Retail Sales Analytics: Data-Driven Insights & Strategy

ADM1370_W26_A02_Group#_PPT

Retail Sales Analytics: Insights & Recommendations

Group Members: [Name 1] | [Name 2] | [Name 3] | [Name 4]

ADM1370 – Winter 2026 | Assignment 02

Company Overview

US-Based Retail Company

Sells Products Across Multiple Categories

Operates in Different Regions Across the US

Serves Consumer, Corporate & Home Office Segments

Focus on Sales, Profit & Customer Behavior

Dataset Overview

Multi-Year Transactional Dataset

Used to analyze performance and trends across the US retail landscape

Sales

Profit

Discount

Category & Sub-Category

Region

Customer Segment

Product Performance Overview

Sales vary significantly across sub-categories

A small number of products drive most revenue

Many sub-categories contribute very little

Best & Worst Performing Products

TOP PERFORMERS

LOW PERFORMERS

Revenue is concentrated in a few product groups — low performers have minimal impact.

Sales & Profit Trends Over Time

Strong Q4 Performance

Sales increase steadily over time

Peak performance occurs in November (Q4)

Profit remains much lower than sales

Profit growth does not match sales growth

Customer Segment Profitability

Average Profit per Sale by Region & Segment

Home Office Peaks

Home Office segment has highest profit per sale (273 in South region).

Regional Leader

South region leads in average profit.

Central Lags Behind

Central region performs weakest (208).

Highly Profitable

Home Office customers are more profitable per transaction.

Regional Sales Performance

$0.73M Sales

$0.11M Profit

$0.68M Sales

$0.09M Profit

$0.50M Sales

(low profit)

$0.39M Sales

Some regions are underperforming despite sales — Central region consistently lowest in profit margins.

KPI 1

KPI 1 – Category Performance

Technology

$0.98M

Office Supplies

$0.84M

Furniture

$0.76M

Technology drives the most revenue — Furniture underperforms relative to other categories.

KPI 2

Sales vs. Profit

High Sales ≠ High Profit

Some products have high sales but low profit

Profit does not scale with sales volume

Margins vary significantly across products

Discounts or costs may be too high in some categories

Furniture has highest avg. discount (17%) — linked to low profit margins.

KPI 3

Monthly Sales Trends

Sales increase toward end of year (Q4 peak)

Lowest performance observed mid-year (June–July)

Strong seasonal pattern every year

Business heavily depends on Q4 performance

Seasonality Risk:

Over-reliance on Q4 could be a business vulnerability.

Profitability Trend & Explanation

The Trend

Sales increase over time but profit stays relatively flat

Possible Reasons

High discount usage across categories

Rising operational and shipping costs

Low-margin products dominating sales mix

Additional Data Needed

Detailed discount levels by product

Product cost and COGS data

Marketing spend by category

Dashboard Overview

Category & Sub-Category Analysis

Region Performance View

Time Series Trends

Segment Profitability

Filters available: Region | Segment | Category — enabling drill-down analysis.

Dashboard Link: [Insert URL here]

Key Insights

Technology is the Main Revenue Driver

$0.98M in sales

Home Office Segment is Most Profitable

Highest avg. profit per sale

South Region Performs Best

Highest profit per segment

Sales Peak in Q4

November shows strongest performance

Profit Margins Are Inconsistent

Sales growth outpaces profit growth

14

Recommendations & Conclusion

Focus on High-Margin Segments

prioritize Home Office and Corporate customers

Reduce Discounts on Low-Profit Products

especially in Furniture category

Improve Central Region Performance

targeted sales and marketing initiatives

Invest More in Q4 Campaigns

capitalize on seasonal demand peak

Review Pricing Strategy

align pricing with actual cost and margin data

By acting on these insights, the company can improve profitability and sustain long-term growth.