Research Proves The Importance of AI-based Customer Interaction Call Analytics

There is global recognition around the advancements in artificial intelligence and how powerful AI enabled tools can be for call centers. Zadarma recently sponsored some significant research for the UK and the US, delivered by ContactBabel. The comprehensive research paper aims to give a detailed and definitive view around the reality of implementing and using AI based technologies such as Speech Recognition and Analytics, as well as explore how best to leverage these AI enabled solutions.

You can read or download the in-depth UK-based research papers in full, through the button above.

If you are more interested in the US version, click here.

Or for a faster read, the following article reviews ContactBabel’s research paper and summarizes key extracts, learnings, and relevant findings. The research report reviews how AI enabled call analytics based tools such as speech recognition and call analytics are being more commonly used today, in call center environments. These tools are providing faster analysis of recorded calls to gather vital customer information to provide various business benefits.

AI Based Speech Analytics

Many call centers today are utilizing AI based solutions to manage phone sales more efficiently without the need to listen to call recordings or create detailed spreadsheets and reports. The paper states that these should be essential tools for the sales department and customer support centers of businesses. Speech analytics has proven to increase call and deal conversion rates. The research paper discusses that the initial adoption of speech analytics has been focused towards analyzing large numbers of recorded calls, often long after the actual event.

However, the paper discusses that AI based speech analytics provides you with the ability to analyze the entire call journey automatically and that this is proving hugely effective as a way to measure call quality and the general level of customer service. This provides a fair and accurate reflection of a call center agent’s performance. Furthermore, the paper goes on to say that while the adoption of real-time analytics has surged in recent years, post-call speech analytics is still proving vital for business intelligence, performance improvement, quality assurance, and compliance.

The research paper mentions that “34% of analytics users state that it is very useful identifying improvements to business processes. Optimizing processes and gaining actionable insight that can be applied to the customer journey will become one of the most important uses of analytics, as users’ sophistication increases and solutions’ capabilities are explored more fully.”

This chart below is an extract from the UK report. This outlines ratings of how useful post analytic call analytics is for call centers.

Business leaders looking to improve customer servicing standards are often seen to be using VoIP based AI analytics to support this strategic priority. As the paper references, speech analytics is helping call handlers better understand customer drivers and expectations through gathering customer insights from each phone call. Call performance indicators, such as the prophecy of calls, quality of calls, and how quickly call issues are resolved, as well as repeat rates of calls through identifying the reason behind customer’s dissatisfaction, are all essential data that can help inform improved customer servicing strategies. To summarize, speech analytics is proving to improve customer care as well as increase call and deal conversion rates.

Conversation AI and Speech Recognition

The research paper goes on to review the benefits of conversational AI tools, exploring how contact centers are utilizing AI based technologies such as speech recognition, machine learning, speech-to-text, deep learning, analytics, chatbots, and natural language understanding to provide outcomes similar or beyond what a human could analyze and recognize. As such, the research paper continues to discuss these solutions and the huge potential they have to improve customer call quality and overall customer experience.

Speech recognition is a feature that recognizes voice commands to delegate actions, instead of manually typing the command. Real-time speech-to-text is proving essential for industry sectors that need transcripts of conversations instantly. With speech recognition in place, any missed call will activate and send a voicemail message directly to you. The voicemail will be transcribed to text to your messenger. Zadarma’s AI enabled speech-to-text capability is useful for on-the-go, busy individuals and teams, as the application can be accessed anywhere, with voice messages being transcribed into a text. Real-time speech-to-text is essential for industry sectors that need transcripts of conversations instantly. As the paper mentions AI based technologies like speech recognition are proving to be faster and more accurate than humans.

The paper goes on to explore further advantageous of conversational AI tools, delivering the following:

• An understanding of the customer’s meaning and intent, rather than just accurately decoding the syntax of the request
• Use of multiple questions in a conversational format to improve understanding
• Using past outcomes to predict and deliver the likeliest most successful output
• The use of confidence levels rather than a binary right/wrong output
• The ability to improve future outcomes without constant human input or monitoring.

Research is showing that call center managers are leveraging AI based analytical tools, utilizing recordings and text transcriptions, to inform the visibility of their call analytics data for further internal business processing, analysis, and call handling improvements. Many managers are building employer training and development plans informed by collected speech analytics data to improve sales and customer service call handling performance.

Usefulness of AI enabled Call Analytics

The paper reviews how businesses are using analytics. Organizations were asked how useful call analytics solutions were for improving various aspects of the customer experience. The paper cites that ”data shows that in most analytics use cases, around 60% of respondents stated that it was “very useful” with 25-30% saying that it was “somewhat useful”. The data (from the UK report) proves an increase in the positive adoption of AI analytic tools with more users acknowledging how such tools can improve customer experience.

Why does your business need AI-based Speech & Call Analytics?

Summary of Key Findings

As mentioned the in-depth research paper can be downloaded in full, however, we have extracted a list of summary points around the importance of leveraging AI call analytical tools, to conclude this article.

1. Call Quality Control: Through introducing AI analytics into your call center, you instantly start to have more control over the quality of your call conversations. Speech analytics and speech recognition, for instance, can be used to monitor your call agents' performance. From there you look to optimize call quality if required. You can introduce a level called quality standards for your teams to adhere to. Call analytics will evaluate calls on various aspects like tone, clarity, and compliance with protocols. This helps in maintaining a consistent level of service and identifying areas that need improvement.
2. Analysis of Competitors' Mentions: This is an AI enabled analytical tool that detects when a competitor's name is mentioned during calls. This tool is proving to provide valuable insights into customer preferences and market trends, helping businesses strategize accordingly.
3. Increased Sales Effectiveness: Research is proving that through analyzing the content and outcomes of sales calls, it can identify and pinpoint strategies that need refinement, thereby improving the overall performance of a call center or sales team.
4. Control of Script Following: AI based call analytics tools can help ensure call scripts are followed and no obscure language is used. Managers want to ensure customer interactions are consistent and that call agents adhere to company guidelines.
5. Time-Saving: AI based VoIP tools such as Speech Analytics and Speech Recognition reduces the need for manual call monitoring and analysis. This saves significant time for managers and departments, allowing them to focus on more strategic tasks.
6. Ability to Easily Find Any Conversation: Call recordings, call analytics and speech recognition tools offer convenient ways to retrieve specific call information and records. The research paper explains that AI based call analytics tools are particularly useful for reviewing important discussions, handling disputes, or for training purposes.

In conclusion:

Research is reinforcing that AI enabled call analytics based technologies are fast moving. To successfully implement such tools, businesses should be sure to select relevant processes and training to support and endorse the adoption strategy. Zadarma offers an AI-based VoIP service and has been commended by call center managers for offering an all-in-one unified communication solution with built-in AI-based analytical tools. Ultimately there will always be a need for human decision making and action at the heart of any business, however, vital call analytical tools are advancing data visibility for managers. AI enabled call analytics tools are allowing managers to easily analyze the efficiency of calls, the quality of calls, and the repeat rates around returning customer calls, fundamentally improving sales performance and customer service levels.