Predictive Analytics for Call Center: Forecasting Future Challenges with Dataplatr

"Organisations that can effectively utilise 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, utilise our expertise in contact centre 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 utilising 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 centre metrics dashboards enables businesses to visualise 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 organisations 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 behaviour & previous purchase patterns.
Allocating the available resources accordingly to optimise efficiency.
Solving potential issues before they escalate.
Partnering with Dataplatr enables businesses to leverage the full potential of predictive analytics which utilises the data from descriptive and diagnostic analysis to understand the past trends and identify inefficiencies to anticipate the future chal