Demand Forecasting That Works: 88% Accuracy, $142M Saved, Stockouts Cut

AI Forecasting That Saved $142M for Global Retailer

Considering each outlet's specifics, we built the AI demand forecasting solution and optimized the volume of goods in the warehouse and the range of goods in different locations. We set up a system that has processed over 8 TB of sales data. These have helped the retail business increase revenue, improve logistics planning, and achieve other business goals.

Data Insights & Forecasting

Data Science

Retail

Data Insights & Forecasting

Data Science

Retail

forecasting accuracy

0.9

out-of-stock reduced

About the client

The retail trading company focused on producing luxury goods, available in more than 3,000 stores worldwide.

Tech stack

ReactJS

Django

Pandas

Pyspark

Redis

The client's needs

The global luxury retailer needed to cut inventory costs across their 3,000+ locations without creating stockout situations that would damage their premium brand image. They needed a demand solution forecasting management system that could process their massive sales history (8TB) to predict future demand with enough accuracy to make actionable stocking decisions. Most critically, they needed store-specific assortment planning that respected the unique buying patterns of customers in different geographic markets, rather than a one-size-fits-all forecasting approach.

Challenges & solutions

Challenge

Optimize the volume of goods in the warehouse by location.

Solution

Clustered stores by customer behavior and applied time series models. Upgraded to a neural network with holiday, weather, and economic inputs for dynamic regional forecasts.

Challenge

Optimize the assortment of goods in various locations.

Solution

Processed 8TB of sales data to build a model recommending SKU-level assortments per store, based on demand patterns and inventory turnover.

Challenge

Build a demand forecasting solution.

Solution

Created a hybrid LSTM + regression model with 88% accuracy. System re-trains on new data, adjusts forecasts, and updates safety stock levels automatically.

Challenge

Solution

Challenge

Solution

Challenge

Solution

Challenge

Solution

Challenge

Solution

Luxury Retailer AI Demand Forecasting Implementation

Results

Business Impact

$142 million saved by reducing excess inventory across the global supply chain.
Stockouts decreased from 4% to 0.9%, improving product availability and customer satisfaction.
Inventory residues reduced by 19%, freeing up warehouse space and reducing waste.

Forecasting Accuracy & System Performance

Achieved 88% forecasting accuracy, significantly improving planning reliability.
The system processed eight terabytes of sales data across 3,000+ stores.
Adjusted forecasts dynamically by factoring in each country's holidays, weather, and economic indicators.

Operational Improvements

Optimized warehouse stock levels per location using store clustering based on customer behavior.
Customized product assortment for each outlet, increasing alignment with local demand.
Enhanced logistics planning and distribution efficiency.

Client Outcomes

Improved revenue and customer experience through better stock availability.
Increased supply chain agility through dynamic, data-informed decisions.
Strengthened long-term decision-making capabilities via a flexible, interpretable AI demand forecasting solution.

I think what is really special about the DATAFOREST service is its flexibility, openness, and level of quality and expertise.

Andrew M.

CEO Luxury Goods Retail

The Way We Deal with Your Task and Help Achieve Results

Step 1 of 5

Web development discovery

It's a good time to get info about each other, share values, and discuss your project in detail. We will advise you on a solution and help you understand if we are a perfect match for you.

Step 2 of 5

Discovering And Feasibility Analysis

One of our core values is flexibility. Hence, we work with either one-page high-level requirements or a whole pack of tech docs. In AI demand forecasting case studies, there are numerous models and approaches, so at this stage, we perform a set of interviews to define project objectives. We elaborate and discuss a set of hypotheses and assumptions. We create a solution architecture, a project plan, and a list of insights or features to achieve.

Step 3 of 5

Solution Development

The work starts with data gathering, data cleaning, and analysis. Feature engineering helps to determine your target variable and build several models for the initial review. Further modeling requires validating results and selecting models for further development. Ultimately, we interpret the results. Nevertheless, demand forecasting solution modeling is a process requiring many back-and-forth iterations. We are result-focused, as it's also one of our core values.

Step 4 of 5

Solution Delivery

AI demand forecasting solutions can be a list of insights or models that consume data and return results. Though we have over 15 years of expertise in data engineering, we expect the client's participation in the project. While modeling, we provide midterm results so you can always see where we are and provide us with feedback. By the way, a high level of communication is also our core value.

Step 5 of 5

Support And Continuous Improvement

We understand how crucial the solutions that we code for our clients are! We aim to build long-term relations, providing guarantees and supporting agreements. Moreover, we are always happy to assist with further developments, and statistics show that 97% of our clients return to us with new projects.

Success stories

Check out a few case studies that show why DATAFOREST will meet your business needs.

All Success Stories

Supply chain dashboard

The client needed to optimize the work of employees by building a data source integration and reporting system to use at different management levels. Ultimately, we developed a system that unifies relevant data from all sources and stores them in a structured form, which saves more than 900 hours of manual work monthly.

900h+

manual work reduced

100+

system integrations

Michelle Nguyen

Senior Supply Chain Transformation Manager Unilever, World’s Largest Consumer Goods Company

View case study

Their technical knowledge and skills offer great advantages. The entire team has been extremely professional.

Performance Measurement

The Retail company struggled with controlling sales and monitoring employees' performance. We implemented a software solution that tracks sales, customer service, and employee performance in real-time. The system also provides recommendations for improvements, helping the company increase profits and improve customer service.

17%

increase in sales

25%

Improvement in Employee KPI Achievement Rate

Amir R.

CEO Fashion Retailer

View case study

They easily understand industry-specific data and KPIs, and their efficiency as a team allows them to deliver results quickly.

Client Identification

The client wanted to provide the highest quality service to its customers. To achieve this, they needed to find the best way to collect information about customer preferences and build an optimal tracking system for customer behavior. To solve this challenge, we built a recommendation and customer behavior tracking system using advanced analytics, Face Recognition, Computer Vision, and AI technologies. This system helped the club staff to build customer loyalty and create a top-notch experience for their customers.

customer retention boost

25%

profit growth

Christopher Loss

CEO Dayrize Co, Restaurant chain

View case study

The team has met all requirements. DATAFOREST produces high-quality deliverables on time and at excellent value.

Stock relocation solution

The client was faced with the challenge of creating an optimal assortment list for more than 2,000 drugstores located in 30 different regions. They turned to us for a solution. We used a mathematical model and AI algorithms that considered location, housing density and proximity to key locations to determine an optimal assortment list for each store. By integrating with POS terminals, we were able to improve sales and help the client to streamline its product offerings.

10%

productivity boost

Mark S.

Partner Pharmacy network

View case study

The team reliably achieves what they promise and does so at a competitive price. Another impressive trait is their ability to prioritize features more critical to the core solution.