AI-Enriched Conversational Intelligence
Powered by Dubber

Absolutely, call reviews are valuable. However, Evolve IP’s conversational intelligence solution powered by Dubber goes beyond simple listening. It uses AI to analyze every conversation, identify key talking points, and surface actionable insights you might miss on a single listen. Imagine having all your calls summarized with key points and customer sentiment readily available.

Dubber is a coaching tool, not a surveillance mechanism. It can help identify areas for improvement and celebrate successes. Features like anonymized data analysis help focus on trends and avoid singling out individuals.

Conversational Intelligence is a technology that uses AI to automatically transcribe, analyze, and score every call that takes place in a call center. CI can capture the voice of the customer and the agent, and extract key information such as sentiment, emotion, intent, topics, keywords, and compliance. CI can also provide real-time feedback and coaching to agents during or after the call, as well as generate reports and dashboards for managers to monitor and improve the overall call quality and customer satisfaction. CI can integrate with existing call center platforms and CRM systems, and offer a scalable and flexible solution that can adapt to different business needs and goals.

Traditional Quality Management is a process that involves manually reviewing a sample of calls by a dedicated staff member, usually a quality analyst or a supervisor. The staff member listens to the calls and evaluates them based on predefined criteria, such as call duration, customer satisfaction, agent behavior, and compliance. The staff member then provides feedback and coaching to the agents, and generates reports and dashboards for managers to track and improve the call quality and customer satisfaction. Traditional QM is often limited by the availability and expertise of the staff member, the accuracy of the sample and how it lines up with prototypical recordings, and the timeliness and effectiveness of the feedback and coaching.

To compare the ROI of CI and traditional QM, we will use a realistic scenario of a call center with 30 agents, who handle 60 calls per day each, for a total of 1800 calls per day. We will also assume that the call center has a dedicated QM staff member, who earns a loaded salary of $90,000 per year, and that the current success rate of traditional QM is 3% of calls reviewed. We will also assume that the cost of CI software is $49.95 per month per agent. We will then calculate the cost per call reviewed, the net savings, and the ROI for both methods, as well as consider some additional factors that could affect the comparison.

The table below summarizes the results of the comparison between CI and traditional QM, based on the scenario described above.

As the table shows, CI can review 100% of calls, compared to only 3% by traditional QM, for a much lower annual cost and cost per call reviewed. CI can also produce $54,036 in net savings per year, by replacing the dedicated staff member's salary with the CI software cost, and generate a very high ROI of 300.6%. However, these results are not the only factors to consider when comparing CI and traditional QM. There are also some additional considerations that could affect the comparison, such as the impact of CI on agent performance, customer satisfaction, and employee engagement.

Besides the financial aspects, there are also some qualitative aspects that could influence the comparison between CI and traditional QM. These include:

• Improved Agent Performance: CI can offer more granular and objective insights into call quality, such as the sentiment, emotion, intent, and compliance of the customer and the agent. CI can also provide real-time feedback and coaching to agents during or after the call, as well as personalized recommendations and best practices. These features can potentially lead to more targeted and effective coaching, improved agent skills and behavior, and increased agent confidence and motivation.
• Increased Customer Satisfaction: Better trained and equipped agents can lead to higher customer satisfaction scores, as they can handle customer inquiries and issues more efficiently and empathetically. CI can also help identify and address customer pain points, needs, and expectations, and provide insights into customer loyalty and retention. These features can potentially lead to more satisfied and loyal customers, increased customer lifetime value, and positive word-of-mouth.
• Employee Engagement: Freeing up the dedicated staff member's time from manual call reviews could be used for other tasks or potentially redeployed elsewhere, impacting overall employee engagement. CI can also help create a culture of continuous learning and improvement, where agents and managers can collaborate and share feedback and best practices. These features can potentially lead to higher employee engagement, lower turnover, and higher productivity.