The Interview World

Moodmap AI, a tech startup situated in Armenia, specializes in offering an AI-based intelligent assistant for customer service teams. This innovative system incorporates live suggestions and real-time analytics to enhance the performance of customer service agents. By leveraging an AI emotion detection model, the platform provides dynamic suggestions during each customer interaction. This not only aids agents in maintaining an emotional connection with customers but also helps in preventing misunderstandings and improving overall communication.

In an exclusive interview with The Interview World, Gagik Tamazyan, the CEO of Moodmap AI, sheds light on how his startup is on the brink of transforming contact center communication. He emphasizes the pivotal role of the system in measuring Customer Satisfaction (CSAT) and evaluating agent performance. Here are the key highlights from his insightful interview.

Q: Can you share insights into the journey that has shaped its success?

A: Two years ago, we embarked on our journey, commencing from the mid-Cacaton region. Emerging victorious among 50 startups, we swiftly assembled our team, which now comprises seven members. This includes five proficient data scientists, myself as the business representative, and a robust backend engineer.

Presently, our application stands as a testament to our progress, requiring no intricate integration process. Installation on your agent’s computer is all that’s necessary, enabling automatic comprehension of calls, identification of the speaker (such as the agent), and streamlined analytics – all achieved without the need for call center integration.

In addition to our initial success, we clinched victories in several hackathons and secured grants, including one from the Ministry of High-Tech Industry of Armenia. Currently, we are in the process of finalizing a contract with our second client, bolstering our clientele to two.

Highlighting our technological prowess, we’ve developed a proprietary voice emotion detection AI model, solidifying our standing in the industry.

Q: What strategies and features does Moodmap AI employ to intelligently address the challenges faced in customer care services?

A: We specialize in comprehending human emotions through voice analysis, providing real-time suggestions to agents during calls to refine their speaking style. Additionally, our text analysis capabilities allow us to understand your customers’ communication patterns and discern the content of their messages. Furthermore, we gain insights into the interactions between your agents and customers.

This enables us to automate not only customer satisfaction but also streamline workforce management. Our approach goes beyond the surface, offering deep analytics to unveil ongoing trends and identify potential issues within your product. In essence, our solution is designed to enhance the efficiency of your operations by addressing and optimizing various aspects of your customer interactions.

Q: Does your solution also address the conversion rate Issues?

A: Our solution offers adaptability as it leverages seven AI models. This flexibility allows you to tailor it to different industries and specific requirements. For instance, if your goal is to boost sales, you have the option to fine-tune the models to provide targeted suggestions to sales representatives.

In practical terms, during customer interactions, our system can prompt the salesperson with specific guidance. For instance, it might suggest phrases like “Avoid asking questions” or “Take a moment to breathe before suggesting discounts.” This type of tailored advice enhances the salesperson’s approach and effectiveness.

Q: Could you provide details about the analytics solution offered by your organization?

A: Certainly, we offer various types of services to cater to our customers’ needs. Our goal is not only to ensure overall customer satisfaction but also to tailor it to specific products. For instance, imagine a scenario where a customer contacts you, expressing dissatisfaction with their credit card performance but praising your competitive credit loan percentage.

In such cases, our sophisticated program comes into play, distinguishing between negative sentiments associated with credit cards and positive sentiments related to the credit loan percentage. This allows us to comprehend and address specific concerns effectively.

Q: How does your organization implement security protocols to effectively address the growing cybersecurity challenges specifically in call centers?

A: We offer two distinct options for utilizing our technology. Firstly, we provide it as a Software Development Kit (SDK), where all the models are hosted on your server—whether it be cloud-based or on-premise. In this setup, we integrate small applications into agent components, ensuring that all operations take place within your company. Importantly, we do not have access to your data.

Alternatively, our second option involves processing voice data. We extract numerous numerical representations—around 3,200 numbers per minute of a call—from the voice. Subsequently, these numbers are transmitted to our server. During this process, we strategically truncate a portion of the data within the PCO of the agent, transmitting only 95%. Despite the reduction, this 95% retains the essential information for our understanding.

It is crucial to note that while we can comprehend the content, we are unable to revert it to text or recreate the original voice. The choice lies between implementing this system on your server or utilizing our server for these operations.

As you accumulate a substantial volume of posts and text interactions, patterns emerge, offering valuable insights into prevalent issues and areas of customer satisfaction. This knowledge becomes instrumental in refining our services and addressing customer needs more efficiently.

Q: What is the current reach of this application?

A: We are a startup currently operating in Armenia, and this marks our inaugural venture into India. Our primary focus is on outsourced call centers, particularly those based in India. Currently, we collaborate with call centers in Armenia that are managed by US-based companies. However, we have yet to explore the global market, making this our debut on the international stage.

Intelligent Emotion Detection Model Designed by Moodmap AI
Intelligent Emotion Detection Model Designed by Moodmap AI

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