Customer Buying Habits App

Customer Buying Habits – Power BI App Overview

In today’s competitive sales landscape, understanding how and when customers make purchasing decisions is essential to driving revenue growth and retention. The Customer Buying Habits Dashboard provides sales teams and leadership with a clear view of customer purchasing trends—such as frequency, deal size, quoting behavior, and sales cycle length—helping prioritize high-value accounts and refine engagement strategies.

This Power BI app transforms raw sales and quotation logs into actionable intelligence to boost sales timing, segment customers effectively, and reduce churn risk.

🔧 Technical Framework

The dashboard is powered by a single structured table titled Customer Habits, capturing customer-level sales and quoting metrics.

Key Components:

Data Source: Excel sheet or system-exported table with customer sales behavior and quoting records.

Data Preparation: Power Query used to:

Clean dates, text, and numeric fields

Calculate average sales cycle time

Categorize deal sizes and purchase frequency

Enable segment-level aggregations

Data Model Dimensions:

Customer ID

Deal Size Category (Small, Medium, Large)

Purchase Frequency (Monthly, Quarterly, Annually)

Last Purchase Date

Average Sales Cycle (Days)

Open Quote Value

Average Deal Size

Previous Orders

This model supports segmentation, customer targeting, and CRM integration.

🎛️ Interactive Filters

The dashboard includes intuitive slicers to support strategic analysis:

Purchase Frequency Filter: Identify customers with recurring, seasonal, or one-off purchase behavior.

Deal Size Filter: Focus on high-value or high-volume segments.

Filters dynamically update all visuals, enabling smarter sales prioritization and outreach planning.

📊 Dashboard Report Highlights

a. KPI Tiles – Buying Behavior Summary

Top-level metrics to assess customer engagement across the base:

“How Many Customers Prioritize Quality?” – (Logic customizable via behavioral thresholds)

Average Sales Cycle Days – Mean time from quote to deal closure

Total Value of Open Quotes – Quoting pipeline value

b. Customer Behavior Table

Detailed view of each customer’s buying pattern, including:

Deal Size and Frequency

Last Purchase Date

Sales Cycle Length

Open Quote Value

Average Deal Size

Previous Orders

Used to identify churn risks, cross-sell opportunities, or high-priority follow-ups.

This dashboard empowers sales organizations to act on real customer behavior—driving better segmentation, engagement timing, and revenue forecasting through data-backed insights.

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