Business Intelligence (data management and advanced analytics) and Customer Value Management head
Azerconnect LLC
Total years of experience :14 years, 7 Months
- Established integrated team of Business Intelligence, Data Science and CVM to manage main commercial and financial issues
- Maintained sustainable business strategy to increase market share, aligning with the company's vision
- Leveraged data analytics, machine learning, and domain expertise to drive innovation, improve customer experience, and contribute to the growth and profitability of her organization
- Developed a machine learning model to predict customer churn based on historical usage patterns and customer demographics. This model allowed the company to proactively identify and retain at-risk customers by offering tailored incentives and personalized services, resulting in a 20% reduction in annual churn rate and controlling it to keep under 2%. Significantly improved CLV (customer lifetime value)
- Optimized network team’s performance by analyzing 2G/3G/4G network traffic and revenue by cell sites and capacity leading to increase customer satisfaction due to network quality increase
- Automated customer analytics by creation marketing data mart. Subscriber activity fluctuations and migrations, implemented customer segmentation based on clustering (K-means) and market research data i.e. socio-economic characteristics) which was used to reshuffle the whole product list (ATL, BTL) and profitability analysis of subscriber groups and tariffs. Established customer data management, onboarding new data sources and developed data ingestion pipelines
- Supported marketing with pricing strategy, CVM upsell, cross-sell and retention models resulting in almost doubled growth rate of total mobile revenue vs. previous years
- Analyzing dynamics, trends and performance of the competitors in local market. Monitoring the international trends in telecommunication industry and their impact on commercial strategy of the company
- Designed analytical models based on roadmap of use cases
- Developed CVM campaigns concept based on performance and market
- Defined campaign objectives, KPIs and target segments and microsegments
- Developed and enhanced subscribers’ life cycle management policies and procedures
• Improved a variety of revenue, productivity, cost and other impactful initiatives through complex data modeling, sampling and analysis projects (i.e., 5G rollout, Bad Debt, Market Share, Churn, ATL/BTL Bundles Fluctuations)
• Provided on-going thought on the projects and usage of Data Science frameworks to accomplish business objectives
• Supported customer segmentation predictive analytics lead management and engagement scoring efforts
• Developed business case presentations and action plans to influence up/cross sell for marketing campaigns including targeting recommendations test design cross-sell optimization
• Tightly worked with cross-functional teams to establish periodical reports to identify and present high-level analytics to key stakeholders and executives and bridge the gap between the business/operations and technology
• Analysis and reporting of main Customer Business Unit KPIs
• Produced automated and simplified dashboards and visualizations to help leaders make data driven decisions
• Developed and implemented databases, data collection systems, data analytics and other strategies optimizing statistical efficiency and quality
• Subscriber data management, onboarding new data sources and developed data ingestion pipelines
• Analyzed and translated business requirements into technical specifications
• Troubleshooting and remedy of data quality issues
• Performed analysis producing meaningful insights and recommendations to improve customer retention
• Establishment, execution, maintenance and improvement of periodical reporting infrastructure in commercial area
• Reconciliation of commercial data and reports between various sources and information consumers
- Consulted and supported Analytics and Research Marketing in terms of forecasting, analyzing and reporting customer base trends and preparation of detailed analytical dashboards by main KPIs and presentations to identify problematic segment
- Analysis of dynamics, trends and performance of the market players in targeted marketing and loyalty areas and assessment of their impact on company and exploiting opportunities for revenue generation in the business
- Churn and retention analysis and suggestions and support of retention and loyalty activities. Monitoring effectiveness of churn prevention measures
- Subcsriber data management, onboarding new data sources and develop data ingestion pipelines
- Analyzed and translated business requirements into technical specifications
- Troubleshooting and remedy of data quality issues
- Geomarketing - improvement of geo-spatial reporting and analysis procedures and infrastructure
Established integrated commercial analytics unit of pharmaceutical marketing.
-Pharmacies
-Hospitals
-Doctors
-Sales & profitability of products
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