Managing stock effectively is one of the key factors in maximizing your business goals. With our new Stock Clearance Strategy in Omnia 2.0, you now have a powerful tool designed to guide your products toward being sold out by a specific date while also optimizing pricing for profitability along the way.
This new goal-based strategy automatically adjusts the prices to clear stock. All you need to do is define a time frame and your desired target stock level.
Why Use the Stock Clearance Strategy?
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Avoid overstock: Prevent products from remaining in your inventory for too long, especially seasonal or perishable goods, and free up storage space for new items. Improve margins: Our algorithm doesn’t just clear stock, it balances your clearance goals with price optimization, helping you retain healthy margins. Save time: Configuring complex pricing rules, or even manually adjusting prices and monitoring inventory can be time-consuming. Our automated approach keeps you on track without manual intervention. |
How does it work?
The Stock Clearance Strategy in Omnia 2.0 uses a time-series based predictive pricing model with elements of statistical analysis and market-aware dynamic pricing.
- Analyze Sales and Stock Level
The algorithm first analyzes the recent sales history (last 30 days) and current stock levels to assess the current sales pace. It avoids overreacting to individual sales events, focusing on overall trends rather than outliers. - Project Sales Trends
Using time-series analysis, the algorithm forecasts future sales, with more weight on recent events. This projection determines if the current sales rate aligns with the stock clearance target. - Calculate Price Adjustments
The algorithm calculates price changes based on the gap between the current and target sales rates. It adjusts prices to close this gap, balancing stock clearance goals with margin preservation. - Compare Market Prices
A competitive market position is key: better pricing leads to higher visibility and faster sales velocity. The strategy evaluates your pricing relative to competitors and factors this into the price adjustment. - Dynamic Price Adjustment
All data from previous steps are considered to determine the final price adjustment. Each day, the algorithm makes a single, controlled adjustment, capped at a maximum of 5% per day.
Key Features
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Goal-Driven Price Adjustments |
You define a target stock level and time range. The algorithm monitors sales and adjusts pricing to help stock be cleared by the end date. |
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Market-Aware Pricing |
Our model takes both sales data and market position into account. The better your price position, the higher your sales. |
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Works with Limited Sales Data |
We only require 30 days of sales data to start calculating recommendations. |
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Handles No Sales/Market Data |
Even with no sales or limited market data, the algorithm can provide reasonable price recommendations. |
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Price Stability with Safety Nets |
Daily price changes are capped at 5%, ensuring stability while allowing necessary adjustments. The configured safety rules within the pricing strategy tree are always considered. |
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Adaptable to Changing Conditions |
The algorithm adapts to changing conditions, such as stock replenishment or market shifts, recalibrating to maintain progress toward your stock clearance goal. |
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Seamless Integration |
This strategy integrates effortlessly into your existing pricing strategy tree within Omnia 2.0, including any predefined safety rules. |
Rigorous Testing & Simulations
We understand the importance of reliability, which is why we have run extensive simulations to ensure the strategy works across a wide range of scenarios, including:
- Varying sales curves
- Presence or absence of market data
- Stock replenishment
- Markets with up to 100+ competitors
- Stock clearance goals that are difficult, impossible or too easy to achieve
- Randomness in sales patterns and sporadic sales events
- Fluctuating price ranges
Requirements & Limitations
Mandatory Requirements
- Stock Levels:
- Must be imported into Omnia 2.0 via the mapped field/tag “Amount In Stock”
- Must be portal-specific: stock levels are for the specific shop and country that match the portal and not total stock level for e.g. multiple countries/shops.
- Sales Data:
- Must be imported into Omnia 2.0 via the mapped field/tag “Units Sold Total Yesterday”
- Minimum of 30 days of sales data.
- Must be portal-specific: sales are for the specific shop and country that match the portal and not total units sold for e.g. multiple countries/shops.
- Must be accurate and up-to-date.
- Price Elasticity: There must be a relationship between price changes and sales (i.e., lowering the price should increase sales).
Recommendations
- Safety Rules: The more room the algorithm has to operate, the better. However, you should still provide reasonable min/max safety rules to prevent undesired price changes.
- Selling Price: The starting selling price doesn’t need to be optimal, but a more reasonable price helps the algorithm find the optimal price faster.
- Stock Clearance Time Range: At least 1 month is recommended, depending on the sales rate.
Limitations
Within the first version of the closed beta there are still some limitations to be aware off:
- Seasonality / pattern recognition not yet included. The initial version is aimed for products or time periods with relatively stable demand and cannot predict a sudden large ramp-up/down in demand yet. It is therefore not yet suited to run the full season of a particular product (including the season demand ramp up), but is suited to run the end-of-season clearance.
- No cross-channel optimization: the beta version will optimize for one sales channel and cannot optimize yet across sales channels (E.g. make tradeoffs between countries).
- Short timeframes not fully supported (only 1 price change a day)
Configuration
Target Level:
Define the target stock level you aim to reach by the end of the stock clearance period. There are two options: It can be a fixed number (zero or positive integer), in which case it applies to all products in the strategy branch. Alternatively, it can be selected from tags or defined by a formula, which allows you to set product-specific target stock levels., Once the target stock level is reached, no further price recommendations are calculated.
End of Season – Start/End Date:
Set the start and end dates for the stock clearance period. Dates can be manually entered or selected from tags, allowing for product-specific timelines. If dates come from tags, they must conform to the ISO 8601 date format.
An example for an ISO 8601 date would be ”2024-09-05T08:59:59.000Z”. Our repricing engine supports all official variants of this date format
Resume After End Date:
If enabled, price recommendations continue after the end date, but prices quickly approach the minimum price set by safety rules.
Beta Phase
The Stock Clearance Strategy is currently in a closed beta and will be soon available for broader use. If you’re interested in joining, please contact us. By opting in, you’ll be among the first to experience our goal-based pricing strategy and have the opportunity to provide valuable feedback as we finalize its features.
Q&A
How does the strategy handle stock replenishment during the clearance period?
If stock is replenished during the clearance period, the algorithm automatically recalibrates to account for the new stock level. It will make more aggressive price recommendations (within safety limits) to accelerate sales, adjusting prices daily based on the remaining time frame.
Is there a minimum or maximum time range for the stock clearance period?
While there’s no strict minimum, we recommend a stock clearance period of at least one month for optimal performance. Shorter periods may not allow sufficient time for price adjustments to take full effect, depending on the sales rate. There is no maximum time limit.
How can I monitor the strategy's progress?
You can track the strategy’s progress on the Price Recommendations Page in Omnia 2.0. Filter by the Stock Clearance Strategy to see the price history through the “Avg. difference to benchmark” graph. You can also view current price recommendations and stock levels in the table at the lower part of the Price Recommendation page. For detailed product-level price curves, visit the product details page. We are also developing tools to better visualize the progress of the goal-based strategy.
Are daily, weekly, or any other recurring sales patterns considered?
Not yet.
My products are located in a central warehouse and distributed to different markets. Does the Stock Clearance Strategy account for that?
Currently, the strategy does not support this scenario. However, please contact us to discuss your use case, as there may be potential workarounds.