI Chatbot and VoIP. Instead, you can combine these two to make your service even better.

Importance of Voice Calls in the Era of Chatbots

Over many customer service channels, local users still prefer voice calls to get their queries solved. A comprehensive study by BrightLocal shows that around 60% of the customers like to call the company to get more information after finding them online. Moreover, only 16% of the users are inclined to use email support, and people just shy away from using social media for having a conversation.

No matter what type of company you are in, be it SaaS or e-commerce, voice calls allow you to build a more reliable relationship with your customers. With voice calls, the users rest assured that real people are supporting the business, not just AI and bots. Even after being so sophisticated, AI still lacks that human touch.

Customers are starting to notice the missing human elements. According to a study by PWC, around 60% of people globally believe that many businesses have lost the human touch in their customer service. Moreover, 71% of Americans claim that they would rather have a conversation with human executives than AI chatbots.

Overcome the Challenges Faced in Voice Call Support

While voice calls are still the backbone of the customer support industry, they might face some problems, including:

• Low customer satisfaction
• There are just too many tools
• The reporting and analytics is not accurate
• Poor performance and employee dissatisfaction

One of the best ways to improve the effectiveness of voice call support is by switching from a traditional phone system to VoIP. Unlike PBX or analogue phone systems, the data in VoIP is transmitted over the Internet.

In VoIP, there are features like call queuing and call routing, which ensures that the customers connect with the right agent at the right time. Moreover, VoIP can enhance the quality of voice calls, for which all you need is a solid internet connection. This service is entirely cloud-based.

Because VoIP can be integrated with CRM software, you can easily track and collect customer information consistently. This means whenever a lead is converted into a customer; their data will be already there in the system for the customer support executive to use it. It can provide the detail of their buying journeys which can help you deliver personalized support.

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Need to Combine VoIP With Chatbots

Advanced chat technology is an exhilarating prospect. However, we are still a long way from chatbots replacing voice call support. Instead, it is best to use chatbots and VoIP in tandem to produce the best results for both agents and customers.

When people have to ask simple questions or when they expect quick fixes, they prefer chatbot over VoIP. There’s no complex theory behind it. The reason is quite simple- regardless of the time zone, the chatbot provides straightforward feedback in real-time.

Because these virtual agents are based on artificial intelligence, they can support your live customer support agents in many ways. To start with, chatbots allow the agents to work on more complex problems by providing quick answers to repetitive customer queries.

Moreover, you can increase the productivity of your agents by placing a chatbot to whisper in their ears. For example, imagine that there’s a major discount on your website, a bot can easily make it prominent to your customer support executives, and these executives can then pass on this information to the customers if needed. It can save the time of agents by finding various information in a jiffy.

Furthermore, chatbots can help users in making quicker shopping decisions by gamifying and personalising their experience. You can use them to ask relevant questions to your customers and based on the answers, you can suggest the best-suited products or services.

Move Seamlessly From Channel to Channel Using ACD

The use of Chabot with VoIP is just adding yet another channel to make it easy for your customers to reach out to you. Your customers expect to reach you by whatever medium they prefer be it social media, VoIP, SMS, or chatbots.

However, just like adding any new channel, the addition of chatbots to VoIP also requires deep integration. You need to reconsider and redefine the customer journey in order to provide a better experience. The flow of data should be seamless from channel to channel.

To make this flow of data seamless, you can even use something like Automatic Call Distribution (ACD). It is mainly a telephony system that can answer the incoming calls of your customers and redirect the customer to a specific agent, branch or department of the company.

To work and route the calls to the most appropriate agent, ACD needs Computer Telephony Integration (CTI) or Interactive Voice Response (IVR). It streamlines the whole process of communication, which makes it a backbone of the customer support industry.

With the use of ACD, you can:

• Route incoming calls to specific agents on the basis of some predefined criteria.
• Identify VIP callers and provide them with rapid response.
• Acquire usage data like the phone number of callers, time spent on a caller, total number of calls, length of calls, waiting time, and much more.
• Engage in call conferencing, call barging, call monitoring, and whisper coaching.
• Make an automatic call back and put multiple callers in the queue.

Track and Analyse Customer Interactions

Investing money in the integration of chatbot, VoIP, and various support channels will not guarantee desired results if you don’t keep checking their effectiveness.

When your channel has chatbots and VoIP, then tracking and analysing the effectiveness becomes easier. This software provides you with advanced analytics, and all you have to do is select the most suitable metrics to determine the success of your customer support channels.

These metrics can be:

• Engagement metrics like the number of bot sessions initiated, the bounce rate, goal completion rate, etc.
• Customer satisfaction metrics such as the rate of retention and the satisfaction score.
• Conversion metrics like chatbot interaction vs human interaction, interaction rate, conversation duration, feedback rate, etc.

In the traditional call centre, tracking and analysing the data is much more complex. This is where switching to VoIP and chatbots become advantageous.

Final Words

The skillset of bots and humans are not comparable; they are completely distinct.

The major advantage of human agents is that with the help of VoIP, they add emotions and human touch to your customer support. They are more likely to understand your customers, their needs, their preferences and choices, and more importantly, they can address your customers with empathy. Yes, AI technologies are getting advanced every day, but irrespective of that, humans will always be the ones responding to the complex queries raised by the customers.

On the other hand, you can use chatbots to automate your customer support and increase its efficiency. With its help, you can collect customer data from various channels and use it to increase the efficacy of your human customer support executives. More importantly, these chatbots can provide support 24/7.

Therefore, there’s no need to decide which one of these two, VoIP and chatbot, you should choose for your customer support. Instead, you should combine these two and appeal to different groups of customers.

Don’t forget to give us your 👏 !

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How To Use A Chatbot & VoIP Together For Better Customer Service? was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.