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Manager - Business Analytics and CVM
2 weeks ago
Identify and implement strategies to generate revenue from a company's data assetsIdentify and implement strategies to generate revenue from a company's data assets.
This includes analyzing data sets to identify valuable insights and potential revenue streams, creating data-driven products or services for targeted campaigns.
Collaborate with other teams such as data scientists, marketers, and legal to ensure that data monetization efforts align with the company's overall goals and values.
Key Responsibilities:
Analyzing data to identify key trends, patterns, and insights that can be used to drive revenue growth.
Based on the insights gained from data analysis, develops monetization strategies that can be used to generate revenue from the organization's data assets.
Implementing the monetization strategies across the organization's various business units, ensuring that they are in line with the organization's overall business objectives.
Measuring the success of the data monetization platform, tracking revenue growth and other key performance indicators to ensure that the platform is meeting its goals and objectives.
Stay up-to-date with the latest trends, technologies, and best practices in data monetization to ensure that the organization is maximizing the value of its data assets.
Defining and strategizing CVM as a service (targeted SMS, WhatsApp, email) roadmap & end to end execution plan.Integration & automation of different IT internal and external systems to build data banks in order to execute multi-segment commercial use cases for customers.
Understanding of Business use cases and convert them into real revenue-generating ideas.Creating business intelligence for B2B Customers and setting up a roadmap for future requirements and Data KPIs.
Business use cases identifications till implementation to get more share of wallet from B2B Customers including managed services for key B2B clients.
Initiative to create new segments in the targeted campaign platform to be used for customers.Collaborate to identify ML model use cases and consumption strategy and best way to drive value.
Driving the cross-functional project team for any new technology implementation with respect to analytics and CVM.Continuous improvement on the platform experience, offerings.
Product Lookalike analysis and target segment identification.Recursive analytics for campaign targeting rule improvements.
Identification of product gaps in the base & success.
Design and implement customer journeys across channels.
Qualification & Experience:
BSc degree in Business / Computer Science / EngineeringMaster degree in Business / Computer Science / Engineering (desired)6+ years of experience in Sales Marketing & AnalyticsStrong Analytical mindsetCustomer Oriented mindset
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