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Client segmentation top-down decision tree
from deck Decision Tree Diagram Charts (PPT Template)

Client Segmentation Top-Down Decision Tree (with Age, Salary, Occupation, Rank of the Credit Score criteria)

Slide Content

The PowerPoint slide presents a decision tree for client segmentation based on various criteria: age, salary, occupation, and credit score rank. Starting from the client, it splits into age categories (under 30, middle-aged, senior) and salary levels (less than 3000, between 3000 to 7000, and over 7000). Each node leads to further classification such as whether the individual is a student or not, and their credit ranking, with symbols representing successful or unsuccessful qualification at each decision point.

Graphical Look

  • The central theme of the slide is a flowchart-like decision tree with interconnected nodes.
  • The nodes are represented by colored circular icons with symbols or numbers indicating different categories such as age and salary.
  • There are checkmark and cross icons indicating a positive or negative decision outcome.
  • The icons for 'Client,' 'Age,' and 'Salary' distinctively feature human silhouettes and a dollar sign, linking the iconography to the concept.
  • Lines connecting the nodes are straight, with right-angle turns, suggesting logical sequence and decision-making steps.
  • The color palette includes shades of blue, green, orange, and purple, creating a contrast between different categories and outcomes.
  • The tree is balanced symmetrically across the center axis of the slide.

The slide is visually clean and structured, utilizing color-coded nodes and icons to represent a systematic approach to client segmentation. The decision tree format is clearly displayed to facilitate understanding of the segmentation process.

Use Cases

  • Explaining customer segmentation strategies in a marketing presentation.
  • Training new employees on client classification procedures within a company.
  • Visualizing decision-making criteria during a business analysis or consulting meeting.
  • Demonstrating the logic of automated systems for credit scoring or eligibility assessment in financial services presentations.

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