The Power of virtualQ Algorithms!
At virtualQ, we believe that data is the foundation of any reliable algorithm. Our team of data specialists has spent more than five years collecting and analyzing data with roughly 280 million entries of time series data to develop a precise prediction algorithm. Additionally, millions of status events that originate from the calls we have already routed serve as valuable data points to refine our algorithms. With the vast amount of data we have collected from 100s of call centers and thousands of waiting fields, the number of data points is steadily increasing day by day.
Our AI and Machine Learning algorithms aim to predict the best time to call back a customer, resulting in a win-win situation for everyone involved. Our customers enjoy increased customer satisfaction and a reduction in wait time for callers, while call center managers can optimize their human resources and reduce excess contact center agents. Leveraging an ensemble of models, our machine learning team develops customized solutions that specifically cater to our customers’ unique needs.
These models built by industry specialists are backed by billions of data points and more than 10 years of experience in contact center data analytics and machine learning across various industries and use cases.
Furthermore, to ensure precision in our prediction models, we combine various algorithmic approaches. Our team tests every model rigorously and picks the one with the best response to your data. The team not only looks closely at the data from individual call centers but also augments it with historical industry-specific data and experience from optimizing 100s of call centers over many years. Our approach to data analytics and machine learning makes our algorithms precise, reliable, and optimized to cater specifically to our customers’ needs.
Why virtualQ’s AI algorithms stand out amongst similar offerings is the years of experience we have backed by billions of data points. Our team of machine learning experts has worked relentlessly for over 10 years, continually honing industry-specific algorithms. Additionally, our team comprises former Managers from the AWS machine learning lab, giving our algorithms an edge over our competition.
Conclusion: What makes virtualQ´s Algorithms so special?
- Data-driven: At virtualQ, data is the foundation of every reliable algorithm. Our team has spent over five years collecting and analyzing data to develop an accurate prediction algorithm.
- Custom-fit Solutions: Our AI and machine learning algorithms aim to predict the best time for a callback to a customer, resulting in a win-win situation for all parties involved.
- Analytical Precision: To ensure the accuracy of our prediction models, we combine various algorithmic approaches. Each model undergoes rigorous testing, and the one that demonstrates the best response to your data is selected.
- Experience and Expertise: What sets virtualQ’s AI algorithms apart from similar offerings is our years of experience and the billions of data points that support our work. Our team of machine learning experts tirelessly works to continuously refine industry-specific algorithms.
- Industry Leader: Our team consists of former managers from the AWS Machine Learning Lab, giving our algorithms an edge over the competition.
In conclusion, the contact center industry is facing challenging times, and virtualQ’s AI algorithms cater to the unique and dynamic needs of the industry. Our algorithms predict the right time to call back a customer, ensuring higher customer satisfaction and reduced wait time due to a very accurate forecast and less redails, even under challenging circumstances. Our data analytics and machine learning approach remain unmatched amongst our competition, backed by years of industry-specific experience and billions of data points.
Why do we need such complicated algorithms?
- Your dynamic situation – Economy of uncertainty:
In today’s dynamic world, rapid technological changes, limited human resources, macroeconomic factors, and global trends lead to unpredictable events. These factors create an economy of uncertainty where predictions and planning are often challenging. - Dynamics in contact centers:
Unforeseen events impact call volumes, and each case has a different business scenario. Management objectives constantly change under pressure to achieve better KPIs with fewer resources. In such an environment, complex algorithms are necessary to control the variable elements and achieve optimal results. - Changing user requirements:
In today’s time, users expect accountability: the callback must happen when the user wants it. The caller should not be burdened with responsibilities such as “not answering,” “changing it at short notice,” and so on. The complexity of requests is also increasing. In this context, our algorithms not only help optimize callback times but also contribute to increasing customer satisfaction and utilizing resources efficiently.
Therefore, our intricate algorithms are crucial for navigating this rapidly changing and unpredictable environment while ensuring customer satisfaction.
