As new regulations like GDPR and CCPA put a stranglehold on the use of third-party consumer data sources, making sure you have access to actionable first-party data is more important than ever. While you probably have access to data like customer purchase history, website and other digital journey information like paid search interactions, there are limits to how much insight marketers can gather from these sources.
Conversational analytics represents one of the last bastions of precise first-party insights into how your customers interact with your brand, how they think of your product or service, and perhaps most importantly, exactly how they talk about it.
What is Conversation Analytics?
Conversation analytics is the process of extracting usable data from human speech and conversation using natural language processing (NLP) to allow computers to “understand” speech and artificial intelligence (AI) to extract and organize data from it. I know, that’s a lot of alphabet soup to deal with, but what conversational AI boils down to is giving machines the ability to process speech and allowing people to gain insights from massive numbers of conversations at scale — both of which were daunting if not impossible tasks just a few years ago.
Conversational analytic tools are used to extract and process data from both spoken speech (e.g. phone calls and voice assistants) and typed speech (e.g. customer service chatbots). The applications are myriad, so we will stick with our area of expertise and show you how it’s used in call tracking software that allows marketers to understand call context, predict outcomes, and apply the data to optimize marketing campaigns and improve customer experience.
4 Common Uses of Conversation Analytics
Ever wished you could understand exactly what your customers are saying? Conversation analysis is like having a secret decoder ring for what your customers are saying, giving you valuable insights you can use to improve your business. Here are four key ways conversation analysis can be your secret weapon:
1. Customer Service Optimization
What if you were able to pinpoint exactly where your customer service conversations break down? Conversation analysis can highlight areas for improvement, like identifying common customer frustrations or recognizing phrases that signal churn. This lets you focus training on the most impactful areas and ensure your customer service team is equipped to handle any situation.
You might discover that a high percentage of calls mentioning a particular product feature end in frustration. This could indicate a need for improved product documentation or additional training for your sales agents or customer service reps on that specific feature.
2. Marketing and Sales Optimization
It would be pretty amazing to know exactly what kind of language resonates with your ideal customers, right? Conversation analytics can scan sales calls and marketing interactions to identify the phrases and topics that lead to conversions. This information would then allow your business to tailor your messaging for maximum impact.
If you’re finding that customers who use specific keywords during sales calls are more likely to convert, you can then use those keywords more frequently in your marketing materials and sales scripts to attract high-quality leads.
3. Voice of the Customer (VoC) Insights
Have you ever wondered what your customers really think about your brand? Conversation analytics goes beyond simple surveys to uncover the underlying sentiment in customer interactions. By analyzing the tone and emotions expressed in conversations, you can gain a deeper understanding of your customers' needs, wants, and frustrations.
You might discover that many customers feel frustrated with a long wait time during the onboarding process. This insight allows you to prioritize improvements to your onboarding flow, leading to happier and more engaged customers.
4. Customer Journey Mapping & Personalization
Providing a seamless and personalized experience for every customer is pivotal. Conversation analysis can help you map out the customer journey, identifying key touchpoints and pinpointing areas for improvement. This allows you to tailor your interactions based on individual customer needs and preferences.
Your conversation analytics tool might discover that a specific group of customers consistently gets stuck at a particular stage in the buying process. By focusing on conversations at that stage, you can identify roadblocks and develop targeted interventions to keep customers moving forward.
You can also use conversation analytics to capture data about your customers and personalize your marketing messaging to target them based on their needs and interests.
What Are the Benefits of Conversation Analytics?
Benefit 1: Meaningful Customer Insights
Conversational analytics provides deep insights into customer behavior, preferences, and sentiment by analyzing conversations across various channels. By analyzing the tone, language, and context of interactions, businesses can gain a comprehensive understanding of their customers' needs, pain points, and expectations. This knowledge enables companies to tailor their products, services, and marketing strategies to better meet customer demands, ultimately leading to improved customer satisfaction and loyalty. To quote the classic 80s cartoon, G.I. Joe, “Now you know. And knowing is half the battle!”
Benefit 2: Real Time Feedback & Resolutions
Conversational analytics allows businesses to monitor and analyze customer conversations in real time. This real-time feedback enables companies to swiftly identify emerging issues, customer complaints, or trends, allowing them to take proactive measures to address these concerns promptly. By capturing and analyzing conversations across multiple channels, such as chatbots, social media, or customer support calls, organizations can identify patterns, spot potential problems, and resolve issues before they escalate, thereby enhancing customer service and reducing churn.
Keep in mind that the information gathered won’t be all negative feedback either. There could be key words, phrases, or strategies being used by members of your team that weren’t considered but are creating positive experiences for your customers. They just need to be recognized and relayed to the rest of your team or department so they can reap the benefits as well.
Benefit 3: Personalized Customer Experience
With conversational analytics, businesses can deliver highly personalized experiences to their customers. By analyzing past conversations and customer profiles, companies can gain insights into individual preferences, behaviors, and past interactions. This information enables organizations to personalize their interactions, recommendations, and marketing efforts, resulting in more engaging and relevant customer experiences. Whether it's tailoring product recommendations, providing targeted offers, or providing personalized support, conversational analytics empowers businesses to create unique experiences that strengthen customer relationships.
Benefit 4: Improved Efficiency
Conversational analytics helps optimize business processes and improve operational efficiency. Automating the conversation analysis saves time and resources previously spent manually reviewing customer interactions. Automated sentiment analysis, topic categorization, and customer intent recognition enable businesses to extract meaningful insights quickly and accurately. This allows companies to focus on strategic decision-making, prioritize areas for improvement, and allocate resources more effectively. By streamlining operations and gaining actionable insights from conversational data, businesses can achieve greater productivity and maximize their operational efficiency.
Benefit 5: Enhanced Sales & Revenue Generation
We saved the best for last! Conversational analytics can significantly impact sales and revenue generation. By analyzing customer conversations, businesses can identify upsell or cross-sell opportunities, understand purchase patterns, and tailor their sales strategies accordingly. This data-driven approach allows companies to offer personalized recommendations, targeted promotions, and timely follow-ups, increasing the likelihood of conversion and driving revenue growth. Conversational analytics also helps identify potential sales bottlenecks, allowing businesses to streamline their sales processes and optimize conversion rates.
You can learn more about Invoca's conversation analytics capabilities here.
Benefit 6: Improved Agent Performance
Equipping your contact center agents with the right tools and feedback is crucial for delivering exceptional customer service. Invoca's conversation analytics platform takes agent performance evaluation to a whole new level.
Invoca automatically analyzes 100% of your contact center calls, removing the limitations of spot-checking calls and ensuring a comprehensive view of agent performance. By leveraging advanced AI and natural language processing, Invoca scores each call based on predefined criteria that align with your specific customer service goals. This automated scoring eliminates bias and subjectivity, providing managers with a data-driven foundation for coaching and development.
Think about the impact this can have. Agents receive clear, objective feedback on their strengths and areas for improvement. Managers can then tailor coaching sessions to address specific needs, helping agents refine their skills and deliver even better service. This two-pronged approach fosters a culture of continuous learning and growth within your contact center, ultimately leading to a more confident and empowered team.
To learn more about how Invoca's automated quality assurance solution can transform your agent performance evaluation, visit Invoca's product page on automated quality assurance.
Challenges in Implementing Conversation Analytics Tools
Conversation analytics is a powerful tool, but like any new technology, there can be a few hurdles to overcome when getting started. Here are a few common challenges businesses face, along with how Invoca's approach can help you navigate them smoothly:
Challenge 1: Data Privacy and Security
Data privacy and security are absolutely paramount concerns, especially when dealing with sensitive customer conversations. In today's digital landscape, consumers are rightfully cautious about where their information goes and how it's used. You need a conversation analytics solution that prioritizes both data privacy and security, giving you peace of mind and building trust with your customers.
Invoca understands this sensitivity. Our platform offers robust security features, including encryption at rest and in transit, to safeguard your valuable customer data. Additionally, Invoca gives you complete control over what data is analyzed, ensuring compliance with all relevant privacy regulations. Businesses across healthcare, government, and banking trust Invoca in large part because of our commitment to data security, privacy, and compliance.
We are SOC 2 Type 2 certified, ISO 27001, HIPAA, and GDPR compliant. In addition, we are PCI DSS, Privacy Shield, and TRUSTe certified. We will also sign BAAs to allow Invoca to record, transcribe, and analyze your calls in a secure and privacy-friendly way.
Visit our security and compliance page to learn more.
Challenge 2: Integration with Existing Systems
Integrating a new tool with your existing systems can sometimes feel like trying to herd cats. It can be a frustrating and time-consuming process, filled with compatibility issues and unexpected roadblocks. Imagine trying to force a square peg into a round hole — it just doesn't fit naturally. That's what it can feel like when a new tool doesn't integrate smoothly with your existing CRM, marketing automation platform, or other business-critical software.
Integrating a new tool to your tech stack should enhance the overall experience, not create a tangled mess of wires. You want a seamless flow of information between your different systems, not a situation where data gets siloed or lost in translation. Invoca's platform is designed with integration in mind. We offer a suite of APIs and easy integrations that allow you to easily connect Invoca with your CRM, marketing automation platform, and the other business-critical tools you use every day. This ensures your conversation data flows freely, and that your existing processes and workflows aren't impacted.
By addressing these common challenges head-on, Invoca makes it easy to leverage the power of conversation analytics without unnecessary headaches. We empower you to unlock the valuable insights hidden within your customer conversations, all while keeping your data secure and your systems running smoothly.
Check out Invoca's full integration library here.
Challenge 3: Interpreting Conversational Data
On the computer side, much of the difficulty in analyzing conversations lies in the many nuances of human speech. Unlike the formulaic equations and coded strings of commands computers usually use, human speech follows only a loose pattern and logic.
Even if we are only talking about analyzing the English language, there are hundreds of different accents, inflections, phrase patterns, varying word usage, slang, and colloquialisms that even other people have difficulty understanding.
New research shows that some elements of speech are hardwired in the human brain, but what really makes people different from machines is our ability to instantaneously process all of this variance of language. Creating a machine learning algorithm that can “learn” how to process human language is a whole different ball of wax.
Leading companies choose Invoca's solution because it leverages a combination of generative AI, large language models (LLMs), voice biometrics, and patented machine-learning technologies. This sophisticated mix allows our solution to interpret human speech identify trends with unparalleled accuracy.
Learn more about our next generation of AI tools in this post.
Why Conversational AI is the Future of First-Party Data
One of the reasons that conversational AI is seen as a great first-party data source is that today’s consumers expect more than the purely digital “point-click-buy” transactions and are demanding blended experiences that bring conversations into the mix. In fact, 70% of consumers feel frustrated or angry when they don’t have the choice of contacting a human representative.
Whether it’s a phone call with a human representative, chatting up chatbot, or getting help on the go with text messaging, consumers want to talk. This means that businesses need better ways to listen. In order to hear and understand what your customers are saying at any sort of scale, you need conversational AI to make sense of and take action on the data.
Companies that frequently have conversations with their customers on the phone are sitting on a goldmine of customer data. They may have thousands of hours of customer phone calls every year and have tens of thousands of call recordings banked — just imagine the kind of customer data that is in all of those calls. You’ll learn why they are calling, what makes a purchase happen, whether they are calling more often for service or sales, whether they are happy or mad — the possibilities are nearly endless. Then imagine manually wading through all those call recordings to gain insights on those calls. It’s just not possible. And as it turns out, it was pretty challenging to get computers to do it, too.
How Does Invoca’s AI-Powered Conversation Analytics Software Work?
Invoca’s conversational analytics tool is designed to help marketers get a new view into conversation data from high-intent consumers — such as purchases made or promotion inquiries. Marketers can quickly gain new insights and get attribution from phone calls and take action on them in real time. It is used to drive more revenue-generating calls, boost conversion rates, and optimize the buying experience. Signal AI conversational analytics is most frequently used to:
- Optimize Ad Spend: Automatically adjust keyword bidding strategies and suppress ads in systems like Google Ads and Search Ads 360 for callers who convert over the phone
- Seed Audiences: Create new audiences using offline conversion data to expand your reach of potential customers through native integrations with Facebook and Adobe Experience Cloud
- Personalize Content: Update content management tools like Adobe Target to personalize content for each subsequent consumer visit based on call conversations
Compared to other conversational analytics software, Signal AI offers marketers deeper insight into the unique conversations happening between a businesses’ buyers and agents — often uncovering conversation patterns and behaviors that marketers didn’t know existed — with consumer-level data that can be made actionable across marketing platforms.
Here’s how conversational AI works in Invoca’s call tracking platform:
Step 1: Call data flows into the Invoca platform during each conversation.
Step 2: The spoken data is transcribed into text so it can be analyzed by the algorithm.
Step 3: The predictive model analyzes the conversation and identifies key patterns, phrases, and actions, then identifies call outcomes such as ‘application submitted’ or ‘quote received’.
Step 4: Those outcomes and insights are pushed into your marketing stack so you can use this valuable conversation data to optimize marketing spend and personalize the customer’s next interaction — all in real time.
Easily Train a Custom AI Model with Invoca Signal AI Studio
Training an AI model may sound like a daunting task to take on, but not with Invoca! Our Signal AI Studio offers no-code UI that speeds you through the process of training a custom AI model. You simply tell it the insight you want to measure, and Signal AI Studio shows you transcribed examples from your calls that either fit or don’t fit that insight. It learns with every response, creating a new AI model in no time.
Custom AI models from Signal AI Studio can accurately detect virtually any insight or topic from conversations, including:
- Caller Intent: Detect if the caller is a sales lead, current customer, new or existing patient, or job seeker
- Caller Interest: Determine the specific product or service the caller is interested in, if they are looking for help with an online order, or need support with a product issue
- Conversation Outcome: Detect if the caller made a purchase, booked an appointment, received a quote, or canceled a service
- Call Events: Discover important events like if the caller asked to be called back or to speak to a supervisor
- Voice of the Customer (VoC) Insights: Detect if the caller asked about pricing or a specific product feature, discussed a competitor, or lodged a complaint
Learn more about how Signal AI Studio works here
Identify Phone Conversation Themes with Topic Explorer
It can be difficult to sift through your mountains of voice-of-the-customer data to identify trends. That's where Invoca Topic Explorer comes in. This tool allows you to visualize the themes and related topics being discussed across thousands of your calls at once to surface unexpected insights. You can specify the topics or categories you want Topic Explorer to visualize, view GPT-powered descriptions of topic summaries, and review transcribed examples from actual calls. Topic Explorer is a unique and powerful way to surface new and actionable insights on customers, call experiences, agent performance, and digital marketing campaigns you weren’t using Signal AI Studio to actively analyze.
These insights can give you a deeper understanding of what your customers are interested in and how to target them.
Conversation Analytics Examples: How Leading Companies Use the Technology
Ok, so now you know what conversational analytics is and how it works. But how are businesses using this technology in the real world? Below is a real-world example of how cutting-edge companies use Invoca’s conversational analytics software to drive better marketing results.
How Rogers uses Invoca conversational analytics to boost revenue from paid search campaigns by 18%
Rogers is Canada’s largest telecom company, serving over 10.8 million subscribers. Rogers’ mission is to provide the very best in wireless, residential, and media to Canadians and Canadian businesses.
The majority of Rogers’ marketing budget goes to Google paid search. However, before using Invoca, Rogers didn’t have visibility into the phone call conversions each campaign, ad, and keyword was driving. Since many of their customers buy over the phone, this was making it difficult for them to understand which campaigns were truly giving them the best ROI.
Rogers used Invoca’s AI to understand not just which customers converted over the phone, but the average value of the conversion for each customer type. With this data, they were able to understand the revenue that each paid search campaign, ad, and keyword was driving — both online and over the phone. They could then feed this revenue data into Google Ads to inform Smart Bidding. Smart Bidding weighs their bids in proportion to their returns, decreasing their cost per acquisition by 82% in a two-year period. They also achieved an 18% lift in net revenue from paid search.
Invoca also helped Rogers identify keywords that they previously thought were promising, but were driving the wrong types of calls. Before using Invoca, Rogers could see the Google data showing that an ad had driven a call — but they were left in the dark about the outcome. This led them to prioritize certain ads that were driving billing questions and customer support calls, rather than sales calls. With Invoca, Rogers was able to cut spend on ads that were driving non- sales-related calls and instead allocate that budget to higher-performing campaigns.
“The results with Invoca have been phenomenal, to say the least,” said Charlie Farrell, Senior Manager of Search Engine Marketing at Rogers. “The benefits are constantly compounding with such minimal lift for the returns. I’ve never had a product where I spend more time selling people on the results than doing the work to get it going.”
Additional Reading
Want to learn more about how Invoca’s AI can help you drive more revenue? Check out these resources:
