Senior Customer Segmentation Specialist

Responsibilities

Customer Segmentation & Strategy Development

·      Develop robust segmentation frameworks by analyzing behavioral, transactional, demographic, and psychographic data.

·      Create and maintain customer personas and lifecycle stages to inform product and marketing strategies.

·      Implement advanced segmentation techniques, such as RFM analysis, propensity modelling, and cluster analysis.

·      Continuously refine segmentation models to adapt to changing customer needs and market dynamics.

Data Analysis, Insights, and Predictive Modelling

·      Analyze complex datasets to uncover trends, patterns, and actionable insights that drive business decisions.

·      Build predictive models to forecast customer behaviors, including churn risk, credit needs, and upsell potential.

·      Collaborate with data science teams to design machine learning algorithms for dynamic segmentation.

·      Translate data insights into clear, actionable recommendations for marketing, sales, and product teams.

Digital Campaign Targeting and Personalization

·      Partner with digital marketing teams to design and execute highly targeted campaigns for different customer segments.

·      Implement and optimize personalized messaging, product recommendations, and promotional offers across digital platforms (mobile apps, websites, email, SMS, and social media).

·      Utilize A/B and multivariate testing to enhance campaign performance and customer engagement.

·      Track and report on campaign performance, ensuring continuous improvement in ROI and engagement metrics.

Customer Journey Optimization

·      Map and analyze end-to-end customer journeys for key segments to identify pain points and opportunities.

·      Develop strategies to enhance the digital customer experience, driving satisfaction, retention, and cross-selling.

·      Collaborate with UX/UI teams to implement customer-friendly digital solutions tailored to specific segments.

Cross-Functional Collaboration

·      Work closely with product, marketing, sales, and IT teams to ensure alignment between segmentation strategies and business objectives.

·      Provide strategic input to product development teams for designing products and services that cater to targeted customer needs.

·      Act as a bridge between business and technical teams to ensure seamless integration of segmentation strategies into digital platforms.

Data Management and Governance

·      Ensure data accuracy, integrity, and compliance with Vietnamese data privacy laws and regulations.

·      Oversee the collection, storage, and usage of customer data, ensuring adherence to company policies and industry standards.

·      Advocate for a data-driven culture within the organization by promoting the importance of analytics and insights.

Qualifications

·      Bachelor's or Master's degree in Business Administration, Marketing, Data Science, Statistics, or a related field.

·      5+ years of experience in customer segmentation, data analytics, or digital marketing, ideally in the financial services or consumer finance sector.

·      Proven track record of managing large-scale segmentation projects and implementing data-driven strategies.

Technical Skills:

·      Strong proficiency in data analytics tools (SQL, Python, R) and data visualization platforms (Tableau, Power BI).

·      Experience with CRM and marketing automation tools (e.g., Salesforce, HubSpot, or similar).

·      Familiarity with advanced statistical techniques and machine learning algorithms for segmentation and predictive modelling.

Soft Skills:

·      Strategic thinker with a customer-first mindset.

·      Excellent communication skills, with the ability to present complex data insights to non-technical stakeholders.

·      Strong leadership and collaboration skills to drive cross-functional projects.

·      Detail-oriented with strong problem-solving abilities.

·      Creative mindset with a focus on customer-centric marketing.

·      Growth in customer acquisition and retention rates within key segments.

·      Improvement in digital campaign engagement and conversion metrics.

·      Increase in cross-sell and upsell opportunities identified through segmentation.

·      Reduction in churn rates within high-value customer segments.

·      Timeliness and accuracy of data insights delivered to stakeholders.