Responsible for analysis, profiling, and modelling activity in the areas of propensity and segmentation to increase understanding of the customer behaviour pattern and providing actionable insights in developing strategies that will increase the customer lifetime value on the network.
- Analyze micro profiles of all market segments, design models using customer profile attributes, and develop multiple scenarios to illustrate behavior patterns in creating targeting and positioning campaign strategies.
- Develop sensitivity and business models that support direct to consumer marketing programs and maximize execution efficiencies.
- Conducts analyses with a focus on experimental design, assessment, execution, measurement of current programs, evaluation of proposed programs, behavioral analysis, data mining, customer segmentation, predictive modeling, performance management, and other relevant statistical analyses.
- Analysis and data interpretation in support of direct marketing strategy development, program implementation and evaluation/back-end analysis.
- Summarizing analytic findings and integrating with non-traditional data sources (research findings, media surveys, customer behaviors, etc.), when appropriate to enhance campaign development initiatives.
- Develop and use all relevant metrics and measures to continually monitor inactivity and revenue generating base and take appropriate actions to ensure consistent usage and reduce inactivity.
- Conduct analysis and present findings leading to improved customer identification, attraction and retention techniques and methodologies.
- A first degree in relevant discipline.
- Industry Certification(s) and or Postgraduate/Professional qualification(s) in a related field (an added advantage)
Experience,Skills & Competencies
- Three (3) to Five (5) years relevant work experience
- Expert knowledge of competitive environment, consumer trends and trade practices in the industry.
- Advanced data mining and analytical skills such as SAS and SQL.
- Excellent understanding of customer data analysis, propensity modelling and segmentation techniques
- Excellent understanding of data manipulation and interrogation techniques, such as data mining and statistical techniques such as linear and logistical regression, CHAID and clustering.