How to use quantitative data analysis for ecommerce demand forecasting

[Haidenhibbert]

1. Brainstorm. Think about your goals for your business and the time frame in which you’d like to achieve them, along with the questions you want answers to. These could include:

• How much of each product you’d like to sell.
• If and how demand for each product line will change.
• Any external factors or events that could affect demand.
• How changing consumer needs will affect sales.

2. Get buy-in and alignment from your stakeholders, including your sales team, social media marketers, and company leaders, to avoid unnecessary delays or surprises later.
3. Collect and record historical data and future projections. These should comprise consumer purchase behavior and past customer purchase patterns, ideally from the past 12 months. If you don’t have this much historical data, you could get a third-party quantitative analysis through sources like Google Trends or Amazon Best Sellers.

Metrics should ideally include:

• Order dates,
• Rates of returns,
• Monthly sales averages,
• Moving sales averages, and
• Underlying and seasonal market conditions or trends.

4. Measure, organize, and analyze your data. Here, you’ll analyze your data to find trends and patterns to draw conclusions from. This can be done manually with an Excel spreadsheet or an ERP system, with the automated help of an AI-driven data analytics platform, or through a data scientist or team.

 Estimate demand and adjust your operations accordingly. Your budgets and revenue will change along with these adjustments so you know what to expect and how to plan when it comes to things such as marketing campaigns, product launches, and inventory management.

[BriCham]

A great tool that can make all of this easier is Cogsy.  Cogsy is an operations platform that helps you do everything you mentioned in your post so you can save time and money. 

Cogsy turns data into actionable insights so you make better decisions around:

Inventory forecasting

Selling on backorder

Growth planning

Optimal purchase orders

Have you tried a tool like this one before?