I can help you manage inventory using sales and demand forecasting

  • 4.3
  • (5)
I can help you manage inventory using sales and demand forecasting
I can help you manage inventory using sales and demand forecasting
I can help you manage inventory using sales and demand forecasting
I can help you manage inventory using sales and demand forecasting
I can help you manage inventory using sales and demand forecasting
I can help you manage inventory using sales and demand forecasting

Project Details

Why Hire Me?

I bring 7+ years of cross-industry experience in data-driven inventory management, with a deep understanding of forecasting methods tailored for e-commerce. My services focus on preventing overstock and stockouts, improving turnover, and aligning inventory with dynamic customer demand.

Why Clients Choose Me:

  • Expertise in sales forecasting, demand prediction, and inventory optimization

  • Proficient in analyzing historical sales data, seasonality, and promotions

  • Skilled in applying models like moving average, regression, exponential smoothing, and ML-based forecasts

  • Capable of developing category-specific inventory strategies, including JIT and EOQ models

  • Delivery includes structured reports, charts, and dashboard-ready outputs

  • Experience across product types: FMCG, fashion, electronics, and niche D2C items


What I Need to Start Your Work

Please provide the following to initiate your inventory forecasting and optimization project:

1) Project Scope and Inventory Management Goals

  • Objective of the project (e.g., reduce holding costs, improve fulfillment rates)

  • Product categories or SKUs to focus on

  • Any known inventory issues or goals (e.g., high stockouts, dead stock)

2) Sales and Demand Data Specifications

  • Historical sales data (format, frequency – daily, weekly, monthly)

  • Inventory logs (stock on hand, stockouts, restock dates)

  • Sales trends during campaigns or seasonal periods

  • Any preprocessing already applied to the dataset

3) Forecasting Methodology

  • Preferred forecasting method (if any): time series, regression, ML-based

  • Software/tool to be used: Excel, R, Python, etc.

  • Any relevant business rules (e.g., buffer stock during sales periods)

4) Inventory Strategy Development

  • Strategy expectations: JIT, EOQ, safety stock levels

  • Input on vendor lead times, MOQ, reorder frequency

  • Approach to handle irregular demand or supply chain disruptions

5) Reporting and Analysis Requirements

  • Format of reports: Excel sheets, PowerPoint decks, PDFs

  • Charts and dashboards: stock projection graphs, reorder schedules

  • Level of detail expected (executive summary vs technical model description)

6) Data Privacy and Ethical Considerations

  • Any NDA or legal requirements

  • Compliance with internal data governance or external regulations

7) Project Timeline and Milestones

  • Final delivery date

  • Review points or intermediate deliveries (e.g., model validation)

  • Urgency or time-sensitive targets (e.g., festive season planning)

8) Communication and Collaboration

  • Preferred channels (Zoom, WhatsApp, Email)

  • Review meeting frequency

  • File sharing protocols (Google Drive, Dropbox, etc.)

9) Additional Requirements or Preferences

  • Any competitive benchmarks to match

  • Past reports, templates, or examples (if any)

  • Other special instructions relevant to your e-commerce vertical

Portfolio

Seasonal Sales Forecasting for Apparel Inventory Optimization

Learn how an online fashion store used time series forecasting and EOQ models to reduce stockouts and overstock. A case study in inventory optimization using Python and Excel for seasonal apparel management.

Machine Learning Forecasting for Grocery Inventory Optimization

See how a grocery chain used Random Forest and XGBoost to improve sales forecasting and reduce waste. A case study in machine learning–driven inventory management for perishables and fast-moving SKUs.

Festive Demand Forecasting for Home Appliance Retail

Discover how a home appliance retailer used ARIMAX and regression models to forecast festive demand and reduce stockouts. A data-driven case study in inventory planning for seasonal sales campaigns.

Process

Customer Reviews

5 reviews for this Gig ★★★★☆ 4.3

5 Stars
(1)
4 Stars
(4)
3 Stars
(0)
2 Stars
(0)
1 Stars
(0)
Rating Breakdown
  • Seller communication level ★ 4.4
  • Recommend to a friend ★ 4.2
  • Service as described ★ 4.2

🇲🇽
Maria Gonzales
4.3 5 July 2025

I run a boutique with lots of SKUs and tracking demand was a headache. He simplified the data and showed me which items were consistently underperforming and what to restock. Now my cash isn’t stuck in the wrong products anymore.



🇺🇸
Ahmed El-Khatib
4.7 5 July 2025

My online store used to run out of bestsellers randomly. His model helped us see the patterns hidden in the past orders and seasonality. Since implementing his suggestions, our sales fulfillment rate has improved a lot.



🇺🇸
Lana Smith
4 5 July 2025

He delivered a decent forecast but the format of the report was a bit plain for my team to understand. Still, the reorder suggestions based on demand trends were accurate and saved us a lot. Would definitely recommend but ask for more visual dashboards.



🇮🇹
Jonas Eriksson
4 5 July 2025

We had no idea how much we were overbuying until we saw his demand prediction charts. The weekly forecasting model helped us reduce wastage by almost 20 percent. Wish I had taken this service earlier during Q4 rush.



🇮🇳
Priya Mehta
4.3 5 July 2025

I was always struggling with dead stock and last-minute stockouts during sales. After working with him, my inventory turnover improved drastically. His forecast was so close to our actual demand that we didn’t over-order for the first time in 2 years.


Doesn’t matter you are a company or a student!

Frequently Asked Questions

I will give you the price after checking the project details.

It will be given after discussion by looking at the complexity of the task and our mutual understanding.

You can trust me because I have been working as a data analyst from past 7 years and have worked on projects across multiple industries.

Refund will be discussed after our mutual discussion and complexity of task. If I completely fail to deliver the task, I will refund 100% of the amount.

50% will be in advance and 50% after the delivery of complete task. This is negotiable and can be discussed and finalized after our discussion.

Data confidentiality is paramount. I adhere to strict data security protocols and ensure that all client information is handled with the utmost discretion and security.

Yes, I have experience across various industries and can tailor my approach to meet the specific needs and nuances of your sector.

I use a variety of methods including time series analysis, regression models, and machine learning techniques, tailored to your specific business context and data availability.

Absolutely, I specialize in customizing forecasting models to various industries and product types, ensuring the forecasts are relevant and actionable for your specific business.

I strike a balance between accuracy and practicality by choosing appropriate models that provide reliable forecasts while being feasible to implement in real-world business scenarios.

By providing accurate sales and demand forecasts, I can help you optimize inventory levels, reducing holding costs and minimizing the risk of stockouts or overstock situations.
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