Speech is powerful. The right combination of spoken words at the right time can inform, inspire, convince, or deceive people. In business, actively listening to sales calls holds the truth to hidden opportunities — like understanding what your customers actually feel.
According to McKinsey & Company, speech analytics can help businesses save 20-30% in operational costs, a 10%+ improvement in customer satisfaction, and increased sales.
In this post, we will cover how you can use speech analytics to improve your sales outcomes.
What is speech analytics?
For example, MeetRecord’s sentiment analytics capabilities can analyze sales conversations and flag keywords or phrases that express doubt, lack of trust, or frustration. Your sales team can use this data to improve your sales approach or meaningfully address your customers’ concerns.
Speech analytics software often use natural language processing (NLP), emotion detection, and keyword spotting as its core components to provide context-rich customer insights. While analyzing speech benefits everyone across the board, it’s especially valuable for sales, call centers, and customer service teams who face customers on a daily basis.
Understanding speech analytics
If we break down the process of speech analytics, there are 4 main stages: transcription, keyword analysis, sentiment analysis, and actionable insights.
- Transcription is the process of turning audio or video conversations into texts.
- Keyword analysis means analyzing recorded conversations to identify specific keywords and phrases.
- Sentiment analysis then parses through the keywords and phrases and interprets their meanings in the context of that conversation.
- Actionable insights are recommendations that tell you what to do with the findings.
Speech analytics technologies existed before AI came into the fold. But adding the AI layer to the speech analytics technology has made it faster, more accurate, and more action-oriented.
For instance, MeetRecord’s speech and sentiment analytics feature quickly analyzes vast amounts of data and provides real-time insights to help you make quicker, data-driven decisions.
Benefits of speech analytics in sales
Sales conversations are a goldmine of insights waiting to be uncovered. But you wouldn’t know it unless you use speech analytics to dig out those insights. Here are the top three benefits of using speech analysis technology specifically in B2B sales scenarios:
Using speech analytics to improve sales performance
Even seasoned sales reps can benefit from a deeper understanding of sales conversations. Speech analytics often reveal data and patterns that can help salespeople drive successful outcomes.
Here are a few tips to make the most out of speech analytics in sales scenarios:
1. Detect doubts or hesitations
Speech analytics technologies are really good at identifying words or phrases that indicate emotions like doubt, hesitation, or confusion. More often than not, customers express these sentiments during sales calls when they aren’t clear about what you say or if your message doesn’t resonate with them.
With real-time sentiment analysis, salespeople can quickly act on this feedback and engage their prospects by addressing their doubts or concerns.
For instance, if a prospect brings up concerns around CRM inefficiencies or data accuracy—like Sarah does in the screenshot below—you can infer that the customer is struggling with data management challenges. Similarly, if they complain that they can’t track call performance—like in Katherine’s case—you can conclude that they need a conversation analytics platform that integrates with the CRM.
2. Analyze objections
While objections are default in sales calls, most sales reps either don’t know how to handle sales objections or wing them with half-baked answers.
Can speech analytics help you handle sales objections? Not directly, but you can use the technology to identify the most common customer objections and document the findings to adapt your sales scripts accordingly. This way, you can prepare yourself for similar situations in the future and improve your conversion rates.
For example, in the screenshot below, you can see a prospect raising concerns about the trial process, how many people they need to involve, or if the setup is simple. If these questions frequently arise, your sales teams can proactively address the objections in future calls and improve the win rate.
3. Discover key moments
Sales isn’t always full of doom and gloom situations — sometimes, customers express ‘aha’ moments that indicate their liking for your product. MeetRecord, for example, can help you understand and categorize customer emotions as either positive, neutral, or negative. If customers express a positive sentiment through their speech, you can tweak your strategy to match their expectations and close deals faster.
Here’s a real-world example. In the image below, you can see the key moments highlighted in stars while the discussion topics are color-coded at the bottom.
This helps an Account Executive quickly see when a customer shows excitement or asks follow-up questions. They can use this interest to guide the conversation to a favorable outcome and increase the likelihood of sales conversion.
4. Meaningful follow-ups
Following up with prospects on your whim or based on automated reminders can be boring — and lack context. But using speech analytics can help you follow up with them based on specific sentiments or intent they had expressed during a call. Calls ending on a positive note signal strong buying intent — and following up promptly can speed up the next steps.
Alternatively, a negative tone may require you to craft a follow-up message that shows proactive concern or helpfulness, which can still land you another meeting with the prospect.
Here’s an example of how MeetRecord generates an AI-powered follow-up email after each sales call. The AI analyzes the call's context and the customer's tone and sentiment to craft a timely, personalized follow-up that aligns with the prospect’s engagement level:
Implementing speech analytics in your sales team
Turning sales conversations into data-driven insights can give your team a competitive edge. But how do you implement speech analytics into your sales process to achieve desired outcomes? Here’s a step-by-step process:
1. Identify key sales goals
One of the first steps to solving any problem is to identify what you want to achieve by overcoming it. What exactly do you want to get out of a speech analytics tool? Your goals may include shortening the sales cycle or increasing conversion rates. Define what’s more important for your team so that you can implement and optimize the tool to drive expected results.
2. Choose the right tool
Rule of thumb — don’t settle with a standalone tool that just offers speech analytics as a product. Instead, pick a tool that meets a wide range of use cases related to conversation intelligence. And make sure the tool integrates with your CRM.
For example, MeetRecord’s all-in-one platform offers an end-to-end solution for sales teams to record and analyze customer conversations and provides actionable insights you can use to improve your sales process. Sentiment analysis is a default part of the product suite that helps you run speech analytics.
3. Train your team
You might be surprised to know that 70% of all change initiatives fail, including the adoption of new tools — mostly due to employee resistance. And the #1 reason your teams don’t like or adopt new tools is because the management doesn’t spend enough time and resources to train them. If you want your teams to make the most out of a speech analytics tool, train them well.
4. Measure results and refine your strategy
This often circles back to the first step — identifying your goals. Once you integrate the speech analytics tool into your sales process, measure it against the milestones that map up to the main goal. If the findings meet your objectives, stretch the goal to achieve better outcomes. If it’s not, refine your current sales approach to meet the goal.
Implementing speech analytics technology is a straightforward process. What’s more challenging is running into unexpected problems that might arise during your implementation.
Here are a few common challenges to running speech analytics and how to overcome them:
Best practices for speech analytics implementation
You can implement speech analytics through trial and error. Or, you can set it up right the first time around and get faster results.
1. Focus on actionable insights
Don’t be obsessed with data. Too much data can be a liability. Instead, identify the high-impact metrics (e.g. talk-to-listen ratio or close probability signals) to drive meaningful improvements.
2. Combine speech analytics with other data sources
Combine the speech analytics findings from other customer interactions such as email, chat, or CRM data to get the full picture. This is why it’s important to use speech analytics as part of a broader conversation intelligence initiative.
3. Regularly audit performance
Most technologies aren’t perfect — including AI. It’s best to take the findings from a speech analytics tool with a grain of salt, review the accuracy, and refine your processes to get optimum results.
4. Learn from successful examples
If you want to maximize the return on investment (ROI) from a speech analytics tool, look at other businesses that have succeeded with it. Case studies on speech analytics for call centers especially provide valuable insights into optimizing your processes and driving sales growth.
How MeetRecord enhances sales performance
Sales teams often overlook the need to mine important insights from customer interactions. MeetRecord automates the entire process so that B2B sales teams can extract valuable insights from customer conversations and improve sales.
Here are a few ways MeetRecord can help sales teams improve their performance:
- Automates call summaries: MeetRecord automatically generates call summaries, and frees up salespeople’s time to focus on more strategic tasks, like closing deals.
- Provides sentiment insights: MeetRecord’s sentiment analysis helps you track customer emotions and engagement levels during calls and emails so you can change your approach in real time.
- Integrates with sales tools: MeetRecord’s integration with popular sales tools ensures a smooth flow of data so that you can understand and apply the findings of speech analytics in a broader context.
- Delivers actionable insights: MeetRecord identifies key patterns and trends in sales calls to offer clear, actionable recommendations that you can use to refine your strategies.
Use speech analytics for better sales results
The landscape of B2B SaaS sales is evolving, and staying ahead of the competition means adapting to new technologies. AI-powered speech analytics can provide valuable insights into customer behavior and give you the edge you need to stay competitive.
Want to see how speech analytics can radically transform your sales outcomes? Book a demo with MeetRecord today to ensure your sales team is set up for success.
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