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On this page you will learn about all the metrics and KPIs available in Delicious Data. We explain how each metric is calculated and what insights it can provide for your business. By the end, you’ll understand which metrics to use for different business questions and how to interpret them correctly.

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Units

For currency based metrics (Revenue, Delivery value, etc.), the currency is defined in the global settings and applies company wide to all locations. For count based metrics (Sales No., Order amount, etc.), the unit is the same as in the source system. For example:
  • If the item is sold in pieces and Sales No. = 12.0 then 12 pieces were sold.
  • If the item is sold in kg and Sales No. = 3.2 then 3.2 kg were sold.
Sometimes integration specific unit conversions are necessary. Check out our integration documentation for more details on your integration.

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Transactional vs. Aggregated Sales Data

There are two ways we can process sales data:
  1. Daily Aggregated: Summary of your daily totals per item and location
  2. Transactional: Detailed data for every single sale including time, items and locations
Most features work fine with aggregated data, but processing transactional data allows us to generate more powerful insights and metrics in your BI dashboard.
Check out our integration documentation to see if your ERP system offers transactional data or if an additional POS integration would be required.

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Sales Metrics

All metrics related to sales coming either from the POS or the ERP. Sales metrics can be grouped & filtered by Location, Location-Tag,Item, Item Groups, Item-Tag, Time (down to hourly level for transactional data, otherwise daily).
The total gross revenue generated from sales.
The total number of items sold.
The average price per item sold.
It is calculated on the fly for the chosen aggregation level in the report and does not reflect a reference or valuation price of the item:Ø Price = Total Revenue / Total Sales No.
The total number of transactions processed.When filtering or grouping by Item, Item Groups or Item-Tag this metric will only reflect the number of transactions which included the respective items.
This metric is only available with transactional data.
The average revenue generated per customer transaction.When filtering or grouping by Item, Item Groups or Item-Tag this metric will only reflect the average revenue per transaction of transactions which included the respective items.
This metric is only available with transactional data.

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Order Metrics

All metrics related to orders and deliveries. Order metrics can be grouped & filtered by Location, Location-Tag, Item, Item Groups, Item-Tag, Time (daily level only).
The total quantity of items ordered.
The total value of all ordered items.
The total quantity of items that were delivered to customers.
The monetary value of all delivered items.
The suggested order quantity based on our prediction algorithms.
This metric is only available when using the order automation feature.
The monetary value of all proposed amounts from our prediction algorithm.
This metric is only available when using the order automation feature.
For the “value” metrics typically a reference or valuation price is used from the ERP system, but sometimes the average price is also used. Check out our integration documentation to see which case applies to you.

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Returns and Depreciation Metrics

All metrics related to returns, write-offs and depreciation. Returns and depreciation metrics can be grouped & filtered by Location, Location-Tag, Item, Item Groups, Item-Tag, Time (daily level only).
The quantity of items that were marked as depreciated or written off.
The monetary value of all depreciated items.
The quantity of items that were returned.
The monetary value of all returned items.
Depending on the configuration this is the percentage of items that were returned relative to
  • total delivered items or
  • the total sold items.
This is the return amount rate weighted by the value of the items.
This metric is recommended over the return amount rate as it weighs expensive items more heavily than cheap items when aggregating over different items.
For the “value” metrics typically a reference or valuation price is used from the ERP system, but sometimes the average price is also used. Check out our integration documentation to see which case applies to you.

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✨ AI Metrics

Our AI algorithms provide valuable insights into your business by analyzing sales patterns, returns data, and other factors. These metrics can help you identify trends, optimize inventory, and make data-driven decisions.

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Lost Revenue Potential due to Stock Outs

By analyzing out of stock data and hourly sales patterns we can estimate the potential sales that could have been made if there hadn’t been a stockout. Revenue potential based metrics can be grouped & filtered by Location, Location-Tag, Item, Item Groups, Item-Tag, Time (down to hourly level for transactional data, otherwise daily).
Shows the percentage of items that were available until the closing of the store. In other words this is the inverse of the stock out rate. This is a daily not hourly metric.
This metric currently only works properly for single day items. If there are returns, then the item is considered available, if there were no returns, then the item is considered stocked out. Items that never have returns are considered available.
The estimated number of total items that could have been sold (based on historical hourly purchase patterns) if a stock out hadn’t occured.If an item doesn’t have a long enough history the AI relies more on average sales patterns than item specific sales patterns.
This metric is only available with transactional data.
The estimated total revenue that could have been generated (based on historical hourly purchase patterns) if a stock out hadn’t occured.If an item doesn’t have a long enough history the AI relies more on average sales patterns than item specific sales patterns.
This metric is only available with transactional data.
The number of potential sales that were missed due to stock outs. In principle this is simply Sales Potential - Sales No..
This metric is only available with transactional data.
The monetary value of missed sales opportunities, calculated from lost sales potential and average prices. In principle this is simply Revenue Potential - Revenue.
This metric is only available with transactional data.
Learn more about how we calculate lost revenue potential and how you can finetune it to your business:

Deep Dive: Lost Revenue Potential

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Net Flow Analysis

By analyzing the net flow of items we can detect if stores are systematically overstocked or if there are unexplained outflows of inventory occuring. Net flow metrics can be grouped & filtered by Location, Location-Tag, Item, Item Groups, Item-Tag, Time (daily level only).
The difference between incoming and outgoing quantities per delivered item.Interpreting net flow:
  • If every delivered amount is typically leaving the store again in some explained way (sales, returns, etc.) then the net flow is typically 0.
  • If the net flow is systematically more than 0 it means there is more inflow than outflow. Reasons for this could be that there are recipes missing that connect ordered to sold items, or that items leave the store in an undocumented way.
  • If the net flow is systematically less than 0 it means there is more outflow than inflow. Reasons for this could be that recipes are faulty or not followed in the store.
It is recommended to compare the net flow for specific items between different locations to better understand if there are systematic issues with the data or location specific problems.
The percentage representation of the net flow relative to total delivered quantities.
Learn more about how to use net flow anaylsis and it’s uses cases:

Deep Dive: Net Flow Analysis