Unlock Powerful Marketing Customer Insights with AI Conversational Analytics

Unlock Marketing Custom Insights with Ai Conversational Analytics - Blog Post Cover

Extracting customer insights can be challenging.

Is it just about asking questions? Not really.

Customers aren’t always willing to fill out your questionnaires or participate in interviews.

Even when they do, gathering, categorizing, and analyzing the data takes time and resources. Do you have the capacity for that?

Customer insights are crucial, though. They drive business growth and product improvement by unlocking key insights about preferences, core pain points, customer journey touchpoints, competitors’ USPs, sentiments towards your brand, and much more.

So, how can you make the process easier?

Keep reading to uncover how modern tactics, technologies and tools like conversational analytics software can save you time and resources, providing the valuable customer insights you need efficiently.

Key Types of Customer Insights

Now, let’s talk about the different types of customer insights you can collect.

  1. Behavioral Insights: These focus on how customers interact with your products or services. They involve website clickstream data, app usage patterns, and purchase history analysis.
  2. Customer Feedback: It’s a fundamental law of physics that every action has an equal and opposite reaction. This principle applies to your relationship with your customers as well. Everything you do, a change in your policy, pricing, product features, anything, will have an impact. Measuring this impact with direct responses from customers through surveys, reviews, and feedback forms will provide valuable insights into customer satisfaction, frustrations, and suggestions for improvement.
  3. Sociodemographic Data: This includes basic information, like age, gender, location, income level, and occupation. They might seem a bit surface level, but they still help you understand your target audience and tailor your offerings accordingly.
  4. Customer Service Data: Interactions with your customer service team leave behind a treasure trove of insights. Analyzing call transcripts, chat logs, and support tickets can reveal common customer issues, areas where your product might be confusing, and how effectively your support team is addressing concerns.
  5. Sales Data: Show me your receipt and I will tell you who you are. Sales figures and purchase history provide insights into customer buying habits. You can identify popular products, track trends, and even use this data for predictive analytics to anticipate future customer needs.
  6. Market Research: Focus groups, competitor analysis, surveys, things most business owners and marketers are well accustomed to. They help you understand industry trends, identify new customer segments, and position your product or service within the larger market landscape.
  7. Social Media Insights: There is a whole world in the social media sphere. Pictures, conversations, comments, tweets (are they still called tweets?) can provide you with insights into what people are saying about your products, identify brand advocates, and understand emerging trends and topics of interest to your target audience.
  8. Website Data: Your website is your very own personal data collector. Analytics tools can track website traffic, user behavior on your webpages, and conversion rates. This data can reveal how customers find your website, what content resonates with them, and where they might be dropping off in the buying journey.
  9. Call Conversation Data: Listen to the call, and you’ll understand your customer. Call conversation data reveals insights into customer preferences, pain points, and satisfaction levels. By analyzing call recordings, you can identify recurring issues, measure sentiment, and enhance customer service strategies. This data also aids in training sales teams, refining scripts, and improving overall communication efficiency.

How to Gather Customer Insights

Now that you know what customer insights are, it’s time to talk about the most important part. How to get that juice information flowing into your business.

We will group the techniques into four categories: Active Listening, Surveys & Feedback Forms, Social Listening & Monitoring, Customer Behavior Analytics. 

Active Listening

  • Customer Interviews: Conduct in-depth interviews with a small group of customers to gain detailed insights into their experiences, needs, and motivations.
  • Focus Groups: Moderate group discussions to explore customer opinions and perceptions around specific topics or products.
  • Customer Support Interactions: Analyze calls, chats, and emails handled by your customer support team to identify common pain points and areas for improvement.

Surveys & Feedback Forms

  • Online Surveys: Distribute online surveys with multiple-choice, open-ended, and Likert scale questions to gather a wider range of feedback from a larger audience.
  • Website Feedback Forms: Embed feedback forms on your website to capture customer sentiment after they interact with specific pages or features.
  • Post-Transaction Surveys: Send surveys after a purchase or customer service interaction to gauge satisfaction and identify areas for improvement. Make sure to strategize these actions by creating the right incentives

Social Listening & Monitoring

  • Social Media Monitoring: Track brand mentions and conversations happening on social media platforms to understand customer sentiment and emerging trends.
  • Online Review Analysis: Analyze customer reviews on your website, third-party review sites, and social media to understand customer pain points and areas of praise.

Customer Behavior Analytics

  • Website Analytics Tools: Utilize website analytics tools like Google Analytics to track website traffic, user behavior, and conversion rates to understand how customers interact with your digital presence.
  • Customer Relationship Management (CRM) Systems: Leverage your CRM to analyze customer data, buying habits, and support interactions to identify trends and personalize future interactions.
  • A/B Testing: Run A/B tests to compare different versions of your website, marketing materials, or product features and see which ones resonate better with your customers.

The 5-step playbook for perfecting customer insight collection

Focus on Quality, Not Just Quantity: Don’t get bogged down by a massive amount of data. Prioritize high-quality insights that are actionable and relevant to your business goals.

Gather Insights from Multiple Sources: A well-rounded understanding comes from a variety of data points. Combine qualitative feedback (interviews, open ended surveys) with quantitative data (website analytics, sales figures) for a holistic view.

Listen with Intent: Actively listen to what your customers are saying, both explicitly and implicitly. Pay attention to not just the content of their feedback but also the emotions and frustrations they express.

Prioritize Actionable Insights: Don’t just collect data and let it sit. Analyze your findings and identify actionable insights that can be used to improve your product, marketing, or customer service.

Maintain Data Privacy: Always ensure you comply with data privacy regulations and be transparent with customers about how you collect and use their information.

Build a Customer-Centric Culture: Make customer insights a core part of your company culture. Integrate customer feedback into all aspects of your business, from product development to marketing campaigns.

Close the Loop: When you take action based on customer insights, let your customers know! This shows you value their feedback and helps build trust and loyalty.

Regularly Revisit Insights: Customer needs and preferences evolve over time. Regularly gather new insights to stay up-to-date with your customer base.

The secret sauce 🍯: Extracting AI Conversational Analytics from phone calls to excel Customer Insights Collection

AI conversational analytics have a wide range of implementations from customer service to lead generation, and marketing. But, let’s start at the beginning. What is conversational analytics?

Cover of Conversational Analytics Blog Post

Conversational analytics Definition

Conversational analytics is a technology that uses Artificial Intelligence, machine learning and natural language processing to analyze text and spoken conversations. It does that first by recording and transcribing the conversations and then applying sentimental analysis. It also takes into account other factors, such as keywords used, conversation duration, questions asked etc.

To simplify it, we could say that conversational analytics are like a trained psychologist at your side. They look into the deeper meaning of a conversation and extract insights that a normal person wouldn’t be able to. That’s because most people don’t have years of education and experience in the field of psychology and even if they did, they wouldn’t be able to work on a scale. Conversational analytics can analyze a great number of conversations in a minimum amount of time.

💡 Discover more on Harnessing Conversational Analytics in 2024, here.

Phone calls are one of the richest sources of insights.


Phone conversations offer a direct line to customer emotions and thought processes. The tone of voice, urgency of the call, and specific language used can reveal frustrations, areas of confusion with your product, and even new feature ideas.

In addition, you can obtain comprehensive insights from call attribution data, revealing the campaigns that generate the highest quality calls to offline touchpoints, ultimately leading to online revenue and positively impacting your ROI. Here are some strategies to transform your phone calls into valuable customer insights:

-> Keep an eye to your secret revenue sources

Today’s customer touchpoints, happen everywhere. This cross-device behavior can sometimes complicate data collection and analysis, potentially leading to suboptimal decisions. Call tracking technology bridges the gap between offline and online touchpoints by attributing what may be reported as offline (such as phone calls) to the corresponding source, campaign, ad group, landing page, or keyword that generated each call.

-> Enrich Marketing Customer Insights with Caller Profile Data

By leveraging caller profile data, you can gain deeper insights into who your customers are. This data includes demographics, marketing attribution data, call summaries, total times called and much more which can help you tailor your marketing strategies more effectively. Understanding your customers at a granular level allows you to provide personalized experiences, enhancing customer satisfaction and loyalty.

-> Map the Customer Journey with Lead Timelines

Tracking the entire customer journey from initial contact to conversion is crucial for understanding how different touchpoints influence purchasing decisions. Lead timelines provide a visual representation of this journey, highlighting key interactions and engagement points. This information helps you identify the most effective touchpoints and optimize your marketing efforts accordingly.

-> CRM Enrichment: Integrating call tracking data with your CRM system enriches your customer records with valuable information. This integration ensures that all interactions, both online and offline, are captured and linked to individual customer profiles. Enriched CRM data allows for more precise segmentation, targeted marketing campaigns, and improved customer relationship management.

-> Gain Customer Insights through Call Outcomes: Tracking the outcomes of calls, such as whether an issue was resolved or a sale was made, helps in assessing the effectiveness of customer service and sales teams. Analyzing call outcomes also highlights follow-up requirements, improving customer satisfaction and reducing churn.

-> Identify Keyword and Topic Trends: By identifying frequently mentioned keywords or topics during calls, businesses can reveal recurring issues or popular products. This helps in addressing common problems proactively and capitalizing on popular trends. Understanding what customers frequently inquire about or request can guide product development and service enhancements.

-> Predict Future Needs and Trends: Analyzing call data can help in predicting future customer needs and trends. For instance, a surge in calls about a particular feature might indicate a growing demand that the business can proactively address. Identifying patterns that lead to customer churn, such as frequent calls about unresolved issues, allows businesses to take preventive measures to retain customers.

-> Gain Competitive Insights: Comparing call tracking and conversational analytics data with industry benchmarks provides insights into how the business stands against competitors. Understanding what competitors are offering, as inferred from customer conversations, can help in refining market positioning and strategic planning.

No idea where to start? No problem! – Putting AI Conversational Analytics into Action

Simply subscribing for an AI conversational analytics tool isn’t enough. Extracting valuable consumer insights requires a well-defined approach. Here’s how to get started:

  1. Choose the right tool: Not every AI conversational analytics tool out there is good for your business. Consider your needs. Do you need a tool for analyzing phone calls, chat transcripts, or social media conversations? What level of customization is required? Research available options and choose a tool that integrates seamlessly with your existing infrastructure.
  2. Data collection and analysis: When you have chosen the right tool, you need to  establish clear data collection protocols. What kind of conversations do you want to analyze? How are you going to acquire customer consent? And how you are going to feed into the AI system for analysis.
  3. Clear and actionable insights: Ok, you got the tool, you got the processes and you got the data. Now, what? Well, you need to present them in a digestible format. Utilize data visualization tools like charts, graphs, and heatmaps to make insights clear and actionable. Focus on highlighting trends, sentiment analysis, and key customer pain points. This allows your team to easily understand the story the data tells and make informed decisions.
  4. Integrations: Refrain from creating data silos in your business. Integrate your AI conversational analytics tool with other platforms as well, like CRM. This holistic view provides a comprehensive understanding of your customers and allows you to connect the dots between their conversations and overall behavior. By combining these data sets, you can personalize marketing messages, improve customer service experiences, and ultimately drive business growth.

Unlocking Customer Insights with Nimbata Call Tracking

Nimbata is a Call Tracking Tool made for Marketers in order to leverage and incorporate conversational analytics into their marketing tactics and gather rich information about their leads.

Initially, call tracking focused primarily on attribution, tracing calls back to specific campaigns and keywords. However, the landscape has evolved significantly.

With the increasing importance of first-party data and advancements in AI, call tracking tools have become powerful sources of actionable insights that can enhance both sales and marketing

In the previous section, we outlined the core benefits of combining conversational analytics with call tracking to extract deeper customer insights.

The next step is understanding how to put this into practice.

Here are the Nimbata features that will help you gather more customer insights for your marketing efforts:

  1. Call Recording, Transcriptions & Call Summaries (very common across Call Tracking Tools)
    • Automatic Call Recording: This essential feature records all incoming and outgoing calls automatically. These recordings can be used for training purposes, quality assurance, and detailed analysis to understand customer interactions better.
    • Automated Transcription: Calls are transcribed into text automatically, making it easier to search and analyze conversations. This feature saves time and allows for more detailed analysis of customer interactions.
    • Detailed Summaries: Automatically generated summaries of each call, highlighting key points and action items. These summaries save time and ensure that important details are not missed during follow-ups.
    • Follow-Up Actions: Summaries can include suggested follow-up actions based on the conversation, helping sales and support teams to stay organized and responsive.
  2. Caller Data and Demographics (very common across Call Tracking Tools)
    • Caller Identification: This feature collects basic information about the caller, such as their name, location, and phone number. This data helps in creating a more personalized customer service experience and
    • Demographic Data: By gathering demographic information like age, gender, and geographic location, businesses can segment their customers more effectively and tailor their marketing strategies to specific groups.
    • Detailed Call Logs: This feature tracks the duration and outcome of each call, providing insights into how long typical calls last and whether they result in sales, support resolutions, or follow-up actions. This data can help in assessing the efficiency of your customer service and sales teams. In Nimbata you can find this information under Call Activity in which you can create new custom filtered views with the data fields you want.
  3. Call Routing (less common across Call Tracking Tools)
    • Dynamic Call Routing: Calls can be automatically routed to the most appropriate department or agent based on predefined criteria such as the caller’s geographic location, the nature of their inquiry, or the time of day. This ensures that customers are connected to the right person quickly, improving their overall experience.
  4. Missed Call Alerts (less common across Call Tracking Tools)
    • Real-Time Notifications: Whenever a call is missed, real-time alerts are sent to the relevant staff to ensure a prompt follow-up. This minimizes the chances of losing potential leads or leaving customer issues unresolved. With Nimbata you can receive these alerts via Slack or Email.
  5. Sentiment Analysis (soon to be launched)
    • Emotion Detection: This feature analyzes the emotional tone of conversations to gauge customer satisfaction. It can detect positive, negative, or neutral sentiments, helping you identify areas where customers are happy or frustrated.
  6. Keyword and Topic Detection (less common across Call Tracking Tools)
    • Keyword Tracking: By identifying frequently mentioned keywords, you can uncover common customer concerns and interests. This information is crucial for addressing recurring issues and refining your products or services.
    • Trend Analysis: Analyzing trends in conversation topics over time helps you stay ahead of market demands and adjust your strategies accordingly. For example, if more customers start asking about a particular feature, it might be time to highlight it in your marketing efforts.
  7. Call Scoring and Classification (less common across Call Tracking Tools)
    • Quality Scoring: Calls are scored based on predefined criteria, such as how well the agent followed the script or resolved the customer’s issue. This helps in assessing the quality of interactions and identifying areas for improvement.
    • Classification: Calls are categorized based on their nature, such as sales, support, or inquiries. This categorization helps in understanding the primary reasons customers are calling and addressing these needs more effectively.
  8. Lead Scoring and Qualification (less common across Call Tracking Tools)
    • Lead Tracking: Track and score leads based on their interactions, such as the number of calls made or the sentiment expressed during conversations. This helps in prioritizing follow-ups and improving sales efficiency by focusing on the most promising leads.

⭐️ New Feature Alert – Automation Builder

Our latest release introduces the Automation Builder, a groundbreaking functionality that revolutionizes the way you manage and optimize your customer interactions. This innovative tool allows users to create complex workflows that handle lead and call scoring, integrations, spam lists, and other custom fields all within a single, user-friendly interface.

With over 30 advanced filters, including keyword and phrase spotting, users can build precise automation processes to streamline their operations. This tool enhances efficiency, improves lead management, provides actionable data-driven insights, and offers customizable workflows tailored to specific business needs, ultimately driving growth and optimizing customer engagement.

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