AI-driven Forecasting

How you can make better and faster decisions with AI-based Forecasting

AI-based forecasting can be a game-changer for small business, providing insights and automation that can improve inventory management, customer satisfaction, and overall business operations. In this article we describe not the upsides of this technology, but also look at why not everybody is keen on embracing it.

Running an online business can be challenging.

And it isn’t made any easier by the fact that there are tons of platforms and tools out there that claim to help you with your business.

But can AI actually help independent retailers or is it just a hype?

While we believe the short answer is yes, it can help, we also want to approach it with a balanced perspective, recognising not only the potential but also considering its limitations and concerns.

Artificial Intelligence, human interpretation

The past decade has seen remarkable advancements in AI and machine learning, with the development of more powerful algorithms, increased computational power, and larger datasets.

These advancements have enabled AI to achieve impressive results in various applications, from natural language processing to image recognition.

AI and machine learning are no longer confined to research labs — they are being used to solve real-world problems and drive business outcomes. Companies across industries are adopting AI for automation, analytics, customer service, personalized marketing, and more, leading to tangible benefits like cost reduction, increased efficiency, and improved customer experiences.

How can AI help me run my business?

Most of today’s demand and sales forecasting tools can already provide you with valuable insights from both online and offline data, so why would you need AI or machine learning?

AI-based forecasting is designed to be more agile and responsive, incorporating up-to-date information on factors like changes in consumer behavior, weather patterns, and economic conditions.

Demand sensing helps organizations better understand and anticipate customer behavior and demand for their products and services. And this means, with demand sensing analytics, organizations can identify and act on insights to improve customer service and optimize pricing, and promotions.

Additionally, demand sensing can help your business to stay ahead of competition by predicting market trends and adjusting your sourcing or product development accordingly. It can also help you lower costs by reducing inventory, avoiding stock-outs, and minimising costly markdowns.

1. Short Term and Mid Term demand accuracy

Demand sensing can improve short-term and mid-term demand accuracy by providing real-time insights into consumer behavior

By using real-time data and advanced analytical techniques, you can make more accurate predictions of future demand, which can be crucial in optimising your sourcing, buying and meeting your customer’s need.

2. Last Mile delivery and Stock-outs

Demand sensing can also help companies avoid stock-outs and optimise last-mile delivery. By predicting demand for specific products, you can ensure that they have the necessary inventory on hand to meet customer demand.

In addition, by using real-time data on traffic, weather, and other external factors, you can optimise delivery routes and schedules to ensure timely delivery.

3. e-commerce benefits

Demand sensing can also be incorporated into e-commerce stores to improve pricing techniques and ad optimisation.

By analysing real-time data on consumer behaviour, companies can optimise pricing strategies and targeted advertising to increase sales and customer satisfaction.

4. Seasonal events

Demand sensing can be particularly useful for events such as Halloween or Black Friday sales. By analyzing historical sales data and external demand signals, companies can accurately predict demand for specific products and adjust inventory levels accordingly.

This can help you to avoid stock-outs during these high-demand periods and ensure that customers have access to products.

5. Impact on sales and bottom line

Demand sensing can provide granular insights into sales activities, engagement, and delivery status. By monitoring late deliveries and comparing pending deliveries with current stock, companies can optimize inventory levels and reduce stockouts.

AI-based forecasting can also identify trends in customer purchases, helping you as a retailer design targeted marketing campaigns and promotions.

Additionally, by gaining insights into accounts receivable and sales outstanding values, you can improve cash flow and minimise financial risk.

AI-based forecasting by Shelf Planner

With Shelf Planner’s AI-driven inventory management, you can pick up on short-term trends and market shifts immediately to better predict what consumers want, and when, and where they want it.

Our solution allows you to create multiple demand models with as much granular detail as you like.

Shelf Planner works with hundreds of retailers in all kinds of industries. Our demand sensing software approach excels in providing businesses with actionable insights, allows easy collaboration, and leverages built-in models.

Of course we also appreciate the concerns you might have regarding this new technology.

To be honest, when we built the first prototype of my.shelfplanner we were skeptical about the accuracy and reliability of AI-based forecasting, fearing that incorrect predictions could lead to incorrect order proposals and wrong recommendations.

But soon enough, we realized we could use the machine learning techniques to improve our more classical forecasting logics, almost working in tandem.