동적 고객 세분화 및 생애 가치 최적화 모델

Create a comprehensive Excel spreadsheet for [companyName] that:

1. Imports and consolidates raw customer data with fields including [customerId], [purchaseHistory], [ageGroup], [geographicRegion], [engagementScore], and [lastPurchaseDate].
2. Implements dynamic clustering algorithms using weighted criteria to segment customers into [segmentCount] groups reflecting buying behaviors and demographic profiles.
3. Calculates individual and segment-level customer lifetime value (LTV) projections over a [forecastHorizon] period using historical purchase frequency, average order value, and retention rates.
4. Incorporates scenario analysis to simulate impacts of varying marketing spend and promotional tactics on segment LTV.
5. Automatically updates segmentation and LTV calculations when new data for [newDataPeriod] is added.
6. Visualizes segment distributions, LTV trends, and projected revenue using interactive pivot tables and dynamic charts.
7. Embeds conditional formatting rules that flag segments with declining engagement or profitability for strategic review.
8. Includes a dashboard summary for [targetMarket] that recommends prioritized marketing actions based on segment potential and risk factors.
9. Provides detailed documentation on assumptions, calculation methods, and instructions for updating data inputs.
10. Ensures user-defined parameters such as [inputBudget], [retentionImprovementRate], and [campaignDuration] can be easily adjusted to test optimization scenarios.

Deliver the spreadsheet with modular worksheets separating raw data, processing logic, visual outputs, and scenario inputs to facilitate scalability and maintenance.