Speech Analytics vs Voice Analytics

Businesses today have access to more consumer data than ever before, especially through their customer support and service centers. The essence lies in understanding the optimal way of extraction and utilization of that data. Speech analytics and voice analytics are two approaches to call analytics that can be used for the same function. Even though they may both analyze phone conversations between customer support representatives and customers in order to reveal customer insights, their mechanisms are quite distinct. Discerning these differences is crucial to determine which solution of call analytics is ideal. Moreover, both the methods are used by customer support and service centers to gather information about the market performance of products. However, speech analytics and voice analytics are very different tools. The operating principles of analyzing used are very diverse.

Call Analytics

Call Analytics refers to the collection, measurement, analysis, and reporting of data collected over phone calls. Retailers and brands can use the insights gained from call analysis to optimize call handling and marketing campaigns. Call analytics also allow for viewing and analysis of both the macro and micro phone traffic patterns and sort the collected data into informative call reports. There are two different methods of call analysis, i.e speech analysis, and voice analysis.

Speech Analytics

Speech analytics analyzes the spoken content of a phone conversation by analyzing what is spoken between support representatives and the customers, and the context of the conversation. It does so by using phonetic indexing or converting speech to text for the organization of the content. Speech analytics makes it feasible to search and locate the speech of a representative or a customer and their response to each other. The context of the conversation is divulged by the method of isolating specific words and phrases in proximity to one another.For example, if a customer calls a business to ask about the shipment of an order and when it is expected to arrive, then the execution of a search for the words “order” and “shipment” of the customer with close proximity to a search of the customer care representative using the word “shipment,” crucial information such as the reason for the customer’s call as well as whether the customer received a satisfactory response may be determined.Important factors such as keywords and syllables based on a frame of reference searches set up by the business play a vital role in speech analytics. Unveiling the most common phrases and words used by customers during such a conversation enables speech analytics to give businesses better insights into the latest trends. This, in turn, prepares the business to be able to create informed marketing strategies and make decisions that provide the customers with the best experience possible.

Voice Analytics

In contrast to speech analytics, which focuses on the words and phrases used in an interaction between the representatives and the customers, voice analytics targets the intonation of how it was spoken. Voice analytics work by analyzing the audio patterns for vocal elements such as the tone, pitch, tempo, rhythm, and syllable stress,  to gauge emotional quotient. This provides businesses with a deeper knowledge of the mood of a customer.For example, if a customer uses the word “amazing”, voice analytics can be used for the detection of cues, such as anger or sarcasm, which utterly changes the meaning of the word. It is crucial to understand the demeanor of a customer in order to be able to provide them with a satisfactory experience.

After the assimilation of raw vocal data, it is run against an emotional voice database, comparing factors generated by the voice analytics system with known factors associated with emotions such as anger, happiness, fear, and sadness, to correctly identify and classify the emotional state of the customer. In essence, voice analytics captures the emotional aspect of speech in a conversation.

Speech analytics is essential in cases where specific keywords and phrases show a strong indication of potential sales opportunities as well as situations such as cancellation of orders. Speech analytics determines the needs of a customer by the use of keyword detection whereas voice analytics, saves time and labor by guessing the meaning of words and phrases used in a conversation.

Furthermore, by analyzing a customer’s response and emotional state, voice analytics can help predict future behaviors. This is used in second call targeting by focusing on customers likely to make similar purchases. Thus, differentiating between what has been said with respect to how it was said can provide with different kinds of information, that may be used to improve the quality of operations in various ways.

 Voice enabled chatbots vs Messenger bots: What you need to know

There are two distinct ways in which a conversational interface works: text conversations and voice. Consumers interact with chatbots using both interfaces on a daily basis, with each having it’s own set of advantages and disadvantages. The big difference between a messenger chatbot and a voice chatbot or a voice assistant is the way people interact with them. 

The major differences

A text based messenger exists in one or more messaging platforms, including features of SMS and web chat messengers. This enables users to interact on a device screen via text or button presses. However, in the case of voice bots, users interact with the bot using their voice in natural language. The voice bot then responds leveraging pre-recorded messages, text-to-speech responses or a mixture of both. 

A voice enabled chatbot can be called upon in many devices such as mobile phones, computers, smart speakers (such Google Home or Alexa), wearables (Apple AirPods) or other IOT devices. These chatbots enable users to accomplish tasks efficiently hands-free. The advantage of using a voice chatbot is its ability to exist on multiple messaging platforms, that can be synchronised across different devices. Some messenger bots are also available via smart speakers - which function like platforms themselves - enabling them to perform dual actions as a voice chatbot as well as text-based bots. This can be seen with Fitness Tips via Google Home.

Key Similarities

Given their differences, the choice of interface depends largely on the purpose and context for a chatbot’s use. While both these platforms enable users to accomplish tasks or find the information they need via natural language, text-based bots can double as a voice enabled chatbot where a user can dictate using their phone’s text-to-speech feature or the bot may be available as a skill integrated into a voice chatbot. While both types of bots depend on NLP to make sense of user input and provide a response, each type has its own set of challenges unique to the interface.  Some of them include text messenger bots understanding shorthand and typos - common to mobile users and voice chatbots understanding different accents across the world. 

One major differentiator between a chatbot and a virtual assistant is its accessibility. A messenger chatbot could be a better choice for consumers who prefer to chat via their mobile phones to get information about different products. Unless voice chatbots exist on a consumer’s phone or computer, interacting with it requires getting a new smart speaker device. However, it is the perfect choice for consumers who prefer to multitask and do not want to use their hands while accomplish a task. For example: It works well for consumers who are looking for the different ingredients for a recipe and can add the items onto the shopping list via voice while doing other tasks. 

Conclusion

Text messaging is especially popular as a mode of communication among Millennials, making messenger chatbots a more natural fit for communication with consumers. The ubiquitous nature of mobile devices further help lower the barrier of entry to the consumers while using a messenger bot. While text messenger bots are popular, voice enabled chatbots are not far behind, gaining popularity in the past year.

Ultimately, the choice of the interface lies with the retailer and the products it offers. Another aspect retailers may consider is the point of contact for the bot and the consumer. Retailers must understand their target audience and tailor make an assistant that can best help them execute the tasks they need to do. 

In the next article, we will explore more about how retailers can choose between Voice enabled chatbots and Messenger bots to enhance their customer experience.

It seems like, these days, you see an Amazon Alexa or a  Google Home everywhere. It’s not uncommon to see a person shout across the room to their voice device trying to turn the television on.

Amazon and Google have sold over 27 million voice command devices in the United States alone, and Apple’s Siri is available to more than 500 million users across the world. 

With the increased adoption of voice assistants, consumers are depending on them to do simple tasks like telling time, setting alarms or even making calls, so that they can focus their attention on some other tasks. However, it’s not just those simple tasks anymore, voice assistants are being increasingly used for online shopping, with users giving voice commands to the assistant about what products to purchase. Consumers are able to multitask without having to manually search different e-commerce portals and selecting products through each of their product categories, thereby, saving a lot of time.

Retailers, recognizing this trend, are slowly incorporating voice to further enhance the user experience. Incorporating voice in the shopping experience not only ups the convenience level of a shopper but also saves time lost in typing and searching for products. 21% of all Alexa and Home users have stated that they are shopping via their device today. Leveraging AI, voice recognizes language patterns such as dialects, intonations, and accents enabling them to converse with the user in a natural, conversational manner. The potential of turning the shopping world upside down is very high and the most immediate impact will be in the following areas:

Better searchability

SEO becomes beneficial for any retailer as it drives maximum traffic for e-commerce. However, there is a lot of difference between typing in search terms and using voice. Technology needs to evolve to differentiate voice commands from typewritten keywords. This will help to institute searchability and compatibility towards voice commands. Understanding the context is important as Voice is conversational. For example, auto-fill options must be provided for sentences or questions to understand the user intent.

With consumers increasingly moving towards voice search, e-commerce businesses must align their website and product pages to account for voice.

Ease of providing product reviews

The increase in voice searches eliminates having to browse through different categories and multiple pages. Furthermore, this has raised the importance of online reviews for products and services. The feedback loop between the retailer and the customer becomes more efficient and seamless.

For instance, imagine a customer ordered a pair of Nike Running shoes but never got around to filling out the review. The voice assistant would then ask questions like: “How would you rate your Nike Running shoes from one to five stars? Did it fit as you expected?” By answering these quick questions, the shopping experience can become increasingly personalized, providing better recommendations for the customer.

Online reviews will become increasingly important with almost 85% of voice-based customers trusting the recommendations provided by their assistants. These recommendations, in turn, are based on the top-reviewed products of that query making providing reviews more important than ever for retailers.

Shipment Tracking made easy

In the future, voice commands may not only be restricted to ordering products or proving reviews for them. Users may even get quick updates about their orders and their shipping status. There is a need for these complex processes to become more intuitive especially when consumers expect prompt responses. The retailer can enhance the shopping experience by connecting shipping operations with the voice app enabling users to get quick updates about their shipping status.

Although voice search and shopping is the next big thing, there are a number of challenges that are left unaddressed. The technology, in its current state, is yet to be equipped to handle complicated queries such as comparing different products. Many users still don't believe that the assistants can pick a product without choice, based on their query.

The consumer behavior is changing and as the popularity of using voice search grows, retailers must make decisions and act fast to cope with the change.