Thursday, 29 June 2017

WeDo launches Shape Telecom

WeDo
Wednesday 08 July 15

WeDo Technologies, a worldwide leader in Enterprise Business Assurance (EBA), has today announced the launch of SHAPE Telecom; software designed to provide CSPs with advanced knowledge to ascertain cost and determine profitability of customers, plans and services. SHAPE Telecom improves customer-base knowledge to critically determine marketing campaign effectiveness, enhance customer satisfaction and boost customer loyalty and retention. SHAPE Telecom leverages customer data to expose a rich behaviour profile for CSP marketing…

WeDo Technologies, a worldwide leader in Enterprise Business Assurance (EBA), has today announced the launch of SHAPE Telecom; software designed to provide CSPs with advanced knowledge to ascertain cost and determine profitability of customers, plans and services. SHAPE Telecom improves customer-base knowledge to critically determine marketing campaign effectiveness, enhance customer satisfaction and boost customer loyalty and retention.

SHAPE Telecom leverages customer data to expose a rich behaviour profile for CSP marketing, sales support and finance teams, offering a better view of key customer value drivers and enabling a customer approach based on their value to the CSP. By cross-referencing customer activity, the solution identifies correlation between behaviour and/or customer preferences, facilitating the creation of new offers for improved customer retention.

Due to its unique data repository, SHAPE Telecom delivers a unified 360-degree view of the customer, allowing service providers to properly apply segmentation rules; focusing on the real value of each customer segment and not merely identifying which customers have the highest revenue. With prebuilt segmentation models designed specifically for the Telecom industry, the stability and accuracy of predictions can be verified and tuned easily by visual model assessment and validation metrics. SHAPE Telecom delivers a profiling model for specific areas to provide straightforward understanding of how the predefined variables contribute to the outcome being modelled.

The five areas that SHAPE Telecom covers include:
• Customer Profitability – identifies all costs involved in the acquisition and maintenance of a customer, while calculating the contribution of each customer to the bottom line.
• Customer Optimization – determines customer habits and usage to identify which selected new products and services can be tailored and offered to customers to increase their value.
• Churn – identify and describe customers at risk of churning and possible causes, including quantification and analysis of the internal churn’s effect.
• Social Value – establishes the effect of subscribers’ social networks on products and services and identifies and monitors 'influencers' to target them with customised marketing offers.
• Monetisation – analyses customer behaviour and consumption patterns to discover how products and services can be priced to maximise their profitability.

SHAPE Telecom represents the evolution of WeDo Technologies’s previous churn prediction solution, Customer Value Broker; using the product experience to expand from solely churn to address SHAPE’s five key areas. It also offers synergies with RAID Telecom, allowing a RAID customer to accelerate the results attained with SHAPE and lower the Total Cost of Ownership (TCO) by implementing the two together.

“In today’s rapidly expanding telecoms market, WeDo recognised the growing need for CSPs to develop new services that address an increasing number of industry challenges, including high market penetration, price competition and a decline in customer loyalty,” said Tony Poulos, Market Strategist, WeDo Technologies. “SHAPE Telecom was designed with the main goal of determining cost and profitability at customer and plan levels and, at the same time, delivering segmentation models for target campaigns that address both customer value growth and customer satisfaction. SHAPE Telecom offers self-service analytics, without the need to rely on data scientists or IT.”


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