The need for businesses to guarantee that their call centers and call center staff are working at peak efficiency has never been greater. Call centers can be challenging to set up and manage, and they are also cost centers. They require a lot of hardware, software, and a strong, comprehensive phone system.

Since many switched to using remote agents during the pandemic, contact center technology is changing quickly as well. Many are turning away from on-premises solutions in favor of cloud-based “contact center as a service” or CCaaS software. Although there were large upfront costs, this will ultimately save money.

The ROI that centers could produce is impressive. That is, if they are supported by call center development tactics that boost productivity and efficiency while simultaneously improving customer satisfaction.

Where do I begin? You may start by utilizing one of your call center’s most valuable resources: the volume of conversation data that is always expanding.

How Are Call Center Data Analyzed?

It goes without saying that manually listening to phone calls is a poor method for gathering data from call centers. It is expensive, subject to human error, and challenging to scale. This is where conversation intelligence products like call tracking systems come into play because they automatically record, transcript, and analyze every phone call to address this problem. You get complete visibility into every contact center conversation thanks to this.

To assist you in understanding when crucial activities take place on the call, conversation intelligence solutions also feature AI-powered analytics. This could be an agreement to meet, a quote offered, a mention of a certain product, a sale, or anything else that might indicate a high-value transaction has occurred. On the other hand, you can also instantly determine if it was a low-value call, such as someone calling the sales center for simple information like directions or arriving for customer care difficulties. This eliminates the need to pore over each call transcript in order to comprehend performance at scale.

Call center data analysis can provide deep insights into your customers.

Depending on the size and type of the business, a call center may employ one or more workers. For instance, a Fortune 100 corporation may employ between 25,000 and 40,000 customer support agents throughout various call centers. These representatives are expected to handle about 50 calls per day, with a four-minute average call time.

That much call time is a lot. These interactions also yield a ton of useful information on call center effectiveness, such as average call duration and pick-up times. Most operators of call centers gather and keep this information. However, most of the time when they examine that data, they are merely beginning to use it.

They may use their call data to compile demographic information, tally the amount of calls received, and track key performance indicators (KPIs) that are pertinent to their call center or a specific division within it. Some may even track quality control by analyzing call data and then using the results to train agents. But frequently, they stop there.

Your company is missing a huge chance to develop data-driven call center improvement methods that can increase call center performance if you aren’t delving deeper into conversation data. Additionally, a new set of tech stack tools based on developments in artificial intelligence (AI) are providing even more insight into call center operations, paving the path for increased productivity and possible cost savings. Among these are the Active Conversation Intelligence solutions driven by AI from call tracking systems.

Call Center Costs Can Be Slashed Quickly With the Help of Predictive Analytics

You can find previously undiscovered inefficiencies in your call center operations by using call tracking systems AI call center technology. For instance, you may learn right away when your call center needs the most staffing and when you can do without it by performing a straightforward, predictive study of call volume trends.

The same is true for the days of the week. For instance, do we require more or less personnel in the call center on Fridays when weekly employees are paid? public holidays (such as Christmas Day or July 4), as well as the number of employees that the call center actually needs. Call center managers can make the best staffing and payroll adjustments to generate cost savings with the use of this kind of predictive analysis of call data.

Efficiency can be increased in the call center, for example, by employing more smart staffing techniques. The amount of time agents spend handling calls is decreased by effectively routing calls to lower transfer rates while keeping agents on the phone with clients. According to an impartial research report.

Another is enhancing agent performance through focused coaching. Additionally, tracking systems Active Conversation Intelligence platform can be a useful tool for pinpointing precisely which team members’ skills need to be improved.

Automating QA using Conversation Intelligence

If your business is typical of most others, you monitor the success of your sales people through a manual QA process. This strategy suffers from a number of drawbacks, including the expense, time commitment, and risk of human mistake involved in manually listening to calls. Additionally, your QA team (or team of one) may only listen to a small portion of the calls made by your agents, which makes it difficult to determine how well they are performing generally. Some of your best agents may have been caught by them on their worst or best days.

Enter call tracking systems, a platform that leverages AI to automatically and impartially rate each call’s agent performance. With call tracking systems, you can quickly identify each agent’s advantages, disadvantages, and potential improvement areas.

Since no two sales organizations are alike, lets you create your own special standards for measuring sales agent success. For instance, you might want your sales representatives to introduce themselves and then announce an upcoming special before asking the caller to make an appointment. By using AI, the call scorecard can figure out which of these requirements are satisfied on each call and provide a score in accordance.

Coaching Agents using Conversation Intelligence

The traditional method of mentoring agents involved manually listening to hundreds of sales calls or practically standing over the agents’ shoulders and listening to what they were saying. Since many contact centers are now entirely remote, it is impossible to simply stand and listen, and it is not productive to spend days listening to call recordings.

You can automate a lot of the call listening and coaching opportunity identification process by utilizing a conversation intelligence software. Call tracking systems can identify any phrase or keywords you wish to look for that may indicate a significant discussion or time in a call by using AI-powered voice analytics.

With this program, you can immediately ascertain the causes of subpar customer service and quickly determine which personnel require additional training. You can also provide your agents the option of listening to their own calls, allowing them to analyze their interactions and determine for themselves whether or not they went well. Additionally, you may use in-platform comments to provide your agents with fast actionable feedback.

For instance, you might discover that a salesperson has been processing requests for offer matching from clients incorrectly because the salesperson isn’t aware that your business is flexible on deals up to a specific amount. As a result, they have refused to budge from the deal the business promoted, costing them sales. Once you are aware of this error, the agent’s supervisor can intervene and give the agent the necessary training. The agent will then be aware of exactly what to do to close the transaction the following time a customer requests an offer matching.

The call center can also uncover excellent practices conversation intelligence. All agents can benefit from the experience of coworkers who consistently achieve high call scores, successfully manage client objections, and aid in closing sales. You can identify what those agents are doing well and make sure the team is aware of it. When mentoring reps to develop their skills, you can highlight material from call transcripts and even share specific passages from call recordings. That kind of knowledge can also be used to train new team members more quickly and efficiently. Additionally, if you operate several stores or call centers, you may measure and monitor sales and lost opportunities across those locations, draw inspiration from the top performers, and reward agents, stores, and locations for their success.

Additionally, you can make sure that top-performing staff members in your call center receive the credit they merit by highlighting their contributions. That can assist you in lowering turnover costs and increasing retention of your finest employees.

Identifying and addressing the causes of ineffective call center procedures

As your company becomes more adept at using conversation intelligence tools to evaluate call center data, you’ll be able to go deeper into the “why” of any inefficiencies you find and perhaps even find answers to issues you weren’t even aware of. Let’s look at the example of CHG Healthcare, which initially used to give its digital marketing initiatives more precise attribution.

After achieving its main goal, the healthcare organization used to further analyze its call traffic and discovered that departments within the call center had wildly varying rates of picking up incoming calls. A other division handled 70% of its calls, while one answered calls in less than 20% of the time. Calls made to the less responding division rarely converted, but calls made to the more responsive division often did.

Analysis of call data revealed that the difference in pick-up rates at the two divisions was caused by the way incoming calls were routed: to a live agent as opposed to a voicemail mailbox. Once the problem was located, a simple repair could be implemented. Additionally, the division that had previously answered less calls had a 50% boost in connection rates, which in turn led to an increase in conversion rates.

More productive calls Mean more “good” calls.

By lowering the number of erroneous service calls, Active Conversation Intelligence platform can also aid in improving the efficiency of call center operations. The main objective of call center operations is frequently to allow employees to spend more time handling calls that can result in sales rather than poor customer service.

Too frequently, people will call customer support because they have a straightforward query that an online search couldn’t resolve. They might be seeking for specifics like office hours or locations, for instance, which should in an easily accessible FAQ section or knowledge base on the organization’s website.

By comparing the content of incoming calls to data on the corporate website that is accessible to the general public, they are was able to assist one call center manager in resolving this issue. 

In the end, this straightforward but crucial adjustment resulted in a 20% decrease in undesired incoming calls to the business’ call center, allowing agents to concentrate more on higher-value calls and be more effective.

Speech analytics can also assist companies make sure their call centers are directing calls to the appropriate locations by generating efficiencies in real time. This can lead to a greater first call resolution (FCR) rate in addition to enhancing the customer experience. Additionally, it gives call center representatives greater chances to turn customer assistance calls into sales.

They are assisted a significant financial institution in increasing sales-related activity after reviewing the bank’s inbound call routing. According to the analysis, customers calling the financial institution were frequently sent to the incorrect division or person and didn’t receive the help they need. The bank optimized its incoming call routing procedure after analyzing call data so that its consumers would encounter fewer phone transfers. That contributed to a two-thirds boost in the bank’s call center efficiency.

Other than that: As a result of its data-driven call center improvement efforts, the bank witnessed a 50% drop in cost per conversion and an increase in call center efficiency of 60%, according to ongoing call tracking and analysis of its incoming calls.

Providing Callers with a More Customized Experience

The conversation intelligence platform uses AI to do more than merely analyze data and provide suggestions for improvement. In order to improve customer satisfaction and increase the chance of conversions, it can work in real time, employing intelligent routing and contextual data to guide calls correctly.

For instance, call tracking can direct a caller to the proper department to solve that issue if they dial the retailer’s call center because they don’t want to submit specific information into an online form at checkout. The e-commerce retailer is then better positioned to close the deal by customizing the experience to suit the customer’s particular needs.

By providing the chosen call center agent with a quick, system-generated audio clip from the incoming call, they helps to provide that personalised experience. By giving the agent additional context about the nature of the call in that clip, they are better prepared to help the consumer before the conversation even starts.

Removing marketing and call center silos

All of the advantages and tactics mentioned above can raise agent productivity, boost call center quality, and assist increase efficiency and cut costs. But the connectivity can foster between the call center and the marketing division is one of the most important advantages of utilizing it there.

The call center and marketing typically operate in isolation from one another, but greater information sharing between these two departments can be profitable for the company overall. Using analyze incoming calls can yield a wealth of information and insights that marketing professionals can use to develop and improve their company’s marketing campaigns. The sophisticated algorithms used are capable of deciphering each call’s intent, results, and judgments. Additionally, each interaction can be linked to a customer’s online experience. Call centers can receive more high-value calls by closely collaborating with marketing and ensuring that advertising initiatives are generating sales calls rather than service calls.

The conversation intelligence platform, powered by AI, also enables the call center to add value to the company. The FCR rate can be increased and customer service agents can provide more individualized assistance by using insights, which call center managers may also use to help agents discover more time and opportunities to convert customer service calls into sales.

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Ruby is “A Programmer’s Best Friend”.

Ruby has features that are similar to those of Smalltalk, Perl, and Python. Perl, Python, and Smalltalk are scripting languages. Smalltalk is a true object-oriented language. Ruby, like Smalltalk, is a perfect object-oriented language. Using Ruby syntax is much easier than using Smalltalk syntax.

Features of Ruby

• Ruby is an open-source and is freely available on the Web, but it is subject to a license.
• Ruby is a general-purpose, interpreted programming language.
• Ruby is a true object-oriented programming language.
• Ruby is a server-side scripting language similar to Python and PERL.
• Ruby can be used to write Common Gateway Interface (CGI) scripts.
• Ruby can be embedded into Hypertext Markup Language (HTML).
• Ruby has a clean and easy syntax that allows a new developer to learn very quickly and easily.
• Ruby has similar syntax to that of many programming languages such as C++ and Perl.
• Ruby is very much scalable and big programs written in Ruby are easily maintainable.
• Ruby can be used for developing Internet and intranet applications.
• Ruby can be installed in Windows and POSIX environments.
• Ruby support many GUI tools such as Tcl/Tk, GTK, and OpenGL.
• Ruby can easily be connected to DB2, MySQL, Oracle, and Sybase.
• Ruby has a rich set of built-in functions, which can be used directly into Ruby scripts.

Why Learn Ruby Code? Advantages & Disadvantages

So, what is Ruby good for if you’re an aspiring developer? Here are some pros and cons of learning the Ruby coding language.

  Pros:

• Easy to learn with a small learning curve; programming with Ruby scripting language feels almost like coding in English.
• Super fast to create working apps and websites; it reduces the development time and helps you hit the market in a really short time.
• Good amount of jobs available. Currently there are over 23,000 jobs on Indeed that mention “software” and “Ruby.”
• Very lucrative career; the average Ruby developer salary in the US is $137,640/year.

  Cons:

• Ruby is not as popular/commonly used as other similar languages. For example, it’s only currently used by 6.1% of all the websites whose server-side programming language is known. Compare that with JavaScript which is used by 97.9% of websites. It is also the 16th most popular programming language used by professional developers.
• Because it’s less popular, there are also fewer support resources available.

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Python, one of the most popular programming languages in the world, has created everything from Netflix’s recommendation algorithm to the software that controls self-driving cars. Python is a general-purpose language, which means it’s designed to be used in a range of applications, including data science, software and web development, automation, and generally getting stuff done.

Let’s take a closer look at what Python is, what it can do, and how you can start learning it.

What is Python?

Python is a computer programming language often used to build websites and software, automate tasks, and conduct data analysis. Python is a general-purpose language, meaning it can be used to create a variety of different programs and isn’t specialized for any specific problems. This versatility, along with its beginner-friendliness, has made it one of the most-used programming languages today. A survey conducted by industry analyst firm RedMonk found that it was the second-most popular programming language among developers in 2021.

Did you know? The name Python comes from Monty Python. When Guido van Rossum was creating Python, he was also reading the scripts from BBC’s Monty Python’s Flying Circus. He thought the name Python was appropriately short and slightly mysterious.

What is Python used for?

Python is commonly used for developing websites and software, task automation, data analysis, and data visualization. Since it’s relatively easy to learn, Python has been adopted by many non-programmers such as accountants and scientists, for a variety of everyday tasks, like organizing finances.

“Writing programs is a very creative and rewarding activity,” says University of Michigan and Coursera instructor Charles R Severance in his book Python for Everybody. “You can write programs for many reasons, ranging from making your living to solving a difficult data analysis problem to having fun to helping someone else solve a problem.”

What can you do with python? Some things include:

• Data analysis and machine learning
• Web development
• Automation or scripting
• Software testing and prototyping
• Everyday tasks

Data analysis and machine learning

Python has become a staple in data science, allowing data analysts and other professionals to use the language to conduct complex statistical calculations, create data visualizations, build machine learning algorithms, manipulate and analyze data, and complete other data-related tasks.

Python can build a wide range of different data visualizations, like line and bar graphs, pie charts, histograms, and 3D plots. Python also has a number of libraries that enable coders to write programs for data analysis and machine learning more quickly and efficiently, like TensorFlow and Keras.

Web development

Python is often used to develop the back end of a website or application—the parts that a user doesn’t see. Python’s role in web development can include sending data to and from servers, processing data and communicating with databases, URL routing, and ensuring security. Python offers several frameworks for web development. Commonly used ones include Django and Flask.

Some web development jobs that use Python includeback end engineers, full stack engineers, Python developers, software engineers, and DevOps engineers.

Automation or scripting

If you find yourself performing a task repeatedly, you could work more efficiently by automating it with Python. Writing code used to build these automated processes is called scripting. In the coding world, automation can be used to check for errors across multiple files, convert files, execute simple math, and remove duplicates in data.

Python can even be used by relative beginners to automate simple tasks on the computer—such as renaming files, finding and downloading online content or sending emails or texts at desired intervals.

Software testing and prototyping

In software development, Python can aid in tasks like build control, bug tracking, and testing. With Python, software developers can automate testing for new products or features. Some Python tools used for software testing include Green and Requestium.

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JavaScript: A Quick Definition

JavaScript is a scripting language used to create and control dynamic website content, i.e. anything that moves, refreshes, or otherwise changes on your screen without requiring you to manually reload a web page. Features like:

• animated graphics
• photo slideshows
• autocomplete text suggestions
• interactive forms

An even better way of understanding what JavaScript does is to think about certain web features you use every day and likely take for granted—like when your Facebook timeline automatically updates on your screen or Google suggests search terms based on a few letters you’ve started typing. In both cases, that’s JavaScript in action.

The results of JavaScript may seem simple, but there’s a reason why we teach an entire segment on JavaScript in both our Front End Web Developer and Break into Tech Blueprints. Underneath all those great animations and autocompletes—there’s some pretty fascinating stuff happening. This guide will break down exactly how JavaScript works and why and how to use it, plus the best ways to learn JavaScript if you’re realizing you need it in your skillset.

1. What Is JavaScript? A Detailed Explanation

If you’re hoping to break into a career in tech, your question might sound more like: “What is JavaScript and do I need it?”

If you’re interested in web development—the answer is a resounding yes. So with that out of the way, let’s go a bit deeper into how JavaScript works.

THE POWER OF 3: HTML, CSS, AND JAVASCRIPT

When most people learn to code, they start with good old HTML and CSS. From there, they move on to JavaScript. Which makes sense! The three elements together form the backbone of web development.

For those not familiar:

• HTML is the structure of your page—the headers, the body text, any images you want to include
• CSS controls how that page looks (it’s what you’ll use to customize fonts, background colors, etc.)
• JavaScript is the magic third element. Once you’ve created your structure (HTML) and your aesthetic vibe (CSS), JavaScript makes your site or project dynamic.

JAVASCRIPT IS USED TO AUTOMATE AND ANIMATE

I mentioned above that JavaScript is a “scripting language.” Scripting languages are coding languages used to automate processes that users would otherwise need to execute on their own, step-by-step. Short of scripting, any changes on web pages you visit would require either manually reloading the page, or navigating a series of static menus to get to the content you’re after

A scripting language like JavaScript (JS, for those in the know) does the heavy lifting by telling computer programs like websites or web applications to “do something.” In the case of JavaScript, this means telling those dynamic features described earlier to do whatever it is they do—like telling images to animate themselves, photos to cycle through a slideshow, or autocomplete suggestions to respond to prompts. It’s the “script” in JavaScript that makes these things happen seemingly on their own.

Meanwhile, because JavaScript is such an integral part of web functionality, all major web browsers come with built-in engines that can render JavaScript. This means JS commands can be typed directly into an HTML document, and web browsers will be able to understand them. In other words, using JavaScript doesn’t require downloading any additional programs or compilers.

2. What is JavaScript Used For?

We covered this a bit in the intro, but here’s a quick list of the main things JavaScript is used for.

• Adding interactivity to websites—yup, if you want a website to be more than a static page of text, you’ll need to do some JavaScripting
• Developing mobile applications—JavaScript isn’t just for websites…it’s used to create those apps you have on your phone and tablet as well
• Creating web browser based games—Ever played a game directly from your web browser? JavaScript probably helped make that happen
• Back end web development—yeah, JavaScript is MOSTLY used on the front end of things, but it’s a versatile enough scripting language to be used on back end infrastructure, too.

3. How Does JavaScript Work?

JavaScript is either embedded into a web page or else it’s included in a .js file. JavaScript is also a “client-side” language (rather than a “server-side” language), which is a fancy way of saying that it gets downloaded to site visitors’ computers, then processed.

HOW DO YOU ADD JAVASCRIPT TO A WEBSITE?

Actually adding JavaScript code to a web page is a pretty simple process (and a familiar one if you’ve done any coding with HTML and CSS). JavaScript can be added directly to a page’s code using <script> tags and giving them the type attribute text/javascript. Honestly, JavaScript looks very similar to adding CSS to a site. Here’s a side-by-side comparison:

CSS:

<style> 
CSS goes here
</style>

JavaScript:

<script type="text/javascript">
JavaScript code goes here
</script>

Voila! JavaScript code can also be added to a page as a separate header file with the extension .js (generally done if it’s code that you want to include across a number of pages at once). The script is then downloaded and processed in each individual’s web browser, turning it into the dynamic objects and effects they see on their screen.

One word of warning, though: since JavaScript is processed by individual browsers, it’s possible a user might have JavaScript disabled on their end. Sites that use JavaScript need to have a back up plan in place to avoid breaking when this happens.

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There is no right answer, of course. Choosing a first language will depend on what kind of projects you want to work on, who you want to work for, or how easy you want it to be. Hopefully, this guide will help give you a better idea of which one you should pursue.

Python

Python is always recommended if you’re looking for an easy and even fun programming language to learn first. Rather than having to jump into strict syntax rules, Python reads like English and is simple to understand for someone who’s new to programming. This allows you to obtain a basic knowledge of coding practices without having to obsess over smaller details that are often important in other languages.

Python also is ideal for web development, graphic user interfaces (GUIs), and software development. In fact, it was used to build Instagram, YouTube, and Spotify, so it’s clearly in demand among employers in addition to having a faster onboarding.

Though it has it’s advantages, Python is often thought of as a slow language that requires more testing and is not as practical for developing mobile apps as other languages.

C#

While C is one of the more difficult languages to learn, it’s still an excellent first language pick up because almost all programming languages are implemented in it. This means that once you learn C, it’ll be simple to learn more languages like C++ and C#.

Because C is more “machine-level”, learning it is great for teaching you how a computer functions. Software Developer Joel Spolsky compares it to understanding basic anatomy before becoming a medical doctor, making it the best way to code efficiently.

In this way, C is an exceptional choice to become a master coder and a talented developer from the get-go if you’re willing to take on the challenge.

Java

Java is an object-oriented and feature-heavy programming language that’s in high demand. It’s been built under the premise of “Write once, run anywhere,” meaning that it can be written on any device and work cross-platform.

This makes it one of the most desired (yes, we mean high-paid) language skills. So, if you’re looking to learn a language that’s going to get you a great career, this might be the one, especially since top employers for Java programmers including Ebay, Amazon, and IBM.

Additionally, Java is often used for Android and iOS app development, as it’s the basis of the Android operating system, which makes it one of the best choices if you want to build mobile apps.

While it may not be as easy to pick up as Python, Java is a high-level language, and so it’s still relatively beginner-friendly. However, it has a slow startup and will take beginners much longer to deploy their first project.

JavaScript

JavaScript is another incredibly popular language. Many websites that you use every day rely on JavaScript including Twitter, Gmail, Spotify, Facebook, and Instagram according to General Assembly.

Additionally, it’s a must-have when adding interactivity to websites because it communicates with HTML and CSS. This makes it essential for front-end development and consumer-facing websites while becoming increasingly important in back-end development and growing in demand all the time. Because of its popularity, JavaScript is also the leading the charge in test automation frameworks, being the backbone of frameworks like Protractor and Nightwatch.JS.

There’s nothing to install with JavaScript since it’s already built into browsers, so it’s the easiest language to get started with in terms of set-up. The con here is that this means it’s interpreted differently across browsers (you’ll need to do some extra cross-browser testing) and may have deficiencies in responsive design compared to server-side scripts.

Again, while it’s not the most difficult to learn, it certainly isn’t as easy as Python. If Javascript does seem difficult at first, try out this Javascript tutorial that’s so easy a cat could do it.

Ruby

Ruby is similar to Python in that it’s one of the easiest languages for people with no prior programming experience to read. You don’t need to know a ton of commands or programming vocabulary to learn it, and it has a multitude of libraries and tools that come in handy.

A big reason people like Ruby is because of the awesome full-stack framework, Ruby on Rails, which is becoming increasingly popular among startups and enterprise solutions. Airbnb, Groupon, Hulu, and Soundcloud are just a few of the websites that were built with Ruby on Rails, and Ruby has quite the active developer community today.

The reason it’s so popular for small businesses, however, is often one of the many criticisms against it. Ruby can have the challenge of scalability across a large system and may have a hard time with performance on larger websites. Additionally, while Ruby is certainly easy to learn, you’ll find most of the opportunities come from learning Ruby on Rails, which may slow down your learning curve if you were just expecting to take the easy way out to create a website.

So, What’s the Best Programming Language to Learn?

• If you’re looking for something easy: Python
• If you want a solid foundation to make you a master developer: C
• If you’re looking for a job or want to make mobile apps: Java
• If you want to try front-end development: Javascript
• If you’re programming for your startup’s website: Ruby

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