동적 다요인 고객 세분화 매트릭스
[companyName]의 정교한 타겟팅 전략을 가능하게 하는 행동, 인구 통계, 거래 데이터를 동적으로 통합하는 다차원 고객 세분화 매트릭스를 생성합니다. 이 모델은 세그먼트의 수익성 및 성장 가능성을 우선하며 [dataSource]로부터 새로운 입력에 따라 동적으로 업데이트할 수 있습니다.
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Develop a dynamic Excel model for [companyName] that performs the following: 1. Import and normalize raw customer data from [dataSource] including behavioral metrics (e.g., purchase frequency), demographic attributes (e.g., age, income), and transactional information (e.g., average order value). 2. Create weighted scoring criteria based on [weightBehavior], [weightDemographic], and [weightTransactional] to evaluate each customer. 3. Use clustering algorithms or pivot logic to segment customers into distinct groups reflecting similar profiles. 4. Incorporate a profitability index derived from [profitMargin] and customer lifetime value calculations. 5. Visualize segmentation results via a matrix displaying segments with their size, profitability, and growth potential. 6. Enable dynamic filtering by [timePeriod] and [region] to observe temporal and geographic variations. 7. Include conditional formatting to highlight high-value or at-risk segments automatically. 8. Provide a summary dashboard with interactive slicers to facilitate scenario analysis. 9. Document all assumptions and methodologies in a dedicated 'Notes' worksheet. 10. Ensure formulas are robust and protected against data input errors. Output deliverables should empower marketing and sales teams to tailor campaigns efficiently for [targetMarket].
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