Product Sales Analytics

Data Science

Analytics

Sales trend analysis and forecasting pipeline.

Overview

This project analyses product-level sales data to identify [TRENDS / SEASONALITY / ANOMALIES] and build a forecasting pipeline for [REVENUE / UNITS SOLD] over [TIME HORIZON].

Methodology

Exploratory analysis — sales trends by [product / region / channel], seasonal decomposition
Forecasting — [ARIMA / Prophet / regression-based] model for [METRIC] over [N]-period horizon
Evaluation — [MAE / RMSE / MAPE] on held-out test period

Key Findings

[KEY FINDING — e.g. “The forecasting model achieves [MAPE VALUE]% on the test period. [PRODUCT CATEGORY] shows strongest seasonality, peaking in [MONTH].”]

[Finding 1]
[Finding 2]
[Finding 3]

Code

Python Notebook

---
title: "Product Sales Analytics"
description: "Sales trend analysis and forecasting pipeline."
categories: [Data Science, Analytics]
---

## Overview

This project analyses product-level sales data to identify
[TRENDS / SEASONALITY / ANOMALIES] and build a forecasting
pipeline for [REVENUE / UNITS SOLD] over [TIME HORIZON].

## Methodology

- **Exploratory analysis** — sales trends by [product / region /
  channel], seasonal decomposition
- **Forecasting** — [ARIMA / Prophet / regression-based] model
  for [METRIC] over [N]-period horizon
- **Evaluation** — [MAE / RMSE / MAPE] on held-out test period

## Key Findings

::: {.result-box}
[KEY FINDING — e.g. "The forecasting model achieves [MAPE VALUE]%
on the test period. [PRODUCT CATEGORY] shows strongest seasonality,
peaking in [MONTH]."]
:::

- [Finding 1]
- [Finding 2]
- [Finding 3]

## Code

[Python Notebook](https://github.com/tkay305/Retail-Projects/blob/main/product_sales_analytics.ipynb)