We all know those hidden corners in your rearview mirror just out of sight can often be the most dangerous when driving.
Similarly, if left unchecked, blind spots in your customer service organization can drive customers away and lead to low NPS scores and high churn rates.
Uncovering and addressing these CX blind spots is crucial; it allows you to navigate your business with a clearer view, making sure your customers have a smooth experience across every stage of the buying journey. By doing so, you prevent small issues from turning into major problems, keeping your customer relationships on a steady and positive track.
When you understand and address these hidden issues, you can more easily report back internally to department heads, draw clear action plans to address problems that are placing retention at risk, and ultimately help you create better customer service strategies that curtail churn and even help you grow topline. Below, we’ll share three ways that generative AI combined with conversation intelligence, or Generative Conversation Intelligence (genCI), can help you gather actionable insights more quickly with the help of LLMs.
Analyze every customer interaction, but not manually
If you’re manually reviewing and randomly sampling calls, odds are your team is spending hours trying to find reasons behind call surges or a spike in cancellations. It’s tough to get a pulse check on the state of the business this way.
The good news is that with the rapid evolution of AI, it’s much more cost-effective and simple to get full insight into the conversations happening between your customers and your agents or chatbots. In fact, with technologies such as Generative Conversation Intelligence (genCI), businesses can quickly access 100% of interactions to get an immediate pulse check on key areas of interest—particularly those where they most urgently need to take action.
GenCI uses multiple large language models, or LLMs, to analyze millions of customer data points at once and extract robust, AI-generated insights on critical business risks and opportunities. GenCI surfaces topics, themes and keywords by itself at a level of detail that is unmatched by most other technologies on the market.
After raw data has been analyzed through speech-to-text models, the data is routed through a pipeline of numerous LLMs, each designed to tackle a specific action or business question. Some common analysis points include:
- Customer intent, or the reason behind why a customer has expressed a frustration, concern, or desire
- Customer sentiment, which uncovers instances of negative and positive emotions expressed by the customer
- Agent sentiment, which uncovers instances of negative and positive emotions expressed by the agent
- Specific details about supply chain, operations, fulfillment, product quality, and more
Once the data has been passed through this second layer of analysis, generative insights surface key trends and themes that have been detected from the data. Generative insights refer to the learnings that have been autonomously detected across millions of data points without any manual tagging or categorization.
These generative insights are summarized by category— providing users with helpful overviews of intent, sentiment, and resolution scores—and organized into high-level themes and trends. With these topic summarizations, business leaders can quickly uncover the reasons behind call surges, cancellations, returns, and more.
The result? Root causes of pressing business issues can be identified faster, even without pre-set keywords or tags. In the next section, we’ll go into greater detail on what this looks like.
Nix the band-aid: get to the root cause
When problems arise out of the blue, it can be easy to slap a band-aid on in an effort to resolve things quickly. Maybe it’s issuing a refund or offering a discount to prevent customer churn. And sometimes, without the right analysis, you might miss a problem until it’s already caused negative downstream impacts on your business.
The only way to get to the bottom is asking “why” until you’ve hit the ground floor. But how do you know when you’ve reached that point? Here’s how genCI helps.
With GenCI, you can drill into specific themes and what your customers are actually saying in conversations. Then, GenCI tells you what percentage of calls pertain to each customer issue and shows you which specific products are referenced. With this invaluable data about how often specific themes are discussed in customer conversations, you can address problems before they escalate and uncover underlying issues. Finally, you can drill into specific conversations to gather full context. With AI-generated transcripts, analysis, and the ability to search for specific terms, you can look into one-off cases or paint a more detailed picture of how your customers feel.
Below, you can see an example of how GenCI can surface insights from conversations where cancellations are detected and allow you to drill into sub-themes, such as unauthorized payments, cancellation process issues, or order errors, all without having these set up tags or keyword monitoring.
By streamlining the root cause analysis process, you can accelerate decision-making, swiftly prioritize areas for improvement, allocate resources effectively, and implement targeted strategies to address identified issues and in turn yield faster ROI.
Surface what you don’t know with generative insights
It’s important to understand that even though generative capabilities have been focused on things like generating images, improving live agent assistance, and even fully automating chat responses, the gen AI use case for insights is powerful.
In fact, according to a recent Forrester report, using genAI for the analysis of customer conversation data is “one of the most straightforward applications that offers clear, attributable ROI.”
With more timely access to customer feedback, your team and business can respond faster and with greater confidence that you’re addressing real customer needs. You’ll benefit from more opportunities to improve outcomes for your customers, team, and organization.
With very little configuration, genCI will automatically surface detailed information around specific themes, trends, or negative outcomes it analyzes. With in-depth information about the number of conversations and issues arising, you get a detailed picture of an issue without having to comb through conversation transcripts or search for keywords. Information is at your fingertips the moment it is automatically analyzed, removing delays, searches, and blind spots.
For example, genCI might raise the theme of product efficacy and usage concerns for a supplement and vitamin company. It can provide the number of conversations such issues were raised in, as well as sub-themes discussed, such as compatibility with other medications or concerns about side effects. GenCI automatically surfaces themes it notices and allows you to get ahead of questions, issues, and concerns without having to listen to a single conversation yourself.
The answers to your pressing CX problems are likely hiding in plain sight, but most CX leaders lack the resources or technology to find them. With genCI, you can get answers to pressing questions faster than ever before, improving the customer experience.
Join us at Execs In The Know’s upcoming Customer Response Summit and swing by Echo AI’s blooth to learn more about how Generative Conversation Intelligence can help you drive better CX.
About Echo AI:
Echo AI is a Generative Conversation Intelligence platform that ensures every customer conversation, across all channels, is used to rapidly find key perishable insights and link them to promotions or retention campaigns while automatically scoring agent performance.
Written By Alex Kvamme, CEO & Co-Founder, Echo AI
