Using conversation intelligence to build a more strategic contact center

This interview first appeared as part of the BAI Special Report: The strategic contact center of today and tomorrow. Find more perspectives in the report on optimizing CX technology and creating enterprise-wide strategies from this crucial banking hub.

Luke Richardson, vice president of sales with Observe.AI, is a proven enterprise technology sales leader with over 15 years of experience spanning cloud computing, server and storage infrastructure and network security. Luke’s notable track record includes helping startups and midsize organizations alike drive revenue growth from $10 million ARR to over $100 million ARR.

Throughout his career, Luke has focused on enhancing talent development, recruiting, leadership and management, as well as executive negotiations, channel sales, revenue and growth planning and establishing foundations for rapid growth.

What is conversation intelligence?

Conversation intelligence is a powerful, efficient tool that helps financial institutions unlock valuable insights from their customer interactions. Key information is often buried within conversations, and conversation intelligence uncovers hidden gems, giving institutions more control over their operations and lifting confidence in decision-making. It improves agent performance, boosts revenue growth and increases efficiency.

Conversation intelligence is not just a tool; it’s your strategic advantage. By analyzing customer conversations—through phone calls, chats or emails—financial institutions can decode what customers need and prefer. This analysis uncovers meaningful patterns and trends, giving institutions a competitive edge and positioning them as forward-thinking leaders in the industry. It’s not just about understanding your customers; it’s about outpacing your competition. With its proactive approach, conversation intelligence goes beyond knowing what actions customers take or how they feel. It delves deeper into understanding why they behave in specific ways, answering questions like: What are the main reasons customers contact us regarding financial products or services? Which interactions lead to successful resolutions or upselling opportunities? This proactive understanding helps financial institutions feel prepared and in control of their operations.

It’s not just about understanding customers but being at least one step ahead. While many financial institutions already use customer surveys and review customer conversations, typically, less than 2% are actually reviewed. Conversation intelligence takes this further by automatically reviewing 100%, enabling financial institutions to have complete visibility into what is actually happening in conversations. Then, it turns your conversation data into actionable insights, helping institutions make better decisions and drive meaningful improvements.

How is conversation intelligence currently being implemented in contact centers?

The use of conversation intelligence significantly impacts how contact centers operate, especially in financial institutions where interactions can be complex. This approach helps financial institutions streamline operations, support agents and improve customer experiences by turning call data into actionable insights.

Here are the top three use cases:

1) Supporting agents during calls: Financial agents often must address detailed customer questions and ensure compliance requirements are met. Conversation intelligence helps by providing real-time access to relevant information and guidelines. For instance, if a customer asks about a specific financial product, the system quickly directs the agent to the most accurate and current information. This real-time support ensures that agents can efficiently handle calls and comply with industry regulations.

2) Streamlining post-call work: After a call, conversation intelligence automatically summarizes the conversation and documents critical details. This automation reduces the time agents spend on paperwork and helps ensure essential information is recorded accurately. With less time spent on administrative tasks, agents can focus on providing excellent service.

3) Enhancing customer satisfaction: Conversation intelligence captures and analyzes data from customer interactions to provide insights into the customer experience. For example, it tracks whether a customer calls for the first time or repeatedly about the same issue. It also evaluates sentiment over time, such as if a customer’s frustration is increasing with each call. By analyzing these patterns, financial institutions can identify areas where service may fall short—such as long hold times or delays in resolving issues. This data allows leadership to make targeted improvements in training, compliance and agent performance to enhance overall customer satisfaction.

What product lines can conversation intelligence tools be applied to?

Financial institutions can leverage conversation intelligence across any product or business area, but it’s particularly impactful in those areas where employees are engaging directly with customers, whether from a sales or service perspective. That includes everything from credit card servicing to lending and brokerage to collections.

The true strength of conversation intelligence is that it’s not just beneficial for individual service or sales teams, but the entire organization. For contact center leaders, it offers actionable insights to enhance team performance, revenue growth, compliance and customer satisfaction. However, its impact extends well beyond the contact center. It also gives the executives leading those teams, and the functional business unit leaders beyond the contact center, actionable insights into customer conversations so that they can make strategic pivots for the business. By understanding customer interactions more deeply, leaders can identify trends, optimize product offerings and refine critical business strategies. This 360-degree view allows for informed decision-making that drives sustained business growth.

In our work, we talk about a powerful transformation—turning the contact center from a cost center to a revenue-generating center. Contact centers hold a wealth of knowledge about how customers interact with the business and its products, so it’s vital to pass that knowledge on to the rest of the business. By integrating these insights into broader business strategies, financial institutions can enhance their overall performance and responsiveness to customer needs, inspiring a new approach to customer service and business growth

What should financial institutions consider about data protection when evaluating conversation intelligence platforms?

Given the significant amount of personally identifiable information (PII) handled by financial institutions, it’s important for buyers who are considering conversation intelligence solutions to prioritize the security and policy controls of their customer data. First, determine whether customer data will be housed on a vendor-controlled platform, or if customer data will at any point be moved onto a third-party platform like OpenAI. On a third-party platform, the financial institution wouldn’t own the data and would have no control over it. So, you need to make sure that your data will be sitting on a proprietary stack inside controlled data centers that have all the necessary security and policy controls in place.

How is a transcript translated into a summary that’s relevant and useful for the business?

Translating a transcript into a helpful summary is crucial for maximizing the value of customer interactions. Transcription accuracy is the foundation of this process. Transcription accuracy is vital to gaining relevant insights into customer interactions. With advancements in AI, contact center tasks like transcription are now automated, ensuring high efficiency and accuracy and reassuring you about the system’s speed and reliability. That said, transcription accuracy begins with obtaining good inputs, so it’s important to ensure your agents have state-of-the-art headsets and mic equipment, as well as a controlled environment for the best audio quality.

Once you have accurate transcripts, the next step is to use a conversation intelligence platform that effectively processes and summarizes this data. It’s important to select a platform that focuses on all the key transcription features: transcription accuracy, sentiment analysis and speaker identification. The platform should also allow customization to recognize and prioritize industry-specific terms and phrases, ensuring the system can be tailored to your needs.

For example, extracting relevant data from a customer interaction involves customizing the types of information you want to collect. If, for instance, a compliance team wants to understand whether mini-Mirandas are being communicated to customers correctly by agents, they’ll want to make sure the parameters for the summary will include relevant terms for their part of the business.

Not all solutions can customize summaries, so it’s important to select one that offers this level of custom configuration to highlight these critical terms in summaries. This customization ensures that summaries are accurate, actionable and tailored to your specific business needs. By leveraging these insights, you can make data-driven decisions that enhance compliance, improve customer service and drive strategic growth, thereby maximizing the value of the information provided by the platform.

How does conversation intelligence complement the work of contact center agents?

Conversation intelligence complements agents’ work in a couple of ways. It significantly reduces an agent’s after-call work. Depending on the complexity of the customer interaction, the after-call note-taking process could take anywhere from 30 seconds to four minutes. Summarization reduces this time, allowing agents to return to calls more quickly. For a sales agent, that means potentially making more money. For a service agent, it might be achieving the required targets. And it’s not just about cutting the time in half; this also takes the stress of note taking for the call summary off the agent’s shoulders so they can be present in conversations with customers and play more of an advisor role. Conversation intelligence can also create custom summaries using natural language prompts, as well as extract specific information from an interaction, such as product names. However, it’s important to remember that using a generic LLM isn’t enough. You’ll need to customize your platform to generate insights relevant to your business.

What advice would you give financial institutions seeking a conversation intelligence platform for their contact center?

Conversation intelligence isn’t an off-the-shelf product, so you need to find a vendor that’s going to be a partner, specifically one that understands the specifics of the contact center and will work to understand the specifics of your business, your agent experience, your team, your day-to-day challenges and the needs of your contact center leadership. You’ll also need a partner that understands what outcomes you’re trying to achieve with a conversation intelligence platform.

Your vendor partner should be able to show proven success with financial institutions like yours and share best practices they’ve developed that can guide your implementation and adoption plan for ultimate success. They should also be able to create a roadmap that shows continual improvement and investments so that you and the vendor can grow and scale together. Given the investment you’re putting into implementing a conversation intelligence platform, the last thing you want is to outgrow it in a few years when adoption is going well with agents and leaders. Your vendor should also help you determine whether your proposed use case is viable—that is, will it achieve the most impact in the shortest amount of time for your organization. For instance, you might want to aim for goals like ensuring compliance and driving better client experiences. You need to approach using conversation intelligence with this mindset: What can it help us achieve? Companies want to leverage AI, but they’re not sure how to do it in a safe and responsible way that drives an impact for their business. You need a vendor that can demonstrate their expertise and show that they’ve successfully done this for financial institutions in the past.

How does conversation intelligence make agents’ lives easier while still protecting customer data?

Conversation intelligence helps improve the agent experience by increasing transparency and empowering agents. Quality assurance features within conversation intelligence software can identify the business-critical elements—e.g., compliance, customer satisfaction—that leaders are looking for in customer interactions. Providing this information in aggregate means customer privacy is maintained while leaders obtain the insights needed to improve agent performance. Conversation intelligence also provides a holistic portrait of an agent’s work. Instead of choosing customer interactions to review at random, team leads are given the ability to view an agent’s work overtime and determine where to focus coaching efforts. Conversation intelligence insights also help to empower agents by giving them a clear view of their performance on calls that they can reference during coaching conversations. It also allows agents access to examples of well-done calls, offering them another way to improve and grow in their careers.

What is the overall value of using conversation intelligence in contact centers?

Conversation intelligence collects and analyzes data and translates it into actionable insights for leaders at all levels of a company. Contact center leaders get insights into overall performance and areas ripe for improvement. Agents get real-time guidance, assistance summarizing call notes and greater transparency in their own performance. Operations leaders get a good look at contact center key performance indicators (KPIs), including the number of interactions agents are taking, the average hold time and overall customer satisfaction. Team leads get data they can take back to their teams for more effective coaching. Regardless of where you sit in the business, conversation intelligence provides the basis for data-driven decision-making.