In today’s digital world, when customers talk to businesses using phones, chatbots, social media, email, and other ways, a lot of information is created. According to a study, a big majority of marketers, around 82%, believe that understanding what people say in phone calls or while conversing with a business, about their experiences can show important things that their organisations might be missing out on or not noticing, and these things could end up costing them.
This information can tell us important things about what customers like, what they need, and how satisfied they are. But looking at all this information manually takes a long time, costs a lot, and can make mistakes. That’s where conversation analytics come in to make things easier.
What is Conversation Analytics?
Conversation analytics involves using AI and other fields of technology to study how people talk and write, like in phone calls, chats, emails, and texts. For businesses, it helps understand human interactions and garner crucial data points for changing consumer behaviour.
As a tool for businesses, conversation analytics use advanced technology to listen, understand, and learn from conversations. This helps businesses know what customers want, improve communication, and make better decisions using data. It identifies patterns, trends, and feelings in conversations, aiding businesses in reaching their goals.
It uses sophisticated artificial intelligence (AI), machine learning, natural language processing, and algorithms to transcribe, analyze, and extract insights from conversations. It can identify patterns, trends, topics, intents, sentiments, and other relevant aspects of conversations that can help businesses achieve their goals.
Why Track Conversations?
Conversations are the most natural and effective way of communication between humans. But how we communicate has evolved. Automated chat support is now the most common and preferred way of communication between customers and businesses. Customers can converse with a business without actually having to talk to an agent. One of our customers, Fenix saw more than a 67% hike in by implementing conversational AI solutions to automate customer engagement and track customer behaviour. Therefore, tracking and analyzing conversations can provide many benefits for businesses, such as:
Enhanced Customer Understanding
Monitoring conversations allows businesses to develop a more comprehensive understanding of their customers. This includes insights into their challenges, expectations, feedback, opinions, and emotions. Businesses can further categorise customers based on their behaviour preferences and needs. Such segmentation assists in tailoring products, services, and marketing approaches to align with customer demands, ensuring personalized and targeted experiences.
Optimised Customer Service
Exceptional customer service plays a pivotal role in fostering customer loyalty and retention. By monitoring conversations, businesses can enhance the quality and efficiency of their customer service. Tracking key performance indicators (KPIs) like response time, resolution rate, customer satisfaction, and net promoter score enables businesses to gauge and elevate service standards.
Swift identification and resolution of customer issues, complaints, and queries contribute to faster and more accurate problem-solving. Additionally, businesses can provide training and coaching to agents, enhancing their skills and overall performance.
Data-Driven Decision Making
Conversations are a rich source of data that can help businesses make informed and strategic decisions. By tracking conversations, businesses can uncover hidden opportunities, challenges, and trends that can affect their business outcomes. They can also test and optimize their hypotheses, assumptions, and actions based on real-time and historical data. They can also leverage predictive analytics to anticipate customer behaviour and needs and take proactive measures to increase customer loyalty and revenue.
Improving Sales Performance
Interactions provides valuable data for businesses to make informed decisions. Monitoring conversations allows businesses to discover hidden opportunities, challenges, and trends impacting their outcomes. Testing and optimizing hypotheses, assumptions, and actions become possible with real-time and historical data. Additionally, businesses can utilise predictive analytics to foresee customer behaviour, enabling proactive measures to boost customer loyalty and revenue.
What to Track in Conversation Analytics
There are many aspects and dimensions of conversations that can be tracked and analyzed to gain insights and value. Some of the most common and important ones are:
Key Performance Indicators (KPIs)
Key Performance Indicators (KPIs) are measurable values that signify a business’s success in meeting its objectives, here improving products, services, and overall operations of the business. Tracking KPIs aids businesses in assessing and enhancing their overall performance and outcomes to plan for the future. In conversation analytics, some common KPIs include:
- Response Time: The duration taken by a business to reply to a customer inquiry or request.
- Resolution Time: The duration taken by a business to resolve a customer issue or query.
- Resolution Rate: The percentage of successfully resolved customer issues or queries.
- Customer Satisfaction: The level of satisfaction customers feel regarding the service or product received.
- Customer Retention: The percentage of customers who continue their association with the business over time. This can be tracked by checking the number of recurring customers.
- Bot Deflection Rate: The percentage of inquiries or issues successfully handled by automated bots, reducing the workload on human agents.
Sentiment analysis involves identifying the customer sentiment or tone conveyed in human speech or text. This process aids businesses in understanding customer satisfaction, loyalty, and advocacy, while also pinpointing potential issues, risks, and opportunities. Sentiment analysis can be conducted at various levels, including:
- Overall Sentiment: Assessing the general sentiment of the entire conversation, whether it’s positive, negative, or neutral.
- Aspect-Based Sentiment: Evaluating the sentiment associated with specific aspects or attributes of the conversation, such as product, service, price, or delivery.
- Emotion Detection: Discerning the customer’s emotion or mood, such as happy, sad, angry, or frustrated.
Customer Journey Mapping
Customer journey mapping is the visual and analytical process of understanding how customers interact with a business across various touchpoints. This method helps businesses pinpoint and enhance critical moments that influence customer behaviour and satisfaction. When tracking and analyzing conversations, customer journey mapping includes:
- Customer Profile: Understanding the customer’s demographic and psychographic details, like age, gender, location, interests, and needs.
- Customer Goals: Identifying the outcomes the customer aims to achieve, such as buying a product, seeking support, or acquiring information.
- Customer Touchpoints: Recognizing the points of interaction between the customer and the business, spanning website, phone, chat, email, or social media.
- Customer Feedback: Gathering opinions expressed by customers through ratings, reviews, comments, or surveys.
- Customer Pain Points: Identifying challenges or problems faced by customers during their journey, such as confusion, frustration, dissatisfaction, or disappointment.
- Customer Opportunities: Pinpointing areas where the business can improve the customer journey, offering opportunities for personalization, recommendations, or loyalty enhancements.
Keyword and Intent Analysis
Keyword and intent analysis involves recognizing and understanding the words and intentions expressed by customers in their conversations. This process assists businesses in delivering relevant and precise responses to customer inquiries and requests, while also enabling them to uncover and predict customer needs and expectations. When tracking and analyzing conversations, keyword and intent analysis includes:
- Keyword Extraction: Identifying the most important or relevant words or phrases from the conversation, such as product names, features, or benefits.
- Keyword Frequency: Determining how often keywords appear in the conversation, indicating their popularity or significance.
- Keyword Clustering: Grouping or categorizing keywords based on their similarity or relatedness, including synonyms, antonyms, or topics.
- Intent Recognition: Identifying the purpose or goal behind the customer’s query or request, such as buying, comparing, or cancelling
- Intent Classification: Categorizing the intent into predefined types, such as informational, transactional, or navigational.
- Intent Ranking: Prioritizing the importance or relevance of identified intents.
Agent performance evaluation involves assessing the quality and effectiveness of agents handling customer conversations. This process aids businesses in monitoring and enhancing the skills and overall performance of their agents. Furthermore, it provides a basis for rewarding and motivating agents. When tracking and analyzing conversations, agent performance evaluation includes:
- Agent Behavior: Examining the behaviour or actions of the agent during the conversation, such as greeting, listening, empathizing, or expressing gratitude.
- Agent Skills: Assessing the skills or competencies displayed by the agent during the conversation, such as knowledge, communication, problem-solving, or persuasion.
- Agent Feedback: Gathering feedback or opinions provided by customers or managers to the agent, including ratings, reviews, comments, or coaching.
- Agent Metrics: Utilising metrics or measures indicating the agent’s performance, such as average handle time, first call resolution, customer satisfaction, or net promoter score.
Conversation analytics is a dynamic tool empowering businesses to extract valuable insights from customer conversations. Through tracking and analyzing these conversations, businesses can elevate their understanding of customers, refine customer service, make informed decisions based on data, and enhance sales performance. This innovative tool extends its capabilities to monitoring various conversation dimensions like KPIs, sentiment, customer journey, keyword and intent, and agent performance. By harnessing the potential of conversation analytics, businesses unlock the power of meaningful interactions, paving the way for improved customer experiences and outcomes.