Senior Specialist: Customer Intelligence

• Manage and deliver customer life cycle programs and activities to maximize the customer lifetime value of the enterprise customers (revenue / margin).
• Develop and manage bundle engagement programme using triggers and behavioural analytics
• Plan, design and execute direct marketing campaigns
• Research and develop methods for measuring and analysing direct marketing campaign impact on customer behaviour as well as revenue (e.g. Design of Experiment)
• Research and implement new methods for optimizing targeting, campaign impact and incremental revenue lift.
• Perform complex analysis on customer characteristics and behaviour to identify opportunities and inform customer value management activities
• Perform diagnostic analysis to understand root causes to revenue dilution or change in behaviour.
• Recommend CVM activities to drive sales and increase revenue.
• Improve CVM data processes though automation
• Consolidate CVM data into one environment to enable ease of access
• Develop, automate, and maintain ETL processes.
• Create automated dashboards using QlikSense
• Develop and maintain and recommend bundle upsell offers
• Select and prioritize leads for different direct campaigns
• Measure effectiveness of direct marketing campaigns using accepted and well researched standards
• Source and process customer feedback from outbound campaigns to inform lead selection and dialling strategies
• Interface with advanced analytics team to ensure seamless handover of model output for campaigns
• Dissect campaign results to understand underlying behavioural patterns and to develop insights
• Developing compelling business cases to support CVM activities
• Set up trigger-based campaigns and manage scheduling thereof
• Source data from different systems, analyse it and provide insights and recommendations to improve business performance.

• Matric/Grade 12 (Essential)
• A 3 year Degree/Diploma in Commerce, Data Science or Quantitative Management/Statistics or any related field
• A minimum of 5 to 8 years data analysis, marketing analytics and/or data engineering experience is essential
• Knowledge on SQL-based databases (e.g. SQL Server, Teradata, Oracle) – Essential
• Database experience (data extraction, transformation & manipulation). – Essential
• An understanding of Python will be an added advantage
• Strong data analytics skills including
• data storage, manipulation, transformation and analysis.
• Advanced knowledge of MS Office Excel and good knowledge on reporting tools i.e. QlikSense, PowerBI.
• Ability to work with multiple data sources – including both transactional and dimensional star schemas & some experience in data model development
• Some exposure to data model development and reporting experience – automating repetitive data reporting tasks
• Excellent communication and conflict management skills.
• Storytelling using data
• Planning and organising skills
• Process and project management skills
• Excellent organisational skills
• Experienced in presenting and communicating findings and recommendations clearly and succinctly.

An understanding of Python will be an added advantage

• Enticing incentive programs and competitive benefit packages
• Retirement funds, risk benefits, and medical aid benefits
• Cell phone and data benefits, advantages fibre connection discounts, and exclusive staff discounts offered in collaboration with partner companies