The landscape of customer service is rapidly evolving, with Contact Center as a Service (CCaaS) providers at the forefront of this transformation. CCaaS businesses operate in a realm defined by two essential elements: sophisticated software infrastructure and the dedicated agents who utilize these tools to deliver exceptional customer experiences. However, amidst the focus on software enhancement, a critical challenge often takes the back seat: high Agent Attrition. This challenge, if left unaddressed, can result in significant financial strain for CCaaS providers.

Traditional solutions to tackle Agent Attrition have been manual, purely driven by business acumen and experience. The business rules update cycles are also long and often outdated with the frequent changes in Agent profile and metrics.. Leveraging advanced Machine Learning solutions, the entire solution becomes Data Driven and Automated.. This technological synergy has paved the way for a revolutionary approach to managing Agent Attrition in contact centers.

Understanding the Advanced Approach: CCaaS Agent Attrition Machine Learning Solutions

Our “Agent Attrition — Machine Learning” solutions stands as a beacon of innovation, designed to combat the pervasive issue of high agent attrition in CCaaS business. The ML approach empowers CCaaS providers to implement targeted measures hence retaining their valuable talent pool and ensuring the continuity of exceptional customer service.

The Journey: From Raw Data to Informed Decisions

Data Preparation: Agent Bucketing

A typical Agent undergoes multiple stages (training, pre-production, in-production, in-reserve etc.) throughout their employment. Our solution focuses on identifying these stages, bucketing Agents and their Features in these business relevant stages and training a separate model for each bucket/stage. This approach enables a focused attention to Agent data, their performance KPIs and hence a more relevant, at Risk Agent predictions.

Data Preparation: Cohort Analytics Report

The complexity of data collection in real-world scenarios necessitates meticulous planning. We collaborate with our clients, drawing up a comprehensive Data Dictionary and a Cohort Analytics Report. This step ensures a deep understanding of available agent features, their business context and relevance to Agent behavior and performances. The Cohort drawn is in agreement with the business stakeholders. This ensures the data that will be fed into the Models will be correct and business relevant.

ML: Data Preprocessing:

Data preprocessing is pivotal for best Model selection, Training and accurate predictions. At this step within the Cohort Data, we address the data issues such as missing data, skewed data, non normally distributed data, imbalanced categorical representative data, highly correlated features, and more. Above steps ensure a clean and statistically relevant dataset for the best Machine Learning Model Training.

ML: Encoding and Scaling:

To prepare the data for Machine Learning models, we encode categorical features and standardize the numerical features, ensuring consistent scales and optimal Model Training. Scaling ensures all Features are equally weighted when Model is trained..

ML: Model Training and Selection:

Multiple Supervised Classification Machine Learning Models were evaluated at the experimentation stage, some of which include Logistic Regression Classification, Random Forest Classification, and Gradient Boosting Classification. The Gradient Boosted Model provided the best performance on the selected KPIs (precision and AUR-ROC) for each of the buckets..

ML: Model Optimizations and Validations:

Selected Gradient Boosted Algorithm was then run through model optimization steps such as Hyperparameter Tuning, K-Fold Cross-Validations etc. This ensured for the best Model Hyperparameter selections. Also the Cross-Validation helped understand model generalization and over/under-fitting.

ML: Model Explanations:

Model predictions were backed with prediction probabilities and SHAP values and SHAP Feature importance values. The features fed into the Model were listed in Descending order of SHAP Feature Importance values. This helped the business understand the Model prediction better with the necessary Agent Features to focus on, for deciding on the mitigation strategies.

MLOps: GCP Vertex AI Pipeline and Looker Dashboard:

All the above ML steps,, from data preprocessing to model predictions, were modularized and orchestrated through the GCP Vertex AI Pipeline. The model serving was automated with triggers on Data refresh for new Prediction runs on Business defined frequencies.The predictions were served to the Business via Looker Dashboards, providing a comprehensive view of Agent at Risk Predictions along with their Features which influenced the Model Predictions.

Transformative Impact and Future Ready

The implementation of our CCaaS — Agent Attrition Machine Learning system brought forth transformative changes for our clients:

• Automation of Attrition Probability and Agent Identification: Rules to identify the Agents at risk of attrition was now Data Driven, Automated with Shorter Refresh cycles.
• Feature Significance Insights: Agent Features influencing attrition were highlighted, guiding targeted mitigation strategies for the Business.
• Informed Business Decisions: The Looker Dashboards empowered businesses to draw informed strategic plans, reducing agent attrition and minimizing operational costs.

Embark on a Future of Success

At Dataplatr, we are dedicated to empowering businesses with innovative solutions. Our CCaaS Agent Attrition Machine Learning system is a testament to our commitment to revolutionizing the contact center industry. Join hands with us to embrace a future where advanced technology meets human expertise, ensuring unparalleled customer service and lasting success.

Ready to Transform Your Contact Center? Schedule a Consultation Today!

The future of your contact center begins now. Schedule a consultation with our experts to explore how our tailored CCaaS Agent Attrition Machine Learning system can elevate your business to new heights. Partner with us and embark on a journey of optimized operations, reduced attrition, and enhanced customer satisfaction. Together, let’s transform your contact center into a beacon of excellence in customer service.

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