Use Cases
October 6, 2023

Speech AI for Sales Intelligence Platforms: How to Use AI

Learn how a Speech AI system can improve your sales intelligence platform.

Jesse Sumrak
Featured writer
Jesse Sumrak
Featured writer
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Table of contents

Sales intelligence platforms make it easier for sales organizations to automatically compile data and extract insights from that data. Specialized AI agents are already delivering productivity boosts of 50% or more in some sectors, driving significant efficiency gains in business operations.

Now, with advancements in AI technology, many businesses are harnessing the power of Speech AI to build a more valuable sales intelligence platform for their customers. In fact, a recent industry survey found that 76% of respondents have embedded conversation intelligence in more than half of their customer interactions. With Speech AI, you can unlock insights hidden within hundreds of hours of audio and conversational data in the form of sales calls, demos, team meetings, and customer service conversations.

Below, we'll walk you through the core technologies powering modern sales intelligence, the business benefits of integration, practical implementation strategies, and ways you can transform outdated workflows with Speech AI.

The growing demand for AI-powered sales intelligence

Speech AI transforms sales intelligence platforms by automatically transcribing, analyzing, and extracting insights from customer conversations. This technology enables sales teams to identify winning behaviors and coach representatives effectively. According to research from Brookings, significant AI investments can translate to roughly 2% in additional sales growth per year, helping teams improve deal outcomes.

Here's a look at how Speech AI is revolutionizing sales intelligence platforms:

Speech AI is not just about automating tasks but about enhancing the quality of interactions, providing deep insights, and ensuring end users' sales strategies are agile, informed, and effective.

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Core speech AI technologies powering sales platforms

Four core Speech AI technologies power modern sales intelligence platforms:

TechnologyFunctionBusiness ImpactSpeech-to-TextConverts audio to readable textEnables automated analysis and searchable recordsSpeaker DiarizationIdentifies who spoke whenTracks talk-to-listen ratios and conversation dynamicsSentiment AnalysisDetects emotional toneIdentifies prospect engagement and objection pointsLLM IntegrationProvides contextual understandingGenerates summaries and actionable insights

Asynchronous and real-time transcription

At the core of any Speech AI system is transcription—converting spoken words into text. Sales intelligence platforms leverage two primary approaches:

Asynchronous transcription processes recorded calls after they occur, enabling post-call analysis and coaching reviews. Real-time transcription converts speech to text during live conversations, enabling immediate coaching and compliance monitoring.

Transcription accuracy directly impacts business outcomes. When systems miss competitor mentions or pricing discussions, sales teams lose critical insights that could determine deal success.

Speaker diarization

Knowing who said what transforms a simple transcript into a powerful analysis tool. Speaker diarization technology identifies and labels different speakers throughout a conversation, enabling sales intelligence platforms to:

Sentiment analysis

Understanding the emotional tone of sales conversations provides crucial context that words alone can't capture. Sentiment analysis evaluates whether speakers express positive, negative, or neutral emotions throughout the call.

This technology helps sales teams identify when prospects become excited about features, frustrated with pricing, or confused about implementation. By tracking sentiment shifts throughout conversations, platforms can pinpoint exact moments where deals gain or lose momentum.

LLM integration for advanced understanding

Large Language Models (LLMs) add a layer of contextual understanding that goes beyond basic transcription and analysis. Through frameworks like LeMUR, sales intelligence platforms can:

Business benefits of integrating speech AI

When you integrate Speech AI into your sales intelligence platform, you're not just adding features—you're delivering measurable business outcomes. As a market survey shows, over 70% of companies reported a measurable increase in end-user satisfaction, directly impacting the customer's bottom line. Here's how these technologies translate into real value for sales organizations.

Identify winning sales tactics

By analyzing thousands of sales conversations, Speech AI helps platforms identify the specific behaviors, phrases, and approaches that correlate with successful outcomes. In fact, research on sales performance confirms that teams see boosted sales outcomes from prospect behavior insights and risk identification derived from conversation analysis. Your users can discover which talk tracks resonate with different buyer personas, which objection-handling techniques work best, and what questions top performers ask to advance deals.

This data-driven approach to sales excellence means teams no longer rely on intuition or anecdotal evidence. Instead, they have concrete insights about what actually moves deals forward in their specific market.

Real-time coaching for sales excellence

Sales managers can't listen to every call, but Speech AI can. Real-time transcription and analysis enable platforms to provide immediate coaching opportunities—flagging when reps miss key talking points, alerting managers to challenging customer situations, or highlighting exceptional performance that should be shared with the team.

This scalable coaching approach ensures consistent skill development across the entire sales organization. After implementing such tools, 69% of surveyed companies reported improved customer service, demonstrating that the benefits extend beyond reps who get direct manager attention.

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Customer sentiment insights

Speech AI tracks sentiment patterns to reveal when prospects are genuinely interested versus politely disengaged. These insights enable sales teams to adjust their approach before deals stall, responding to actual customer emotions rather than assumptions.

Performance enhancement at scale

Speech AI democratizes access to best practices by making top performer insights available to everyone. New reps can learn from analyzed recordings of successful calls, experienced reps can refine their approach based on data-driven feedback, and entire teams can standardize around proven methodologies.

The result is accelerated ramp time for new hires, consistent performance improvement across all experience levels, and a culture of continuous learning powered by actual conversation data.

How a speech AI system can improve your sales intelligence platform

Every interaction, every word spoken, and every sentiment expressed can be the difference between a successful deal and a missed opportunity for your end users. With a complete Speech AI system, you can build on top of AI models and boost your sales intelligence platform with new features and tools that enable your customers to digest and analyze voice data, streamline their operations, and move more quickly.

Here's how AssemblyAI's Speech AI system can improve your sales intelligence platform:

1. Analyze hours of audio data

Leverage our state-of-the-art speech recognition model to transcribe hours of audio data.

Then, use Speech Understanding models to quickly identify breaks in speech, patterns, common objections, and more from the transcription texts.

2. Use AI summarization for quick analysis

Time is of the essence in sales. AI-generated summary tools built on top of AI summarization models remove the need for a manual analysis of data and, instead, provide concise overviews of lengthy calls, giving sales reps upfront information they need to immediately follow up and take action.

With AI summaries, sales organizations can review key points and prepare for follow-up conversations.

3. Collect insights with sentiment analysis

Build tools that dive deep into the nuances of a discussion, gauging a caller's overall sentiment. This provides invaluable insights into a prospect's concerns, interests, and potential objections.

With Speech Understanding models like Sentiment Analysis, you can extract this information more quickly.

Regularly reviewing sentiment analysis reports helps your users better tailor their pitches. If a particular segment of the pitch consistently elicits negative sentiments, it lets the user know it's time to re-evaluate and adjust.

4. Transcribe in real time

With AssemblyAI, sales teams can get real-time transcriptions of their calls. This not only aids in maintaining accurate records but also allows for immediate analysis and strategy adjustments.

Users can have real-time transcriptions during sales meetings to highlight key points, ensuring no crucial detail is missed. This can be especially useful when discussing complex products or services.

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5. Recap action items from calls

Use LeMUR to automatically identify and list action items from a call to give your users' sales reps a clear roadmap for follow-ups and next steps.

After each call, your users can easily review the list of action items and integrate them into the CRM or task management system. This ensures timely follow-ups and keeps the sales process moving smoothly.

6. Request feedback and areas for improvement

Create a Custom Task that analyzes your customers' calls to find areas for improvement. It might let them know where things went wrong (or right) and give them actionable advice on refining their approach next time.

Behind this activity is a framework called LeMUR (Leveraging Large Language Models to Understand Recognized Speech), which applies Large Language Models to spoken data.

Real-world AI sales success stories

CompanyUse CaseResultJiminnyAI-powered coaching and conversation intelligence15% higher win rates for customersClariRevenue intelligence and forecastingImproved forecast accuracy and deal visibilityCallSourceCall tracking and analyticsEnhanced lead attribution and ROI measurement

Speech AI is already being implemented by today's leading companies like Jiminny who leveraged Speech AI to secure 15% higher win rates for their customers.

Jiminny is a platform designed to improve sales performance by offering a suite of tools that includes CRM automation, coaching, and conversation intelligence. It aims to help sales teams analyze customer interactions, streamline administrative tasks, and enhance coaching and training processes to drive better sales outcomes.

Jiminny uses AssemblyAI's models to power many of its key features:

With the transformative power of Speech AI, Jiminny helped their customers see better results.

Other sales intelligence platforms leveraging AssemblyAI's Speech AI include companies like Clari for revenue intelligence and CallSource for call tracking and analytics. These platforms demonstrate how Speech AI technology drives more efficiency, precision, and insights that traditional methods simply can't match.

Today's AI models offer a faster way to bring value to end users without compromising the quality of your platform.

Overcoming implementation challenges

While the benefits of Speech AI are clear, implementing these technologies into your sales intelligence platform requires careful consideration of several key challenges. Understanding and addressing these upfront ensures a smooth integration and successful deployment.

Ensuring data security and compliance

Sales conversations contain sensitive information—pricing discussions, competitive intelligence, and customer data that must be protected. When selecting a Speech AI provider, prioritize those with:

Your customers trust you with their most valuable asset—their customer relationships. Choose Speech AI infrastructure that maintains that trust through enterprise-grade security.

Maintaining accuracy across diverse conditions

Real-world sales calls happen in less-than-ideal conditions. Background noise from home offices, varying accents across global teams, industry-specific jargon, and poor phone connections all challenge transcription accuracy.

Look for Speech AI models trained on diverse, real-world data that maintain high accuracy even in challenging conditions. The difference between capturing "we need to discuss pricing" versus "we need to dismiss pricing" can determine whether a deal advances or stalls.

Managing integration complexity

Your engineering team should focus on building differentiating features, not wrestling with AI infrastructure. As one product leader noted, the goal is to "focus on delivering customer value early, so we very often decide to buy rather than build." The right Speech AI provider offers:

A smooth integration process means faster time-to-market and more resources available for innovation rather than implementation.

Scaling with growth

Your Speech AI infrastructure needs to grow with your platform. Whether you're processing hundreds or millions of hours of audio, the underlying technology should scale seamlessly without degrading performance or exploding costs.

Consider providers that offer transparent, usage-based pricing that aligns with your business model and infrastructure that automatically scales to handle peak loads without manual intervention.

Build the future of sales intelligence with speech AI

The sales intelligence landscape is evolving rapidly. Platforms that once competed on basic CRM features now differentiate through AI-powered insights that transform how sales teams operate. Speech AI sits at the center of this transformation, turning every customer conversation into a strategic asset.

The opportunity isn't just to transcribe calls—it's to build intelligence that understands context, identifies patterns, and delivers insights that help sales teams win more deals. Leading platforms are already using these capabilities to help their customers achieve measurable improvements in win rates and shorter sales cycles. Beyond sales metrics, research into AI's impact shows that firms investing in AI also see significant increases in innovation, such as a 24% rise in product patents, contributing to more predictable long-term revenue.

Your competitors are likely evaluating or already implementing Speech AI. The question isn't whether to integrate these capabilities, but how quickly you can deliver them to your customers. Every day without Speech AI is a day your users lack insights that could help them close more deals.

Building with AssemblyAI means accessing industry-leading accuracy, comprehensive audio intelligence features, and infrastructure that scales with your growth. Our API is designed for developers who need to move fast without sacrificing quality or security.

Ready to see what's possible? Try our API for free and start building the speech intelligence features your customers need to stay competitive.

Frequently asked questions about speech AI for sales intelligence platforms

What's the typical implementation timeline for adding speech AI to sales platforms?

Most platforms deploy basic transcription features within 4-8 weeks, with proof of concepts built in days using well-documented APIs.

How do we measure ROI from speech AI investments?

Track conversation-to-opportunity conversion rates, average deal size, sales cycle length, and rep ramp time to measure direct revenue impact.

What integration challenges should we expect with existing CRM systems?

Main challenges include data synchronization and handling high transcript volumes, though most modern CRMs offer APIs for integration.

How do we ensure transcription accuracy for industry-specific terminology?

Choose Speech AI providers that support features like Custom Spelling for specific formatting, or advanced models that can be prompted with key terms to improve recognition of industry-specific language.

What's the best way to handle data privacy and compliance concerns?

Select Speech AI providers with enterprise-grade security certifications and PII redaction features to protect sensitive conversation data.

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