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AI-driven sales forecasting for fresh

Is fresh a differentiator for your company? Is forecasting sales a challenge? Artificial intelligence enables you to tackle the problem of sales forecasting in the best possible way.

Risky forecasting in Excel

“Tom has been our planner for ten years, he knows how much meat will be sold during the first BBQ weekend.”  

*In year 11, Tom leaves the company

Reliable computing power

200 shops x 200 products x 3 weather variables x 7 weekdays x 4 seasons = 3.360.000 possible combinations. With only three parameters. We calculate many more.

1% better forecasting = 2% decreasing costs

Most food companies work with little or no external information, have difficulties combining parameters such as a promotion, bad weather and a holiday or are unable to pick up on new trends. That is where the added value of artificial intelligence lies.


Using rule-based software to estimate future demand is impossible

Traditional programming is based on hard-coded rules. To forecast demand of fresh, that would mean the impact of all parameters would need a hard-coded rule: if Tuesday + sun + season + … = x impact on sales. That’s impossible to do. That’s why machine learning is the better option. It learns the rules from the data.

Thanks to our SAAS business model, we keep the technology up to date. Updates are simply included in your package.

Power to the people!

Planners need a tool that’s fit for the challenge. No more Excel stress, errors or boring manual tasks. Use our software to better forecast, ease the workload and focus valuable time on valuable tasks. The machine learns from you and you learn from the machine. Win win.

Still a little skeptical? Yes please! Using and relying on technology is part of our product and process.

Is this for you? 

You only need 3 years of historical sales data. Promotional dates are also useful, but not even a must. Accurate fresh food forecasting is more important than ever, so why not give it a try?

Step 1: backtest

We feed the algorithms with 80% of your data and “predict” the remaining 20%. Since the actual sale has already taken place, you have the perfect experiment to see if this could work for you.

Step 2: in parallel

After the backtest, we run our software in parallel to your current forecast. This way you can compare and your employees learn to trust the technology.

Step 3: software-as-a-service

Ready, set? go! We plug our turbo into your current systems. Do you need a dashboard or just the number? We are flexible and start from your needs.

How can we help?  

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We are very online and flexible on location.

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