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ROI: The Only Contact Center Acronym That Matters

Contact Centers who work with a technology partner like Grupo NGN get better results than centers that purchase software from faceless vendors

The original working title of this blog post was “Is AI just BS?” but we decided to expand the focus of the article beyond just focusing on how Artificial Intelligence term is misused to a discussion around cutting through all the noise in the Contact Center industry. Grupo NGN is not simply a vendor of software; we are a technology partner who works with our clients to ensure their success and Return on Investment on our products.

I spent years in the Army where acronyms are part of the culture, and I am glad I did! It prepared me for a career in the Contact Center industry where acronyms are used even more often. ACW, WFM, BPO, CRM, CSAT, DID, DNIS, IVR, NPS, WFO to just list a few. It’s a complete alphabet soup! But we believe there is one acronym more important than all the others – ROI.

I know you are thinking: “wait a minute, didn’t Grupo NGN just publish an article  about TX being most important?”  From an AI point of view, you must account for multidimensional quantities of data points to see  which data points are driving results.  Total Experience is the most important strategy for the overall  health of a company. But without a positive ROI there is no company in the first place.    

There are dozens of CCaaS providers for Contact Centers to choose from and hundreds if not thousands of additional technology options to manage and run a Contact Center. Ultimately Contact Centers need to consider how any software purchase is going to affect their Return on Investment. Specifically, they should ask “Will buying this software make my company more profitable?”. 

AI: What is it and What Does it do?

The following paragraph was in an article regarding technology in Contact Centers:

Many call center services are also implementing artificial intelligence to better serve their client companies’ customers. For call centers, AI has made a big impact with interactive voice response (IVR), the automated phone trees that many customer service departments use to improve efficiency. AI-enabled IVR tools can better interpret customer accents and intonation and assign incoming calls to the appropriate agents.

Let’s take a closer look at the reality of using “artificial intelligence” to improve an IVR.

First what exactly is Artificial Intelligence? A common definition of AI is “machines capable of performing tasks that typically require human intelligence”. That is a broad definition that could technically make a lot of things “AI”. Are calculators that do the human intelligence of math calculations AI? What about a remote control that allows you to change your TV channel more easily? Most people would not consider these technologies that have been around for decades to be AI. But it becomes less clear where that line exists as existing technologies are applied in new ways or to new industries.

If you directly ask someone to explain or define AI – what most people describe is a combination of machine learning, predictive analysis, or simple algorithms. Each of those can be considered subsets of AI but referring to them individually as AI gives them a sense of sophistication that may not be deserved. Because it is poorly defined and not widely understood, AI has become a buzz word to represent any kind of automated system.

Looking deeper at this specific example of AI enhancing an IVR, consider how “AI” would handle interpreting accents and intonation. This sounds very impressive but some of my first questions are: how does the system tell if someone is angry without any baseline? The evidence for the accuracy of polygraphs or “lie detectors” has been inconsistent and any polygraph exam requires a trained and certified human examiner who sets a baseline as part of the process. Another question is how does this “AI” system handle multiple languages? A recent MIT review found that a popular AI hiring software wasn’t even capable of recognizing candidates who didn’t speak English. This doesn’t even take into consideration intonation or regional accents let alone aggressive vs passive personality styles.

For arguments sake put all those questions aside and say that despite evidence to the contrary there is AI that does in fact accurately recognize the attitude of a caller. My final question is – so what? The action of the AI is to separate those callers to different queues based on that analysis. So as a contact center you need to consider what is the actual value of that AI driven action? And what is the potential additional cost of putting a system in place that is inconsistent and inaccurate in how it evaluates and queues your inbound customers?

IVRs have been assigning customers to different queues based on feedback for years and no one has thought to call it AI. The only thing this “AI” is doing is “assign[ing] incoming calls to the appropriate agents.” So, a customer calls in and say the AI recognizes this customer is angry, livid in fact and looking to make whatever agent gets on the phone a target for verbal abuse. Knowing this before the agent takes the call is helpful – and certainly if you have some agents that are specifically trained in de-escalation you would want to route the customer to that agent.
But what happens when your de-escalation agents (or singular – agent) are already on a call? Do you make this customer you already know is angry wait longer to get to one of those specially trained agents? Or do you end up queuing them up for the next available agent anyway? As you consider the real-world application of adding so called “AI” technology to your IVR I believe it is likely the costs will outweigh any actual value.

Using AI to drive ROI

At Grupo NGN we do not believe in using generic terms like AI to become part of the trend but to employ it to drive real results, measurable. AI can be a fantastic tool when used properly along with solid management and well-trained agents but it fails when it is expected to replace those employees.

For example, one of the uses of AI inside our NGNCloudComm software is to employ AI Prediction algorithms when it comes to outbound calling. We utilize a Fuzzy Logic Neuronal Network that learns from its environment. It constantly monitors the behavior of the phone lines, the state of the data network, the internet, the agent behavior with one goal in mind. To make the most accurate prediction and maintain the systems dialing parameters at peak efficiency to ensure maximum return. It does all of this without needing a person to take any manual effort, so that person can focus on other, more pressing tasks. Please note that to us AI is not a new trend that we must follow because everyone else is now claiming to use it. We are pioneers in this field since our software has had this AI predictive module since 1995! Almost 30 years ago!

One of the most “expensive” modes of operations is to trust your agents enforce your company’s business rules. The reason I call it expensive is that to obtain a magnitude of success, a lot of policing has to be implemented, either by automatic or people (supervisors, QA, Speech analytics, etc…) means. Having a system that combines AI with Business Rules that are automatically enforced without agent intervention introduces magnitudes of savings while improving agent/manager and customer satisfaction.

NGNInsights, our gamification and performance improvement platform, makes practical use of AI with automated benchmarks. Customers can manually set benchmarks for each “Insight” or KPI (Key Performance Indicator) for Agents and Managers to easily see if performance is above standard, meeting standard, approaching standard or below standard. With automated benchmarks, customers can have historical and real time data analyzed by AI to generate benchmark thresholds based on natural breaks. This allows customers options in driving ROI:

  • Removing Bias: using the AI benchmarks in place of manually set benchmarks removes human bias and allows the benchmarks to be set based on the actual performance. While this doesn’t work for every KPI a Contact Center wants to track (IE: manually determined attendance quotas or time allowed for lunch breaks) it is a great option for performance-based metrics like contact or sales ratios. By removing bias, Contact Centers maximize the ROI of their agent’s performance
  • Trend Comparison: NGNInsights users can apply multiple benchmarks for comparison. This allows a Contact Center to have manual benchmarks and then use AI benchmarks to compare the results. The AI benchmarks are then a tool for the Contact Center to use in making changes to their benchmarks to maximize the efficiency of their agents and drive ROI

Note: You can have a complimentary review of your agent’s performance by simply providing us a single CSV or excel file of historical performance data which we will turn into an NGNInsights tile and run our AI analysis on to benchmark the performance. Request a free analysis here.

CX: The Current Buzzword

Here are some of the home page slogans I found from some well-known CCaaS providers:

  • Making CX Work for Real Life
  • Make Experiences Flow
  • Create a Seamless Customer Journey Across Channels That is Fast and Frictionless

Think back to your last customer support or sales experience with a contact center agent. Did you have a “Journey”? Was your “Real Life” experience “Seamless” or “Fast and Frictionless”?

This chart shows the relative popularity of the search term “Customer Experience” from 2004 to the present. Note that the popularity of the term was generally flat from 2004 until 2011. There was a steady increase from 2011 until January of 2021 at which point, we see a spike in the popularity of searching “Customer Experience” over the last 18-20 months.

The problem with vapid slogans whose primary purpose is chasing after attention through SEO tricks is the realization of how empty the statement is the moment anyone slows down to think about the statement for more than 2 or 3 seconds. Customer Service or as the new trend states, Customer Experience, is only one factor that Contact Centers deal with every day. What about Agent Experience (AX) or Management Experience (MX)? No Customer is going to have a “flowing, seamless, fast and frictionless experience” if the Agent they are working with is not empowered by good software and quality Management.

Total Experience

Contact Centers need to consider a Total Experience (TX) when considering any software including what CCaaS to use. We contend that there is no good Customer Experience (CX) without having a Great Agent (AX) and Manager Experience (MX).

Working With a Technology Partner vs Buying from a Vendor

As you have seen throughout this article, Grupo NGN is not simply a vendor selling software. We are invested in the success of our customers and work with our customers to ensure they are maximizing the tools we provide in NGNCloudComm, NGNInsights, and NGNShadowCoach to increase their profitability and ROI. We have recently begun working with a review aggregation site, G2 and the customer response has been eye opening.

NGNCloudComm User Ratings

Ease of Use

Call & Contact Center: 8.8 Average

Quality of Support


Call & Contact Center: 8.6 Average

We have an above average score of 9.4 for the “Ease of Use” of our CCaaS and a perfect 10 for “Quality of Support”. Here are some highlights from the reviews of our current customers:

If you would like to work with a technology partner and experience the same or better customer service contact us today to learn more about our products and support.



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