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Category Archives: Tech Trends

IoT solutions

Why Is UX Research Necessary for IoT Solutions?

People tend to think about websites and software when talking about UX. But with the age of IoT (the Internet of Things) upon us, UX design is expanding to new horizons. Our devices will be interlinked more than ever in upcoming years, so it’s time to think about how the popularity of IoT solutions will affect UX research.

There are a few basic UX design principles to keep in mind when conducting research for IoT. Read on to find them out.

The Importance of UX Research for IoTs

UX adds value to the Internet of Things devices by making them user-centric. While IoT are developed, UX research is performed to comprehend the ideal user and their needs.

The initial phase of UX design includes research, whether you’re designing for one website or a network of devices.

And one of the basic principles when researching is to think about the value an IoT device can offer your users and your business. When diving into IoT UX design, you’re not dealing with products anymore. You are now building services and experiences that have the potential to make users’ lives better. So a thorough qualitative analysis is vital for moving on with your UX design.

UX research should focus not just on attempting to make the product look pretty but also on providing users with seamless communications, high usability, and easily accessible customer support.

UX Challenges to Research for IoT Solutions

To develop an effective product, UX design for IoTs must mix several design disciplines. They are difficult to handle individually, let alone combined.

UX for IoT solutions needs to keep track of a variety of things – from standard paths to structures. And, a change from standard UX design will be this – you won’t just be designing the actions users want. You also need to make these products customized on a user basis and able to connect to different IoT devices. 

IoT solutions UX

UX challenges in the IoT sphere include:

  • Lack of efficiency – Embedded systems are still heavily ladened with expenses. You need to do proper research to figure out how you can minimize costs and further drive the development of various digital elements.
  • System security – Security is always an imperative. But it’s a special kind of challenge when you need to provide an excellent user experience for embedded systems. Taking a product from prototype to deployment will have a lot of security bumps to solve along the way.
  • Emerging standards – Some devices might be unaware of the presence or capabilities of others on the IoT network because their manufacturers have designed them to work exclusively with those of specific providers. The main challenge for developers is dealing with the potential interference of such different devices.

3 Key Components for UX design for IoT Solutions

Good UX design for IoT solutions has three components:

  1. Great technology functionality
  2. High usability
  3. Compatibility with human psychology

We’ll go over each in more depth.

Great Technology Functionality

To no surprise to anyone, you should focus a lot of your effort on successfully delivering a product. That is because you can’t just expect to sell your product solely on great marketing. Whatmore, false advertising can hurt your brand for years to come. Especially if a user’s first introduction to your product is a negative one. You should align your marketing messages with your product and the needs of your users.

High Usability

No matter if your user is highly educated in using technology, or just a novice, they should be able to set up your product. Operating and maintaining IoT should be even easier than non-IoT solutions.

Compatibility with Human Psychology

IoT should seamlessly go with human psychology. New tech should offer massive payoff for users to get them out of their comfort zones. UX design for IoT solutions should also strive to win the trust of users by making them rely on their devices for safe and simple actions.

Another thing the human mind will register as trustworthy is offering a user experience that pays attention to personal privacy.

Final Word

IoT is on track to become one of the most dominant technology trends. It will disrupt the scene and easily impact our everyday lives. IoT solutions are already present, so our interactions with tech devices are already evolving. And all those interconnected devices need detailed User Experience design. The key elements we have listed in this article can guide your UX research when designing for IoT.

hackers use AI

How Hackers Use AI and Machine Learning to Target Enterprises

AI (Artificial Intelligence) and machine learning are often touted as things that will bring both small businesses and enterprises to new levels. But the bad frequently follows the good. Meaning that while AI and machine learning improve cybersecurity, they are also being used by cybercriminals.

Cybercriminals are using advanced technology to create and launch sophisticated malware and cyber attacks that easily bypass and fool cybersecurity systems.

More complex cyberattacks are our future, along with increased frequency. So in this article, we will cover in more detail what AI and machine learning do when in the wrong hands.

Importance of Cybersecurity in 2022

With the increasing number of cyberattacks, spotting vulnerable spots in your IT infrastructure is crucial to keep your business’ data, hardware, and other software safe.

In case your company does fall victim to a cyberattack (which isn’t the end of the world because you can never be 100% safe), there are steps to take afterward. After neutralizing the threat, the important thing is to revise the security protocols using the lessons learned from the recent attack.

Another vital step is to never stop learning – hackers use AI and machine learning more and more, and you should know about the latest hacker trends and what exactly they do to extract sensitive company data.

What are AI and Machine Learning in Cybersecurity?

Artificial intelligence (AI) is great in assisting security operations analysts to tackle the cyberattacks’ increase in scale and variety. Artificial intelligence (AI) tech such as machine learning and natural language processing enables analysts to link together various threats.

Machine learning, as a subset of AI, creates automated analytical models. What this translates to is that it lets IT systems gain more insight and thus update various processes according to what the program experienced through continuous use. That allows IT systems to learn from previous calculations and adapt on their own.

Ways Hackers Use AI and Machine Learning

Hackers use increasingly sophisticated methods to breach IT security, gather information, and launch attacks. The usefulness of machine learning and AI also benefits cybercriminals. The following evolving threats in the IT sector are ones that your company needs to be aware of.

More Sophisticated Phishing Emails

Attackers create phishing emails using machine learning. On dark web forums, they are promoting the sale of these services. There, they mention utilizing machine learning to produce more effective phishing emails. They operate by creating fake personalities for use in scam efforts.

Hackers can use machine learning to creatively alter phishing emails so that they don’t appear in bulk email lists and are optimized to encourage engagement and clicks. They go beyond the email’s text. Hackers use AI to produce realistic images, social media personas, and other content to give the interaction the best possible legitimacy.

hackers use AI Cyber threat

Faster Password Guessing

Additionally, criminals use AI and machine learning to improve their password guessing skills. It is evident that password guessing engines now have more sophisticated techniques based on the frequency and success rates of criminal hacking attempts. The ability to hack stolen hashes is also improving as criminals are creating better dictionaries.

Additionally, they are utilizing machine learning to identify security measures so they can guess better passwords with fewer attempts, increasing their likelihood of success.

Using Deep Fakes

The deep fake tools that can produce video or audio difficult to distinguish from the real human speech are the most terrifying way hackers use AI and machine learning.

A few high-profile cases involving faked audio costing businesses hundreds of thousands or millions of dollars have come to light recently.

In order to make their messages seem more credible, scammers are increasingly using artificial intelligence and machine learning to create realistic-looking user-profiles and videos. It’s a huge industry. Since 2016, company email scams have caused over $43 billion in losses, according to the FBI.

Social Engineering

Cybercriminals use the tactic of social engineering to trick and convince victims to disclose confidential details or perform a specific action, like sending money abroad or opening an infected file.

By making it simpler and faster for them to gather data on businesses, employees, and partners, AI and machine learning make use of the actions of criminals. In other words, social engineering-based attacks are strengthened by artificial intelligence and machine learning.

Final Word

There are so many different aspects of cybersecurity to cover, and we covered just a tiny portion in this article. But it is enough to get you started and realize just how much hackers use AI and machine learning.

So if criminals are using the best technology out there to perform malicious activities, you should be breathing down their necks, too, by continuously updating your security systems.

Because remember – AI and machine learning can keep you safe from various cyber threats.

Customer Service Automation

Customer Service Automation [Definition + Benefits]

This post is all about customer service automation.

In fact, 31.7% of major companies already advanced technology to augment their customer support.

So if you want to know what tech to focus your business on and the benefits it can bring you, you’ll enjoy this article.

Let’s dive in!

What is customer service automation?

Customer service automation is a kind of customer support that relies on technology to reduce human involvement in the process of solving daily customer queries. Smart support automation solutions are intuitive to closely resemble human nature and its level of proactivity.

Types of CS automation

Businesses use different methods to introduce independent help desk solutions. 

Here are the most common types of customer support automation:

  • Simulated chats
  • AI chatbots
  • Email automation
  • Automated workflows
  • Pre-made responses
  • Contextual FAQs
  • Interactive Voice Response (IVR)
  • Social media case routing

All of these solutions can be used in combination. While the advantages are manyfold.

Benefits of automating customer services

Let’s go over some of the main benefits of customer support automation:

Customer Service Automation

Minimized Human Error

A key benefit of an automated contact center is the fact that it helps reduce the number of human errors. 

Although humans can be great at showing empathy to each other, they do not have the capacity to offer the same accuracy and speed when it comes to repetitive tasks like data entry or crawling through thousands of pieces of information looking for just one. 

Customers value fast and efficient help, without being bounced around from one agent to another, and having an automated call center is a sure way to reduce friction and end up with fewer errors that ruin the speed of problem-solving. 

Today’s automation tools powered by AI and machine learning technologies are also able to learn from previous interactions and modify their behavior based on the knowledge they accumulated. 

This helps them provide more accurate assistance that can only get better over time.

24/7 Support Availability

There is only a limited number of hours that human agents can work in a day, and if you want to make them available 24/7, your cost of labor will skyrocket. 

As opposed to that, automated support tools can provide non-stop customer service with no interruption, and without breaking the bank. 

For example, the use of chat automation allows you to offer online assistance without any human involvement. 

In the case of certain types of workflows, the chatbot can notify the staff about a potential interruption or the need for additional help. 

Moreover, having a service solution that is always available goes beyond regular customer support and tackles the care of prospects, too. 

Smart chatbots can gather invaluable information from potential customers without forcing them to fill out time-consuming forms. 

Customer Service Automation email

Improved Team Collaboration

Automated customer support tools can make team collaboration much smoother and more efficient by eliminating confusion and making it clear who owns a particular support ticket. 

Businesses that use automated help desk solutions benefit from having better-organized workflows built around solving customer issues, without any extra steps that would only waste the company’s time and money. 

For example, if a ticket is about to fall through the cracks, the automated system can flag it for an urgent review and remind the staff that its status hasn’t been changed for a while. 

Some tools even include an internal wiki feature that allows the staff members to share insights and other information with each other. This type of software can even offer personalized help to agents by sending them dynamic suggestions of which articles from the knowledge base would be most helpful for them to read at the moment.

Get started with customer service automation

If you’re interested in revolutionizing your customer service with automated solutions, our help desk support services are tailored to the needs of your business.

Contact us today to reach out to one of our specialists at Demakis Technologies.

AI customer support chatbots

AI-Powered Customer Service DONE RIGHT [+How to Do It]

Today, we’re going to explain AI-powered customer service solutions. 

You’ll see: 

  • Why AI works with customer services
  • How it improves workflows and productivity
  • How to set it up and do use AI correctly

So if you want to boost customer experience, you’ll enjoy this post.

Let’s start!

Why does AI-powered customer service work?

There are lots of benefits to using artificial intelligence in customer service. 

Less Staff

Customer service requires hard effort. Not all of the businesses have enough resources to hire staff to get the efforts done. That’s why AI in customer experience (CX) comes in handy. It’s economical in the long run, easy to use and obviously helpful. 


Integrating AI allows you to personalise and deliver your content to the right audience. This will provide your customer service better targeting. 


Automating daily jobs gives you and your employees time to focus on more complex tasks.

Better Customer Experience

AI support

Chatbots for artificial intelligence customer service can work round the clock without leave. 

Customers can have their inquiries with AI bots resolved 24/7. Also, they don’t have to wait hours or days for a response. This can greatly improve reliability and customer satisfaction. 

These are just some of the key benefits to using artificial intelligence customer service.

In truth there are many more, such as: 

  • Cost savings 
  • Improved conversion rates
  • Better customer retention 
  • Higher quality scores 
  • Greater precision

But to get ahead of the curb, you’ll need to use AI effectively.


How to effectively use AI in CX?

There’s an opinion that AI customer service is less personalised and effective. It doesn’t have to be the case, if done right. Here are the three hand-on tips on how to effectively use AI in CX. 

#1 Start automating user-specific queries

Most people think AI bots answer only basic questions, like: What’s your refund policy?

More user-specific questions are usually considered better answered by human agents. 

But that’s not necessarily correct. 

Today, AI bot can answer even more specific queries, like: When will my order get here?

AI and bots can actively pull customer data from CRM platforms.

So, when a customer asks for an ETA on their order, the bot taps into the order management system. From there, it pulls the order data and gives the customer a precise answer. 

Also, AI customer-facing bots can be programmed to learn from the past interactions. Still, they can’t do it on their own.

You have to program use-cases and commonly-asked questions specific to your business. 

#2 Train your chatbots to learn from agents

You need to educate your AI customer support chatbots. The more they learn from your agents, the smarter they get. 

Your AI bot needs to study successful agent-customer interactions from your experts. This way, it can respond with greater accuracy. 

Also, it’s good to set up a deflection team to monitor your bot’s initial performance. Leaving your bot going solo can be nerve-wracking, even to the most confident of CX teams. 

#3 Set up chatbots to assist agents

Customer-facing AI bots are extremely important. 

Still, you need to think about setting up agent-facing bots, too. 

They deal with ticket classification and routing, and relevant article suggestions for next steps. 

Agent-facing bots route specialised tickets to the right agents. 

This way, there will be no time delays. Also, Artificial Intelligence in call-centres helps avoid internal customer call transfers. 

ai customer service

Looking for AI and helpdesk support?

Customer service is going through a period of change for the better all thanks to AI. 

That’s why more and more companies choose to implement AI helpdesks. 

Many businesses saw significant improvements after they’ve included AI service desks. 

Do you feel like your organisation could benefit from AI and helpdesk support? 

If so, then you can get in touch with one of our Support Helpdesk experts for further assistance. 

Or, you can just follow our blog to stay ahead of competitors. 

chatbots and conversational AI

Chatbots vs. Conversational AI: What’s the Difference?

In this post, we will explain the difference between chatbots and conversational AI. You will get an understanding of what each of the terms means, how they relate to one another, as well as some of their key benefits.

Let’s begin!

What’s the difference between Chatbots and Conversational AI?

Conversational AI refers to the technology and tools that enable computers to simulate real human conversations. 

Chatbots, on the other hand, are programs that can use conversational AI to communicate with humans. But they can rely on other technology, as well. 

What is a chatbot?

A chatbot is a program that mimics human conversations in order to improve the quality of customer experience. 

Chatbots can function either on pre-built conversation flows or with the help of natural language processing (NLP) and artificial intelligence that enables them to get a better understanding of user intent.


Rule-based chatbots

Rule-based chatbots are the most basic chatbots out there. They function with the help of pre-set rules: if a user asks question “A”, the chatbot replies with answer “A”. 

Sometimes the conversation flow is designed in the form of a decision tree that gives clients the option to choose the answers based on their use cases. 

Rule-based chatbots somewhat resemble automated phone menus that prompt the users to go through a series of choices that guide them towards the information they need.

AI chatbots

AI chatbots (or contextual chatbots) utilize NLP, machine learning, or both, to recognize user intent and respond to it in a meaningful way. 

It’s the type of chatbots that has the ability to learn from every interaction with customers, so their ability to provide quality service actually increases with time. 

What is conversational AI?

Conversational AI is a term that describes AI-powered communication technologies that include chatbots and virtual assistants such as Amazon Alexa.

The technology helps deep learning algorithms understand human language and recognize user intent.

Thanks to NLP and machine learning, conversational AI platforms are able to recognize textual and audio inputs and facilitate the creation of realistic conversations. 

The goal behind every AI chatbot online is to create a feeling of real human interaction.

conversational artificial intelligence

How do chatbots relate to conversational AI?

Conversational artificial intelligence can be used to power chatbots. But not every chatbot can be described as a conversational chatbot.

Simply put, not all chatbots are considered a type of conversational AI. 

For example, rule-based chatbots that rely on pre-built scripts are not designed using conversational AI technology. 

A conversational AI chatbot can be very useful when it comes to mirroring human conversations for the sake of improving the user experience.

Chatbots & Conversational AI: Examples in Customer Service

Both rule-based chatbots and conversational AI agents can make a huge difference in the quality of customer service. 

Let’s take a look at some useful chatbot and conversational AI examples:

Domino’s ordering assistant chatbot

When the chatbot market started getting attention, Domino’s was actually one of the first businesses that put a Facebook Messenger bot in charge of taking orders through live chat.

The bot is also capable of tracking delivery times and redirecting customers to live agents whenever needed.

The chatbot named Dom is also present on other communication channels such as the company’s website and app, as well as Google Home and Alexa.

Amtrak’s virtual travel assistant powered by AI

Amtrak’s virtual assistant called Julie, also known as Ask Julie, has been an invaluable tool when it comes to helping travelers find all the necessary information without having to contact customer support.

Since the time Julie was launched, the platform has made an 8x return on investment by reducing the company’s customer service costs by a total of $1 million. 

There was also a 25% growth in the booking rate, as well as 30% more revenue than with bookings completed through other forms.

Customers can reach Julie through Amtrak’s website, or by calling the company’s phone number.

chat with AI bot

Improve your Customer Service with Conversational AI

According to NewVoiceMedia, US businesses lose $75 billion per year due to the poor quality of their customer service.

That’s why more and more companies choose to implement AI chat into their customer service sectors. 

Many businesses saw significant improvements after they’ve included a conversational bot in their customer service teams. 

The clients show no resistance when they chat with AI bot. In fact, they appreciate the speed with which an AI chat bot is able to resolve their issues.

If you feel like your organization could benefit from chatbots and conversational AI, follow our blog to stay ahead of competitors or get in touch with one of our tech specialists for further assistance.

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