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Examples of business intelligence goals from a smart sales project.

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smart-sales-analysis-goals

Examples of business intelligence goals from a smart sales project.

Objective

In any business intelligence (BI) project, data-driven decision-making (DDDM) is crucial for guiding effective actions. DDDM involves using data to identify trends, opportunities, and actionable insights.

In a smart sales project, BI tools can be used to analyze sales data, product performance, and customer behavior to uncover insights and inform business decisions.

This repository contains examples of data-driven goals that could be achieved using BI in a smart sales project. Decision-makers might want to:

  • Identify top-selling products to influence production and marketing efforts.
  • Analyze customer demographics to improve targeted marketing campaigns.
  • Evaluate promotion effectiveness by region or product to improve future campaigns.
  • Identify low-performing products to consider discontinuation or repositioning strategies.
  • Analyze seasonal sales trends to better manage inventory and staffing.
  • Examine customer purchasing patterns to optimize loyalty programs or upsell opportunities.

Value

Our real value as BI analysts is to get value. Focus on understanding the most critical drivers and what data will be needed. This is the hardest part to teach, but arguably the most important. If we can define it well enough, it becomes easier to get the information needed.

Always have the business goal in mind when working on a project.

Difficulty

Some insights are relatively straightforward. Start with Level 1 goals. As proficiency increases, consider trying some Level 2 or higher goals.

Examples

These are just examples. You are encouraged to use a similar process to define unique goals and plan the associated analysis.

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