AI Modeling and Forecasting
Our pricing modeling and forecasting module offers advanced features for analyzing historical data in real time, and for creating forecasting models based on this data.
Trends and Patterns Analysis
The pricing forecasting and modeling module allows you to analyze trends and patterns in historical data, whether sales, prices, promotions, etc. It therefore allows detect seasonal variations, product launch effects. But also special events and other factors that may influence sales performance.
Demand Forecasting
Using historical data and forecast models, the module helps estimate future demand for different products or product categories. This helps you to anticipate fluctuations in demand and adjust stock levels. But also to make informed pricing decisions to maximize their sales.
Automatic selection of the best statistical model
The pricing forecasting and modeling module automatically identifies the best statistical model to apply based on your data. Additionally, the module takes into account criteria such as history duration (generally 3 years are required for optimal accuracy), seasonality detection and trend detection. This therefore ensures that the selected model is the most suitable for forecasting future sales.
8 implemented statistical models
The sales forecasting module offers a range of 8 predefined statistical models.
These models include methods such as linear regression, time series, Holt-Winters, ARIMA models and more.
Each model has its own advantages and adaptability to different types of data.
So users can choose the model that best suits their specific needs.
Application of the optimal model for product-store analysis
Simulation of pricing scenarios
Simulate different pricing scenarios using predictive models and test the impact of different pricing strategies on your sales. But also on your profit margins and your competitive positioning. This enables you to make informed pricing decisions and optimize profitability.
Identification of opportunities and risks
Thanks to data analysis and forecasts, the pricing modeling and forecasting module makes it possible to identify potential opportunities and risks linked to the pricing strategy. It can highlight products or product categories with high growth potential. As well as those that might require price adjustments to improve their performance.
AI-based models
Our solution offers models based on artificial intelligence to improve the accuracy of your pricing decisions. Additionally, these models use advanced algorithms to analyze historical data in real time, identifying patterns and trends that can influence optimal pricing.
Configuration accessible to Data Analysts
We offer intuitive setup allowing Data Analysts to customize models based on the specific needs of your business and market. Adjust parameters, constraints and variables to create forecasting and pricing models tailored to your business strategy.
Iterative simulation and version traceability
Price elasticity measurement and sales forecasting
Our solution includes built-in models to measure the price elasticity of demand, helping you to understand how price variations can influence sales volumes.
In addition, our forecasting system allows us to estimate future sales volumes based on planned prices.
- Consideration of all price variations and adjusted sales
- Normalization
- Development of linear regression models
- Determination of Elasticity Coefficients
- Management of new items and store openings
- Management of replaced/replacement products
- Reliability measurement(RMSE)
Analysis and prevention of cannibalization
We offer forecasting and pricing modeling models that analyze and prevent cannibalization between different types of brands.
So optimize your product assortment by avoiding pricing conflicts that could reduce your profit margins.
Automatic price determination
Our pricing forecasting and modeling solution uses constrained reasoning models to automatically determine optimal prices while taking into account various requirements such as target margins, profitability objectives and competitive constraints.
Estimation of the number of price ranking
Additionally, we provide models that estimate the optimal number of tariff ranks needed for each product category.
This allows you to effectively adjust your pricing strategy according to the specific characteristics of each category.
Price change
Finally, our solution uses optimization models to determine the optimal number of price changes.
This therefore helps you avoid excessive price changes, while allowing you to optimize your margins and competitiveness.
Customer testimonials
« Optimix XPA is a very interesting tool. It has already allowed me to identify and correct pricing anomalies shortly after taking over my new store in Nice. I have just discovered that I can automate the generation of my analysis projects. I can't wait to use it for my other local stores. »
« Optimix is a highly effective pricing tool that enables us to adapt our pricing to our competitive context and margin objectives. Optimix offers the option to work at the item, category, or even based on national top sales, either individually or simultaneously, as well as on private label products, national brands, and regional products. »
« The Optimix Pricing XPA solution enables us to track the daily fluctuations in internal purchase prices as well as our competitors' selling prices so we can swiftly adapt our pricing strategy to ensure we achieve our desired margin or gain a competitive edge in the market. »
*6 months after deployment in 45 stores.
They trust us
FAQ Modeling and Forecasting
FAQ 1 : What statistical models and AI algorithms do you integrate into your solutions?
Our statistical sales forecasting models are mainly based on the “best fit” method, which will select the most relevant model to calculate future sales of your products.
To go further, we have strengthened our AI algorithms using neural networks, in order to generate price elasticity and cannibalization calculations, based on numerous exogenous factors.
FAQ 2: What distinguishes your forecasting and pricing modeling module from other solutions on the market?
Our XPA pricing forecasting and modeling module is specifically designed for the retail sector. It incorporates advanced features that analyze historical data in real time and use this data to create forecasting models.
Using AI, our solution automatically selects the best statistical model based on your data, ensuring optimal accuracy. What’s more, we offer a range of 8 predefined statistical models, enabling retailers to choose the one best suited to their needs.
Trend analysis, pricing scenario simulation, and cannibalization prevention are some of the many features that make our solution unique.
FAQ 3 : What is the source of historical data used by XPA for modeling and forecasting?
XPA uses historical data supplied by retailers. This data may include information on sales, prices, promotions and other relevant variables.
Real-time analysis of this data enables XPA to create forecasting models based on historical trends and patterns. It is crucial for retailers to provide complete and accurate data to ensure effective forecasting.
FAQ 4: How does this XPA module compare to other forecasting tools on the market?
XPA stands out for its ability to automatically select the most appropriate statistical model based on the data provided. With a range of 8 predefined statistical models, the module is designed to adapt to different types of data.
What’s more, XPA uses artificial intelligence to improve the accuracy of pricing decisions, offering greater adaptability and precision than other tools.
FAQ 5: How does XPA help prevent cannibalization between products?
XPA offers forecasting and pricing models that actively analyze and prevent cannibalization between different brands or products.
By identifying potential pricing conflicts that could reduce your profit margins, XPA allows you to optimize your product assortment and avoid internal competition issues.
