Predictive Analytics for Call Center: Forecasting Future Challenges with Dataplatr

Predictive Analytics for Call Center: Forecasting Future Challenges with Dataplatr

Organizations that can effectively utilize predictive analytics are the ones that are bound to be successful in the competition in the long run. A business enterprise to be successful, it is necessary for them to predict the future changes, challenges and be proactive to take on the challenges. We at Dataplatr, utilize our expertise in contact center analytics to help our clients be prepared to take on the challenges.

The Challenges & Solution:

Dataplatr’s call center analytics solutions, utilize the historical data from various sources and develop forecasting models using our data mining, AI and ML expertise to overcome the challenges like data quality, integration and security in predictive modelling. This enables our clients to deploy the forecasting models developed by utilizing the techniques like decision trees, neural network and NLP for ascertaining the future with improved accuracy resulting in better decision making.

The Benefits:

Dataplatr’s capability to build interactive call center metrics dashboards enables businesses to visualize the future trends and provide a comprehensive overview of how they can benefit by predicting the call volumes, customer churn rate, products or services the customer is interested, peak service times and customer sentiment etc., which can help organizations in taking proactive measures like

  • Equipping the representatives with relevant information to increase the first call resolution rate (FCR).
  • Coming up with effective retention strategies for retaining the customers.
  • Recommending the products & services based on their behavior & previous purchase patterns.
  • Allocating the available resources accordingly to optimize efficiency.
  • Solving potential issues before they escalate.

Partnering with Dataplatr enables businesses to leverage the full potential of predictive analytics which utilizes the data from descriptive and diagnostic analysis to understand the past trends and identify inefficiencies to anticipate the future challenges which helps businesses to be proactive and stay ahead in the competition.


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