Sales organizations handle large volumes of customer conversations, both inbound and outbound, through various communication channels. According to studies, about 76% of customers contact businesses by phone, while 21% and 13% use emails and chats, respectively.
The number of outbound conversations in a sales organization is equally high. Statistics indicate that about 30% of agents make over 50 dials/day as part of sales efforts. The total number of business emails per day in 2022 is about 333.2 billion and will reach 376 billion by 2025.
Such customer conversations say a lot about their preferences, market trends, your brand reputation, and more. The question is this – how do you make the most of them? That is where conversation analysis comes into the picture.
This post gives you a quick rundown of what conversation analysis is, its benefits, and how organizations can analyze customer conversations for actionable insights.
What is the goal of conversation analysis?
In the strictest definition of the term, conversation analysis (CA) is a method for analyzing conversations produced in everyday interactions. Though first developed to interpret social interactions, it is now widely used in business contexts.
In business, CA refers to the analysis of customer conversations taking place through various communication channels, including:
- Social media comments, posts, and mentions
- Third-party reviews
Why should you do conversation analysis?
Conversation analysis helps organizations in more ways than one. It allows them to:
- Gather data
The primary objective of CA is to extract both structured and unstructured data. The data is stored in the CRM and used for various sales and marketing activities.
- Understand customer pain points
Analyzing conversations is one of the best ways to understand the concerns and frustrations of your customers and take remedial measures before issues escalate.
- Optimize product/service development
Customer conversations act as a doorway to understanding market trends. It enables you to keep up with the trends and develop and offer relevant products or services.
- Understand customer behavior
Organizations can gain insights into customer behavior through CA and do selling and upselling the right way at the right time. Moreover, it allows you to offer personalized experiences based on their preferences.
- Improve the performance of sales and support teams
Customer conversation analysis helps you improve the quality of your services. Your sales and marketing teams can run more targeted campaigns, while your support agents can resolve issues on time or proactively reach out to customers.
- Enhance the customer journey
When you respond to customer pain points and improve the quality of services using the data extracted from conversations, it helps increase customer satisfaction, enhance your brand reputation and loyalty, and reduce customer churn.
- Improve decision making
You can make better business decisions by gaining insights into what customers want or how they perceive your brands. In the long run, it leads to increased sales and revenue.
How is conversation analysis done?
There was a time when businesses analyzed customer conversations manually. Today, you can leverage the power of technology to analyze customer conversations. Many providers offer AI-powered conversation intelligence software tools that collect and analyze data from multiple sources.
Such tools typically comprise a suite of technologies to decipher raw conversational data and find patterns using Natural Language Processing (NLP) techniques, AI algorithms, and machine learning. In addition to textual analysis, they help analyze data in the speech format by converting it to text.
Conversation analysis software usually offers speech-to-text transcription, omnichannel presence, sentiment analysis, data collection, data cleaning, machine-based translation, data visualization, reports and analytics, and other features. It also offers easy integrations with your CRM, business phone system, and other sales tools for data syncing.
What are the elements of conversation analysis?
Customer conversation analysis is a complex process comprising multiple components. Though these steps and elements may vary based on the CA software you use, the process usually has the following:
- Data collection
It involves collecting customer conversations from multiple channels, such as emails, phone calls, chats, social media, etc. You also have tools to convert speech data into text format.
- Text cleaning
It involves cleaning the unstructured and cluttered text and converting the collected data into a format that can be easily analyzed using AI algorithms.
- Data categorization
The tool categorizes the collected and cleaned data by assigning meanings and intents to the components.
- Data analysis
It is the most crucial element where a tool detects meaningful patterns, trends, and sentiments in customer communications.
- Visualization and actioning
The final element is the visualization of the results by turning them into charts and reports on the dashboard. The objective here is to make present the insights derived from conversational data actionable and usable.
Is conversation analysis qualitative or quantitative?
Conversation analysis is a predominantly qualitative method. It analyzes unstructured and qualitative conversations, such as phone call transcripts, emails, reviews, social media comments, chats, etc., collected through multiple channels and in various formats. In other words, it is a knowledge structuring tool for interpreting, detecting patterns and meanings, and gaining relevant insights from large volumes of qualitative data.
What is the difference between conversation analysis and discourse analysis?
Discourse analysis is a large category where you analyze written or spoken words in any format, including a lecture, written texts, etc. It is a qualitative and interpretive method to investigate and understand the meaning of spoken or written words taking the content and social context into account.
Like discourse analysis, conversation analysis is a qualitative method. However, its focus is on conversations between people rather than any form of written/spoken words. In other words, you can call CA a subset of discourse analysis.
Invest in the right communication tools
As we have already seen, a conversation analysis tool collects customer conversations across multiple channels. For it to give optimal results, you must integrate it with all essential communication and sales tools.
For instance, you must invest in a CRM that integrates with your CA tool or call center software. Likewise, it is crucial to have a unified communication platform or a business phone system with calling and call-management capabilities.
If you are looking for a VoIP telephony system that offers seamless integrations with CRMs and conversation intelligence tools, Ringover is a good choice. The cloud-based platform lets you have all customer communications in one place, making it easy to analyze them further. Learn more about Ringover here.