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Node Split Optimizer

Split the right node at the right time

As the demand for bandwidth continues to increase, MSOs are devoting considerable capital budget to node splits. The success of node splits depends answering two key questions;

Traditionally, network congestion statistics are used as the basis for answering those two questions. However, customers in different nodes with different demographic and competitive characteristics have different tolerance levels to network congestion. Discovering how the customers in a given node will respond to improved network speeds requires considerably more than congestion information. Fortunately, there is a multitude of factors about each node and customer that can be used to predict the value of a node split.

Just as marketers in many industries have obtained improved conversion rates by using big data techniques to better understand each customer, MSOs can improve the financial return of node splitting by using similar techniques to understand the particular characteristics of each node in the plant.

The Node Split Optimizer utilizes a big data approach, incorporating machine-learning and predictive modelling techniques, to quickly and comprehensively assess the multitude of factors involved in node split decisions. Using the Node Split Optimizer, MSOs can unlock unrealized value in their networks by splitting the right node at the right time, and obtaining:

The Node Split Optimizer can be deployed quickly and efficiently, with minimal disruption to the MSO’s organization, and starts to return value in weeks, not months or years. A Pilot deployment can be accomplished in about 60 to 90 days and clearly demonstrates the value of the Node Split Optimizer when fully deployed across an MSO’s footprint.

To learn more, contact us for a demo.

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