Tech Trends Archives - Demakis Technologies

March 22, 2022March 24, 2022 Roxanne Demakis Managed Services, Tech Trends

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:

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.

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.

March 14, 2022March 16, 2022 Roxanne Demakis Managed Services, Tech Trends

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.

Personalization

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

Productivity

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

Better Customer Experience

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.

So…

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.

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.

February 8, 2022February 9, 2022 Roxanne Demakis Tech Trends

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.

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.

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.

February 4, 2022February 7, 2022 Roxanne Demakis Tech Trends

7 Practical Uses for AI in Your Financial Company

Artificial intelligence is changing the way we interact with money in finance.

Using AI in banking and finance is a way to meet customers’ demands who desire more convenient, safer, and more innovative ways to access, spend, save, and invest their money in finance.

In this article, you’ll learn how you can use the benefits of AI in finance.

Let’s start!

What is AI and Machine Learning?

AI has been shown as a beneficial resource for businesses, increasing the efficiency and quality of work produced.

The term AI refers to any software designed to function similarly to the human brain.

Machine learning, a type of AI, is a program that changes based on the information fed into it to train it and the feedback it receives from the humans who developed it and those who are using it.

AI software with machine learning capabilities can provide a faster research process while providing reliable investment recommendations.

Machine learning for financial services can significantly reduce operating costs and allow people to focus on making the best possible, informed suggestions for their clients.

Practical Application of AI in Finance

Now that you have a better understanding of AI let’s look at how you can apply artificial intelligence in finance.

#1 Evaluating investment opportunities

For a human, combing through massive amounts of data and comparing hundreds of data sources to one another is a difficult task.

With AI, this task can be done faster, with greater accuracy, and without bias.

AI finance solutions can even project the success rate/potential opportunity for each of the proposed options.

It’s beneficial to use AI for financial services firms because they can then devote more time to opportunities with a high probability of success and less time going through data that will most likely be ignored.

#2 Processing RFPs, loans, and credit requests

Opportunities are presented to financial services firms in the form of a Request for Proposal (RFP).

Because AI can use both unstructured and structured data sets, simply scanning your RFP will allow a machine to read it and learn whatever is required to develop your desired answer.

That eliminates the need for the time-consuming data submission process.

As more RFPs are processed, the data lake grows, implying that your machine is becoming smarter and smarter as it is used.

#3 Trading and financial advisory

It’s no surprise that artificial intelligence is frequently used in trading because it analyzes patterns within large data sets.

AI-powered finance solutions can go through data faster than humans, which speeds up the process and saves significant time.

AI technology and finance will allow you to stay on top of the latest financial trends or review your portfolio.

#4 Fraud detection and prevention

One essential operation that already benefits from machine learning is fraud detection.

A machine’s ability to track and compare numerous data points while instantly comparing the data to previous transactions on an account is incomparable to a human doing the same job.

Fraud detection AI systems in finance examine a person’s purchasing habits and raise an alert if something contradicts your usual spending habits.

#5 Risk assessment and risk management

Machine learning algorithms are being used by banks and apps to determine a person’s loan eligibility and provide personalized options.

The advantage is that AI is not biased and can make a loan eligibility decision quickly and accurately.

Risk management is always a challenge in banking.

Machine learning in finance can now assist experts in using data to identify risks, save the workforce, and make future planning easier with better information.

#6 Preventing cyber attacks

People want to know that their money and personal information will be kept as safe and secure as possible.

Human error is thought to be responsible for up to 95% of cloud breaches.

Artificial intelligence can help companies improve their security by analyzing and determining standard data patterns and trends and alerting them to inconsistencies or unusual activity.

#7 24/7 customer services

Customers can ask questions at any time of day or night, thanks to artificial intelligence and the prevalence of virtual assistants and chatbots.

They don’t have to wait to speak with a person.

AI increases productivity by reducing the time and effort spent on generic customer queries, allowing teams to focus on longer-term projects that drive business innovation.

Ready to use AI in your Finance Business?

With the popularization of AI, it’s no surprise that AI in the finance sector is taking off.

Especially now that COVID-19 has changed human interaction.

Using AI in finance has had a profound impact by streamlining and consolidating tasks and analyzing data and information far faster than humans.

Experts predict that it will save the banking industry approximately $1 trillion by 2030.
If you want to know more about Artificial Intelligence and its use in business, stay up to date by reading the latest trends in technology and business on the Demakis Technologies blog.

January 28, 2022February 7, 2022 Roxanne Demakis Tech Trends

Conversational UX: Definition & Benefits (+ 5 Best Practices)

This post will help you learn everything you need to know about conversational UX by answering the following questions:

What is conversational user experience?
How does it impact tech and web users?
What are the best ways to include it in your business?

If you are interested in learning how to improve user experience with this innovative approach, keep on reading!

What Is Conversational UX?

Conversational UX is a type of user experience that uses voice, chat, or any other form of language-based technology to simulate real human conversation. The end goal is to create the feeling of true human communication.

It defines the way businesses build chatbots, with seamless interaction as the final goal.

Why Is Conversational UX Important?

Let’s go over the three main reasons why conversational UX design is important:

Higher Agent Efficiency

When live agents are free from dealing with basic questions that chatbots can handle, they can focus on more delicate requests that cannot be completed without human contact.

The agents will no longer feel overwhelmed by the number of mundane tasks and they will be able to handle more queries.

More efficient workflows will also uplift the agents’ mood which directly improves the quality of customer support.

Better Customer Experience

Today’s customers have high expectations when they interact with businesses.

They seek convenience and solutions that will work around their schedule.

That is why the use of chatbots that are available 24/7 can improve the quality of the helpdesk experience dramatically.

Client satisfaction, another benefit of conversational UX, is one of the best marketing strategies.

According to Deloitte, customers are very likely to share positive experiences with nine other people.

More Conversions

Conversational UX can be a great tool for lead generation, upselling and cross-selling.

For instance, many businesses use chatbots to collect valuable marketing information from visitors before they get a chance to ask questions.

Gathering visitors’ names and email addresses helps marketers create strategies to increase the number of conversions.

everything you need to know about conversational ux

5 Conversational UX Best Practices

If you’re looking to implement or improve your conversational user experience, take a look at our list of five best practices:

Establish the Basics First

Although jumping into the practical parts of conversational UX, in order to do it right, you need to determine some of its basic components.

Trying to answer the following questions will help you set the foundations for your new chatbot UX project:

Where will you use the conversational interface? (website, social media etc.)
What will be its format? (a voice-based or text-based interface).
Does the project require advanced features such as AI?

Match Customer’s Intent

In order for your design to work, it needs to go hand in hand with your customers’ intent.

You will only be able to write successful scripts if you have a good understanding of all the potential conversational UX use cases.

Customer interactions are either related to sales or to support, and you should determine which of the two types dominates your business.

If most of your interactions are sales-based, create conversational UX scripts that lead to conversions.

On the other hand, if the interactions are mostly support-related, build a design that spins around informational use cases.

Gather Customer Context

Sometimes chatbots are unable to gather the context of the conversation, and the best way to prevent that is to build your chat flow with both optional and mandatory variables in mind.

Mandatory variables are the key pieces of information that are crucial for the communication to flow, while optional variables stand for additional details that are not essential for the conversation, but they can make it more efficient.

Chatbots will use this data to move smoothly through the conversation and provide helpful answers as fast as possible.

Mimic Natural Conversations

The best chatbot scripts are written with the customer’s perspective in mind, and formulated with structures used by humans.

There are several useful ideas that can help you mimic real human interaction:

Know the language your client base uses, avoid jargon and complicated terms.
Keep the answers short and concise.
Use ‘welcome back’ intents.
Include different agreement tokens such as ‘Perfect’, ‘I think so’, etc.
Create repair sequences to use after an error or a misunderstanding occurs.
Include phrases that show politeness and sociocultural elements.

Analyze and Review Regularly

Your conversational UX interface needs to keep up with the changes in your customers’ needs and desires.

To keep exceeding client expectations, you will need to revisit the setup regularly and modify it as needed.

Take some time each month, or stick to any other interval, to inspect the efficiency of conversational flows, as well as to analyze past conversations.

Look for patterns that will help you fine-tune the scripts and address common pitfalls.

Need Help Getting Started with Conversational UX?

If you think your business can benefit from conversational UX but you are not sure where to start, feel free to contact us at Demakis Technologies.

One of our seasoned professionals will be happy to assist you.

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