Speech analytics platforms capture the pulse of customers, enabling enterprises to extract a wealth of information from every engagement and improve the quality of the customer service they provide. Despite gaining momentum, prevalent myths still remain around speech analytics.
This article will dispel some of the most common myths that prevent organisations of all sizes from successfully utilising speech analytics and unleashing their full potential.
Myth #1: People speak using perfect grammar.
When writing an email or crafting a letter, we tend to be meticulous. There is a cognitive mechanism that happens during this process as thoughts are summarised and organised. We plan, we write, then scan for errors before sending. However, the same is not true for speech.
Mark Twain once said, "I didn't have time to write you a short letter, so I wrote you a long one." But even analysing a long letter would be easier than analysing speech. Why?
Because people don't articulate their thoughts as perfectly as they usually do in writing - they 'think aloud'. In response to a plain "Yes or no" question, I recall one conversation where a customer said, "No, no no, I mean Yes"—now, getting a computer to fully grasp the reason for "no no no" before yes, will be near impossible. Speech analytics tools are impressive, but not infallible, bringing us to myth number two.
Myth #2: Speech analytics is a set-it-and-forget-it technology.
The fundamental goal of speech analytics is to unlock the treasure trove of insight and data housed in the many conversations with customers pouring through your contact centre each day. Without speech analytics, these valuable insights remain locked behind call recordings as none of us have the capacity to listen to all recorded calls & identify recurring patterns.
That doesn’t mean human analysis is redundant. Quite the opposite, in fact. It’s crucial to understand that the insights surfaced are useless without human action.
Speech analytics is hands-on. The more you use it and understand it, the better results and greater the return.
Myth #3: Speech Analytics is too expensive.
If you have been scared off by the steep price tag for speech analytics, it is time to look again. Speech analytics has never been more affordable!
Advancements in cloud-based solutions have eliminated hardware expenses, while out-of-the-box operations end the need for expensive professional services and implementation fees. The cost of speech to text transcription has dropped, while speed and accuracy have increased, meaning you get more bang for your buck.
Myth #4: It takes 6-12 months to get to ROI.
While speech analytics has been around for the past few decades, it hasn't garnered much of a reputation. We could blame this on many factors. For one, it largely relies on the accuracy of speech to text, meaning it isn't 100% accurate. Another prevalent myth about speech analytics is that it takes time to see results, with up to 6 to 12 months before you see any return on your investment.
Analytic software can be trained to target key phrases and emotions expressed by the customer, allowing a business to analyse their mood, interaction, and overall satisfaction in real-time.
Speech analytics will save you time and money from countless hours of manual call analysis, help you improve your overall customer interactions and relations, and have a near-direct impact on your ROI.
Myth #5: Speech Analytics is only for the contact centre and large companies.
Let's quickly dispel the myths of exclusivity. While it's true that speech analytics can boost the quality assurance and coaching efforts for any contact centre, this isn't exclusive to customer support. How can other industries benefit from speech analytics?
The travel and hospitality industry - an industry that for the most part has been phone and app-based - can use speech analytics to reduce overheads in booking services and improve customer experience according to tastes, dietary requirements and cultural preferences. The health industry may also begin to see benefits from speech analysis. While not possible just yet, using voice data to mine health-related information about the caller will be viable in the not too distant future to provide appropriate emergency responses to those in need.
Myth #6: Speech Analytics Software is Too Complicated to Use
It is quite natural to feel daunted by the challenge ahead when installing new and unfamiliar software. Legacy speech analytics platforms can be quite challenging to use, requiring you to master the skills of finding interesting insights. Yet, speech analytics software does not have to be that complicated.
The software is extremely powerful and often only needs an Internet browser to run, however there are different interfaces available. At Sentient Machines our goal is to make our UI as easy to use as possible by our clients, which means that they are only a few clicks away from gaining transformative insights. There is no need to have any prior knowledge of how the system works or what Artificial Intelligence is.
Myth #7: Speech analytics is the same as speech to text.
I have often heard people refer to speech analytics as simply transcription, and not fully understanding the difference between the two. Let’s break it down.
You can define speech analytics as a collection of programs and statistical algorithms that help to analyse live or pre-recorded phone calls and gather structured data from unstructured conversations. On the other hand, text analytics is a technology that helps extract meaningful and structured information from written text by equipping the machine to decode and understand a human-written natural language.
Speech analytics will use various voice parameters that reflect changes in the autonomic and somatic nervous system to detect different emotions, moods, and stress levels. For instance, the loudness of voice can be correlated with anger, while fast speech could suggest frustration. On the other hand, text analytics uses words and phrases with positive or negative connotes and disfluency words to gauge emotion.
Conclusion.
While speech analytics has been around for the best part of a decade, businesses are only now starting to understand how valuable speech analytics is in enhancing their strategic planning processes and improving their business strategy.
With this technology, you'll be able to see what's working and what's not for your company through various metrics – such as customer satisfaction rates or customer engagement time on your site.