80% of a company’s collected data sits unused and over 50% of executives think their company’s data isn’t viewed as a valuable asset. In today’s data-abundant world, this means a significant resource is sitting underutilized. Why not instead leverage this wealth of information to extract key insights about leads, customers, and competitors?
For some, the answer is that the mechanics simply aren’t feasible. Manually sifting through, sorting, and analyzing this data is time-consuming and costly. However, significant recent advances in Artificial Intelligence (AI) have made the intelligent automation of this task possible.
That’s why some AI-first companies are building Conversation Intelligence tools and products, or tools that intelligently automate some of the above tasks, by applying the same advanced research that is informing technology like ChatGPT, self-driving cars, and automated fraud detection. In fact, the Conversation Intelligence market is expected to double over the next ten years in response to growing demand for AI-powered conversational data analysis.
AI summarization, or AI models that accurately summarize text, audio, and video, are further increasing the utility and robustness of Conversation Intelligence products. If your product team is looking to add to an existing Conversation Intelligence tool, or to build a Conversation Intelligence product from the ground up, AI summarization could be a powerful building block to consider.
This article explores the basics of Conversation Intelligence and AI summarization before drilling into the mechanics behind incorporating AI summarization into a Conversation Intelligence tool, feature, or product.
What is Conversation Intelligence?
89% of marketers agree that AI-powered Conversation Intelligence tools will be key to staying competitive moving forward.
What is Conversation Intelligence? Conversation Intelligence, or Conversational Intelligence AI, refers to tools that embed state-of-the-art AI models to extract key actionable insights from conversational data at scale.
Sales and marketing teams use Conversation Intelligence tools to identify risks, highlight opportunities, refine agent or representative coaching strategies, flag key sections of conversations, analyze buying patterns, and more.
What is AI summarization?
AI summarization models intelligently summarize text, audio, and video files into accurate, usable snippets.
Depending on the model, AI summarization models can return summaries of different styles, like a single paragraph or bullet points. Some AI summarization models can also return timestamps for summarized audio and video files.
For example, AssemblyAI’s Conversational Summarization Model is built specifically for two-person conversations, such as a 1:1 meeting, interview, or phone call, and can return summaries as bullets, long-form bullets (bullets verbose), a single paragraph, or headline.
Take this conversation as an example:
Speaker A: Hey, Susan. Have you got a sec? I have some questions about my paycheck. Speaker B: You bet, Emily. Pull up a chair. Speaker A: Well, this is my first paycheck here in the States and there are a few things I don't understand. First of all, what is this FICA, and SUI Y tax, and why are there deductions both for Medicare and for my health insurance plan? Speaker B: OK, let's start from the top of your pay stub. This number here represents your gross pay. Then here we have a series of deductions. First off are the federal ones. FICA stands for Federal Insurance Contribution Act, or something like that. It's your federal income tax. And then there's Social Security and Medicare, which are both federal programs to help you out after you retire or if you were unable to work. Speaker A: All right, I see. So the Medicare isn't actually a health insurance I can use now. Speaker B: That's right. Below the federal deductions are the state deductions. There's the state income tax, and then this SUI/SDI tax you were asking about is paying into an unemployment and disability fund that our state has set up, but you can see it's a pretty small quantity that they take. Speaker A: Yeah, I don't mind giving them a dollar fifty for that. So there are two separate income taxes,one at a state level and one at a federal level? Speaker B: That's right. Not all states have an income tax. Some use higher property taxes or sales taxes instead. Speaker A: I see. All right, well I think everything else I can figure out on my own. The deductions for health insurance and my 401(K) are pretty self-explanatory. Thanks for your help, Susan. Speaker B: No problem! All those deductions do add up, and nobody's net pay is as high as they'd like. I can understand why you'd want some explanation. Speaker A: Yeah, I guess it's the same in the UK, I just never paid much attention. See you later!
Speaker A suggests Sarah buy a house far away from the city center and tells her about her sister in law.
See AI Summarization in action with AssemblyAI’s AI Playground
Speaker A tells Sarah that buying a house near their company can be expensive and recommends her to buy a house far away from the city center to save money. Sarah's sister in law just bought a house that way.
Benefits of AI Summarization for Conversation Intelligence
The impact of Conversation Intelligence is profound. One independent study found that investing in Conversation Intelligence tools can deliver over 365% ROI for companies.
For product teams looking to build or enhance their Conversation Intelligence tools, AI summarization can be a powerful addition to their suite.
Key benefits of adding AI summarization to Conversation Intelligence tools include:
- Speeding up call review and QA by automating slow manual review processes
- Monitoring calls for key mentions or insights
- Flagging areas of concern in the conversation
- Facilitating faster review of conversations by management
- Quickly summarizing meetings and interviews for record keeping
- Increasing representative and customer engagement by automating note taking
- Enabling efficient context sharing
- Identifying key trends
For example, leading call tracking and intelligence software company CallRail recently built its new Conversation Intelligence feature, Call Summaries, to help its customers generate more intelligent insights while saving them time and money in the process.
3 steps to add AI Summarization to a Conversation Intelligence tool
Product teams at call coaching, call centers, virtual meeting, and lead intelligence companies can enhance their Conversation Intelligence tools with AI summarization.
Here’s how to get started with your build:
1. Find an AI partner
Choosing the right AI partner to help add AI summarization to your Conversation Intelligence tool is a crucial first step in the process. Look for an AI partner that gives you easy access to state-of-the-art, production-ready summarization models, leveraging the latest AI breakthroughs, and available via a simple API. By partnering with an AI expert, you won’t have to worry about building a summarization model from scratch and can accelerate time to deployment.
In addition, you’ll want to prioritize a partner who can investigate your use case, offer guidance for your implementation, and provide technical on-demand support as you build out and deploy the new summarization component of your Conversation Intelligence feature. Some AI partners can even go further by helping product teams build out their monetization and go-to-market strategies.
Since you’ll be dealing with customer data, you’ll also want to ensure your AI partner prioritizes robust security measures like SOC Type 1 and 2 compliance and regular third-party audits.
2. Review considerations
In addition to finding the right AI vendor, product teams should also make sure the following considerations are discussed during the build process:
- Focusing on the user value: If you’ve already created or deployed your Conversation Intelligence tool, feature, or product, your team will still want to take time to clearly examine the user value of adding AI summarization. What does your tool or product currently lack without summarization? How will the AI summarization change the tool? How will your users best consume the summaries? What changes to the UI will you need to make? What sort of educational materials will you need to create to teach users how to unlock the most value from summaries? By finding answers to these questions before deployment, your team will be better positioned for a successful launch.
- Set measurable goals: To define a measurable goal for adding AI summarization, your team will want to consider the best possible outcome you hope to achieve by making this change. What’s the largest benefit to your customers? Will adding AI summarization have any additional downstream effects? Then, create a clear goal that defines this intended outcome. For example, one goal could be to increase the usage of your Conversation Intelligence tool by 10%. Or another goal could be to win 15% more deals.
- Identify your KPIs: Your product team should also identify and define the most appropriate Key Performance Indicators (KPIs) that you will need to measure the success of adding AI summarization to your Conversation Intelligence tool.
3. Deploy and iterate
Your team has found the best AI partner, reviewed the above considerations, and successfully added AI summarization to your Conversation Intelligence tool, feature, or product. To be successful in the long term, your team will also want to consider how you will manage user feedback, incorporate new UI changes or further iterations, and monitor performance. This way, you can ensure that your Conversation Intelligence tool is always cutting-edge and competitive into the future.