6 High-Impact Ways To Improve Your Sales Performance Using AI Insights

Did you know that only 21% of sales calls result in a win, and up to 60% of sales interactions end in indecision? While these facts might be surprising, they also show that there is a lot of room for improvement when it comes to sales performance. This is where AI Insights come in.

AI Insights are insights and data points extracted from call recording transcripts using generative AI. This year alone, I have helped dozens of companies significantly improve their sales performance by implementing AI Insights. The outcomes are astounding.

However, I also noticed that it is hard for many contact center managers to imagine what is possible with AI. Last week, I published the first article of a mini-series in which we explored how AI can help boost your contact center’s revenue by identifying missed opportunities, tailoring customer offerings, and more.

Now, I want to tackle another major challenge with you: improving the overall performance of your sales team. As a former contact center manager, I struggled to ensure consistent rep performance, high-quality interactions, and effective coaching. The good news? AI Insights are here to make that job a whole lot easier. Let’s look at how AI Insights can improve your team's sales performance.

The Role of AI in Sales Enhancement

AI, especially generative AI, has already drastically transformed how we sell. In this article, we will focus specifically on AI Insights. AI Insights are data points and information automatically extracted from call transcripts to answer specific questions. This leads to tangible improvements in sales techniques and efficiency. While AI Insights live mainly in your Contact Center AI solution, like MiaRec, they can be pushed into CRM systems if integration is available, drastically reducing the error rate and the time an agent spends on data entry. 

AI Insights for Sales Improvement

AI can help transform the way your sales reps interact with customers. By analyzing recorded calls, AI surfaces insights that can increase training efficiency, improve adherence to sales processes, pinpoint coaching opportunities, and much more, with the goal of ultimately leading to better sales outcomes. 

Challenges Faced by Sales Teams in Contact Centers

Sales teams often struggle with maintaining consistency across interactions, handling objections effectively, and staying on top of customer needs. AI brings a level of consistency that is hard to achieve manually, giving managers the ability to train, coach, and improve reps in a data-driven way.

Key Ways AI Insights Can Improve Sales Performance

1. Categorizing Sales Calls for Targeted Coaching

Unless you are purely a sales contact center, one of the biggest hurdles is knowing which calls are sales calls and which are customer support interactions. AI automatically categorizes calls as “sales calls” or “support calls” and flags interactions that need improvement. This ensures that sales-specific coaching efforts are directed where they will have the most impact: on sales calls.

Example: Your contact center receives hundreds or even thousands of calls every day. You want to improve your agent's closing technique and ability to handle objections. To do that, you have to pick the right calls to review and provide feedback on. AI Insights can automatically categorize calls by Sales or Non-Sales Calls or even go deeper to identify those calls where a customer raised objections (e.g., price is too high) or a deal was won or lost.

2. Lead Scoring for Better Prioritization

Traditionally, lead scoring is done within the CRM by assigning scores based on actions and events, like email opens, page views, etc. However, AI Insights can add context and nuance to lead scoring beyond typical CRM-based scoring methods. By analyzing the content of calls, AI adds a qualitative layer that can help prioritize leads more effectively.

Example: During a call, a customer expresses genuine interest in a specific product feature and mentions their company’s immediate need for a solution. AI picks up on this and adds a signal to the lead score in the CRM, giving reps a more nuanced view of the lead’s readiness to buy and prompting them to focus follow-up efforts accordingly.

3. Identification of Buyer Intent

Identifying buyer intent from traditional signals alone can be difficult. AI can identify strong buying signals within call transcripts by analyzing specific phrases, questions, and customer sentiment. This helps sales reps understand the level of intent and allows them to adapt their approach quickly.

Example: During a call, a customer asks detailed questions about product integration and mentions timelines for purchasing. AI identifies this as a high buyer intent, flagging it for immediate follow-up and highlighting the need for tailored engagement to close the sale. As a next step, the agent could send a how-to video explaining how easy it is to integrate both solutions, moving the deal forward.

4. Analyzing Common Sales Objections

One of the biggest challenges for sales teams today is handling objections effectively. To learn how to successfully address or (even better) proactively bring up common objections, you need to know which objections your buyers have. AI listens for and tracks these objections across multiple calls, giving managers insight into the most frequent barriers reps encounter. Now, managers can design training and coaching around these objections.

Example: AI identifies that a recurring objection revolves around product pricing being too high. Sales managers can then create specific training sessions or scripts to help reps address this concern, framing the product’s value to mitigate the pricing objection.

5. Providing Individualized Coaching Recommendations

Ideally, we would like to give each agent feedback after almost every call. However, we all know how difficult it is to even evaluate agent performance manually on a fraction of calls every day. Thanks to AI Insights, your agent can now have personalized coaching suggestions right within the call record after every call. Within MiaRec, for example, you can include detailed information in the prompt, describing what good looks like. This way, your AI looks specifically for those quality standards that are important to your organization.

Example: AI notices that a particular rep struggles with closing statements. It offers individualized coaching suggestions to improve closing techniques, helping the rep become more effective in sealing deals. 

6. Sharing Best Practices Across Teams

Sharing best practices across a sales team is a great way to improve sales performance. AI can help identify which sales techniques work best by analyzing the most successful sales calls. Contact center managers can then share these best practices across the team, helping less experienced reps learn and adopt winning strategies.

Example: AI flags a high-performing sales call where the rep effectively handled multiple objections and closed successfully. The system extracts the key strategies used. These are then shared with the entire team, allowing everyone to learn from top performers and replicate success.

Practical Steps to Leverage AI for Sales Improvement

Start by Identifying One or Two Areas for Improvement

AI Insights are game changers, and once you implement them and see firsthand what is possible, all kinds of ideas come to mind. But rather than trying to build the ocean and solve every challenge at once, focus on one or two high-impact areas where your team could improve, such as objection handling or effective questioning. Implement AI Insights here first to see a quick impact, and then expand from there.

Integrate AI Insights with CRM Systems

One of the most powerful ways to take AI Insights from "good to have" information to actionable insights is by integrating them with your CRM system. Start by adding detailed call notes and a few extracted data points to the CRM contact records. As you gain confidence, add more complex scenarios, e.g., using AI Insights to get better lead scoring.

Continuous Iteration and Feedback Loop

AI Insights get more powerful over time. Use AI iteratively: Try something new, iterate, measure your results, and adjust as needed to refine your approach. Over time, the data collected will provide a clearer picture of what works and where there is room for improvement.

Conclusion

AI can be a powerful tool in driving consistent, high-quality performance across your sales team. By focusing on targeted coaching, improving objection handling, and sharing best practices, AI helps your sales reps become more effective in every customer interaction.

Ready to see how AI can help your team perform better and close more deals? Schedule a demo today to explore how integrating AI Insights into your sales process can turn your reps into high-performing sales stars.