How Sales Contact Centers Can Use AI Insights To Increase Efficiency And Profitability
Are your sales agents spending excessive time on administrative work, like logging call details and updating CRM data? Are you struggling to make sure they are spending their time effectively on the calls that matter most rather than getting bogged down in lower-value interactions? I know I was when I was a contact center manager! Some days, I felt like I was in a giant hamster wheel just trying to catch up. The constant pressure of increasing profitability and efficiency is real...
Thankfully for you now, there is contact center AI! In my most recent blog articles, I have shown you how to use AI Insights in your sales contact center to boost revenue and improve sales performance. This is the third and final article in our series on how AI can transform your sales contact center into a powerhouse of efficiency, profitability, and growth.
In this article, we will take a closer look at how AI Insights can help you increase operational efficiency while boosting profitability. AI Insights are data points and pieces of information that are automatically extracted from the transcripts of your call recordings by Generative AI based on specific prompts you provided.
This article is part of a mini-series, "The AI-Powered Contact Center: Transform AI Insights into Action for Lasting Business Growth." You can download the comprehensive guide on using AI Insights to improve sales outcomes here, or read our articles on how to use AI Insights in sales contact centers to:
- Boost your revenue generation
- Improve your team's sales performance
- Increase sales team efficiency and profitability (this article)
The Role of AI in Sales Efficiency and Profitability
AI technology can do more than automatically score your agents' performance and coach your reps. It can streamline the entire operation, helping you manage costs, reduce manual workloads, and make your contact center a lean, efficient machine. In particular, AI Insights can be helpful in increasing your efficiency and improving your organization's profitability by extracting data points and valuable insights. Below are seven examples of how AI Insights can help you achieve exactly that:
1. Automating Data Entry
Manual data entry is time-consuming, tedious, and prone to error. Agents in sales contact centers are often under high pressure to meet stringent sales targets and efficiency KPIs. Every minute that can be saved is valuable time that the agent can spend on the phone, selling.
AI Insights can be used to capture call data automatically and, if the CRM is integrated with your contact center AI solution, log key details from call transcripts into your CRM, thus eliminating the need for manual input and ensuring accuracy. This is especially powerful if used in combination with auto call summaries. Automating this process can increase the data entry accuracy rate from 96% to 99% and reduce errors from 400 to 100 for every 10,000 data entries.
Example: During a call, an agent and a customer discuss a specific product. The agent explained the pricing and addressed some of the customer's concerns. AI automatically captures these details and updates the CRM contact record shortly after the call is completed. This saves the rep an extra 3-5 minutes logging the call and ensures no information is lost or inaccurately recorded.
2. Reducing Sales Costs by Identifying Inefficiencies
The most efficient sales contact centers know where to focus their efforts the most: their "likely-to-close" leads and their high-value customers. Not knowing this forces your agents to use a generic “spray and pray” approach, which causes expensive inefficiencies. AI can spot opportunities to streamline sales processes and optimize resource allocation, such as identifying high-potential leads to focus agent time. For example, AI Insights can assign to prospects a "likelihood to close" status to make it easier for your sales team to know where they should focus their follow-up and outreach efforts. It can also identify high-value customers if your sales team is looking for up- or cross-sell opportunities.
Example: An agent just finished a conversation with a prospect who is excited to purchase a specific product. The prospect ended the conversation by agreeing that they would be in touch soon after they spoke with their spouse. AI Insights tags this call as "likely to close," prompting the sales person to prioritize the prospect in their follow-ups in the coming days.
Image: A screenshot from the MiaRec application displaying an AI-generated call summary alongside an AI-assigned "Likelihood to Close" score for the prospect, determined based on the conversation context.
3. Customer Journey Mapping
Another great way to use AI Insights to increase sales efficiency and effectiveness is to use it for customer journey mapping.
By tracking leads through every stage of their journey, AI helps sales teams prioritize high-value prospects, address specific needs, and proactively manage potential obstacles. For example, AI can analyze customer sentiment, topics of interest, and deal stages from call transcripts, providing a clear picture of each customer's progress. This insight empowers sales managers and agents to make informed decisions about next steps and focus their efforts where they are most likely to drive results.
If you assign client phone numbers to a "Client" in MiaRec, you can easily track where they are in their customer journey with AI Insights:
Image: This screenshot shows how you can assign a phone number to a client as a unique identifier which allows you then to track them through their customer journey.
Client | Call Date | Deal Stage | Product | Topics | Sentiment Label |
John Smith | 7/1/2024 | Prospect | Mutual Funds | Investment, Pricing Inquiry | Very Positive |
John Smith | 7/8/2024 | Prospect | Mutual Funds | Investment, Pricing Inquiry, Upgrade | Positive |
John Smith | 8/6/2024 | Discovery | Mutual Funds, Bonds | Investment, Pricing Inquiry | Positive |
John Smith | 8/25/2024 | Proposal | Mutual Funds, Bonds | Frustration, Investment, Lack of Knowledge, Pricing Inquiry | Negative |
John Smith | 9/3/2024 | Proposal | Mutual Funds, Bonds | Escalation Request, Frustration, Investment, Lack of Knowledge, Pricing Inquiry | Very Negative |
John Smith | 9/15/2024 | Proposal | Mutual Funds, Bonds | Investment, Pricing Inquiry | Neutral |
John Smith | 10/1/2024 | Closed | Mutual Funds, Bonds | Investment, Payment Made, Pricing Inquiry | Positive |
John Smith | 10/17/2024 | Closed | Mutual Funds, Bonds | Frustration, Order Cancellation, Refund Request | Very Negative |
4. Spotting Customer Advocacy Potential
Sales contact centers are untapped gold mines containing customers that would be happy to refer you or become advocates. The problem—until now—was how to identify them. Thanks to AI Insights, that is now easy. Simply ask the AI to identify customers expressing high satisfaction or willingness to recommend. Then, your sales team can immediately nurture these customers into advocates or referral sources.
Example: A customer is very pleased with their purchase experience. During the call, they say, "This has been great so far!" The AI picks up on their possible customer advocacy potential. The sales rep can now reach out with a family and friend referral coupon.
Image: Screenshot from a "Customer Advocacy Potential" report in the MiaRec application. From here, you can easily click on "View calls" to review calls where the AI has identified callers with a high potential for customer advocacy.
5. Identifying Post-Purchase Friction Points
Post-sale interactions are critical for long-term customer satisfaction and retention. Customers, even though they have already purchased the product, often have lingering objections or hesitations. AI can analyze call transcripts to identify those, helping your onboarding and customer success team proactively address and resolve them.
Example: AI notices that a customer mentioned multiple times that they aren't technically inclined and that they are hesitant about the setup process. The salesperson reassured them that the setup would be easy. However, after purchasing the product, the customer still fears that the solution might be too technical for them. Because the onboarding team is aware of their hesitation, they can proactively address it: "So, I know you were concerned about the technical setup. We are here every step of the way!" Thanks to AI, the customer feels heard and well taken care of.
6. Competitor Benchmarking Feedback
Understanding how customers perceive your product compared to your competitor's product is crucial for positioning and improving sales strategies as sales teams often struggle with competitors claiming to be cheaper or better. AI Insights can track how customers perceive your product compared to a competitor's, providing valuable insights to address competitive threats.
Example: During calls, customers frequently mention a competitor’s particular feature. AI tracks these mentions and explains why customers may favor a competitor in specific areas. This allows your sales and marketing teams to adjust messaging or product features to compete better, ultimately leading to a stronger position in the market.
Image: A screenshot from the MiaRec application demonstrating how Topic Analysis identifies calls where competitors are mentioned. It also showcases how AI Insights provides detailed context about the competitor mentioned.
7. Improving Training Effectiveness
Our last example of how to use AI Insights to boost your sales contact center's efficiency is using AI Insights to improve your training effectiveness. When it comes to training, sales contact centers often invest a lot of time, energy, and resources, but measuring the effectiveness of each training session is often difficult. While tools like Auto QA can measure objective metrics, such as script adherence or compliance with specific guidelines, AI Insights takes it further. It evaluates whether agents are effectively implementing soft skills and sales techniques learned during training, and then offers actionable insights to improve their performance.
Example: Your agents recently completed a contact center etiquette and objections-handling training. Now you are customizing the AI Insights prompt to specifically look for whether or not your agent is following what they learned in their training.
Practical Steps to Leverage AI for Efficiency and Profitability
Start with Automation
The fastest route to efficiency is automation. Start by automating repetitive tasks like data entry and follow-up logging. Implementing these quick wins will free up your reps to focus on building relationships and closing sales.
Use AI to Optimize Workflows
If possible, integrate AI with your CRM and other systems to provide reps with valuable insights and next-step suggestions. These integrations will make workflows smoother and ensure that reps always know what they should do next.
Analyze, Iterate, Improve
AI is not a one-and-done solution. Continue to analyze call data, assess productivity, and iterate on your processes. Efficiency and profitability will improve as you continually refine how AI is integrated and used within your operations.
Conclusion
AI can significantly boost the efficiency and profitability of your sales contact center by automating repetitive tasks, suggesting the next best actions, optimizing resource allocation, and identifying opportunities for operational improvement. By leveraging AI to streamline your workflows and reduce inefficiencies, you’re not just saving time—you’re setting the foundation for long-term profitability and growth.
If you're ready to see how AI can help streamline your contact center and boost profits, schedule a demo today, and let’s start transforming your operation into an efficient, well-oiled machine.
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