DataNow - Financial Tie Outs & Reports Overview

Description:
This article outlines the various sales and financial reports available within DataNow, their use cases, and how to apply filters for specific reporting needs. It also explains order states, date filters, reconciliation steps, and upcoming data retention policies.

Table of Contents

• Sales Report Types
• Filter Setup
• Syncing Open Orders
• Reconciling Cart Totals and Payment Transactions in DataNow
• Reconciling DataNow Totals and LTM
• Key Definition Fields
• Historical Data | Data Retention(2025)

Sales Report Types 

Sales Summary

• This report can provide key KPIs while on the go or during an event. See your top selling items and move around staff members to the most popular selling locations, if necessary. 

Operational Sales

• Assist with building recs for each concession location. 
• See the top selling items nearest to whatever storage areas are available on the concourse level for easy restock throughout the night. 
• Visibility into locations with Approved Offline orders. 
• Downloadable Employee Data Table for a streamlined Gratuity payout.

Financial Sales

• Comprehensive report for all financial/payment information. 
• See settlement amounts for each payment type and processor. 
• Downloadable Category Sales report
• Approved Offline order hub
  • See the current status of each order that originated in Approved Offline
  • Approved Offline Failure report displaying payments that failed during order syncing

Settlement by Processor

• This report provides an aggregate view of settled payments by date or date range. Payment Processor can be specified (defaults to Shift4) and is useful when comparing transactions to the payment gateway. 

F&B Sales and Merchandise Sales

• These reports act as an amalgamation of Sales Summary, Operational Sales, and Financial Sales. A one stop shop into all reporting for the period of time you’re looking for. 
• The biggest reports we offer, with more than 20 tiles worth of data. 
• Due to the size, this report becomes less performant if pulling for more than one day’s worth of data.

Marketplace Sales

• For those using our Marketplace and Experiences service, you’ll be able to find all sales information here. 

RvC Items and Orders

• See line by line cart totals for each order. Click on either Orders ID or Confirmation Number to see this order information in Canopy. 

Sales Audit

• See a summary of all sales numbers, and tie out cart totals (line items, tax, and tips) to payments. This report does not include transactional data. 
• This report omits the approved offline state, in lieu of a tile dedicated to Approved Offline orders. If Approved Offline is a state desired in the reporting, it can be added in the Order State filter.
• Useful when pulling sales numbers for multiple days or month/s.

Filter Setup

Filters can be found either at the top or on the right-hand side of the report. Use these filters to refine the data you want to query.

Once you've made your filter selections, click the Refresh button located on the right side of the page to update the data. You’ll notice that the refresh button will turn blue once your filters are set and ready to be applied.

Default Order States in DataNow

The default order states in DataNow are: completed, delivered_without_alcohol, partially_refunded, and refunded. These are set as defaults to prevent any misinterpretation of received funds.

If you wish to include additional order states, you can do so by adjusting the Order State filter. Below is a list of order states along with their definitions. The states we consider completed (bolded in blue) are highlighted for easy reference:

• Approved_offline: An order that was placed while the POS was offline and has since synced with the VenueNext backend. Once it has been approved or declined with the payment processor it would move to either completed or authorization_failed.
• Authorization_failed: Guest tried to make a purchase but the payment processor was unable to authorize their credit card.
• Bumped: Orders that have been placed and are now being processed, i.e. order being prepared.
• Cancelled: Orders that have been cancelled & voided.  A void happens when the order has been refunded before it has been completed.
• Closed_by_admin: Manual status change that can only be done in Canopy.  This state doesn't affect auth or settlement but moves it out of an open state.
• Completed: An order has been completed (i.e. picked up or delivered).  This will then trigger the processor to settle the transaction.
• Completion_pending: An FS or EC order has been closed on the POS, but it in a pre-settlement state that can be reopened (i.e. moved back to tabbed).
• Delivered_without_alcohol: Completed order but the alcohol items have been voided.
• Not_collected: Nobody came to pick up their order, usually does not occur during event, rather occurs post-event.  The payment for the order has also settled.
• Partially_refunded: Order is partially refunded after the order was completed.
• Problem_reported: Something went wrong in the order.
• Processing: Order has been accepted, pre-bumped, order has gone through and payment has been accepted, isn't being prepared yet
• Refund_failed: Indicates a failed refund after the order was completed.
• Refunded: Successful refund after the order was completed.
• Settlement_failed: Settlement fails after the order is completed
• Submitted: The card reader has been activated to accept a card for a POS order. The order will remain in this state if there is an interruption during the payment process prior to capturing payment details, most commonly due to a device reboot. Orders in this state should be omitted from reports for reconciliation purposes. 
• Submission_failed: During a POS order, the card reader returned an error OR the user tapped the Back button after activating the card reader. Orders in this state should be omitted from reports for reconciliation purposes. The guest’s card has not been charged for these transactions.
• Tabbed: An order is created and still open.  The payment is authorized but has not been submitted for settlement yet.

Different Date Filters in DataNow

• Effective Business Date: This date reflects when an order was taken on the device. If this date is NULL or if it occurs after the Calendar Date, the field defaults to the Calendar Date.
  • If the device’s date and time occur after the Calendar Date it could be due to incorrect configuration of the device’s date time settings. 
• Calendar Date and Created Date: This is the timestamp of when an order was created on the platform. It’s typically used in sales reports because it offers better performance and represents the actual time an order synced to the system as opposed to when it was created on the device. 
• Updated Date: This timestamp represents when the order was last updated. (typical with order state changes).
• Business Date: This date represents when the order was recorded in the system, based on the revenue center’s defined business end time. Regardless of the specific time it was placed.

While Calendar Date is the standard for sales reports due to performance considerations, the Effective Business Date is more precise in reflecting the moment an order was captured on a device. For example, the Settlement by Processor report uses the Effective Business Date to provide a closer match with external systems, such as LTM, which more reliably tracks when orders were created on the device.

Syncing Open Orders

DataNow has a report titled Device Monitoring, which will display any devices and their location with approved offline or completion pending orders on them. It is imperative that these devices are synced and closed out as soon as possible after an event, ideally the night of. Letting these orders sit on a device could lead to those orders never syncing and a potential loss of revenue.

• It is highly recommended to schedule a recurring report to see these open orders. Please note the Calendar Date filter is reflective of the date an order was created, thus it will not show all open orders, only the ones that the date filter is set to.
• If you would like to see a detailed look on these orders, you can either click the orders or gross sales totals and dive into a transactional report. From there you can download that specific data.

Reconciling Cart Totals and Payment Transactions in DataNow

In DataNow, two key totals are derived from each order: the Cart Total and the Payment Transaction Total.

• Cart Total: This is the sum of all line items in an order, including any discounts, taxes, and tips applied.
• Payment Transaction Total: This represents the actual amount that is charged and recorded in the ledger.

In most cases these totals should fall within a KPI threshold of 0.1%. However, there may be instances where discrepancies arise due to factors such as system bugs, synchronization issues with devices, or other technical challenges. These occurrences are rare but can cause the totals to not align. If this amount falls outside of 0.1% please report this discrepancy to our support team. 

You can review and compare these totals in several places within DataNow, but the most effective method is using the Sales Audit Report. In this report, you can set the Calendar date to your event date/s, and hit refresh:

1. Check Cart Totals: From the Revenue Summary dataset, you can total the Net Sales, Tax, and Tip figures.
2. Compare Payment Totals: Compare the result to the Settlement Amount Total found in the Payment Type Summary dataset.

This comparison allows you to quickly verify if the Cart Total and Payment Transaction Total align as expected.

Interpreting Results

• If the totals fall within a KPI threshold of 0.1%, you can confidently consider the Cart Total to represent actualized revenue.
• For businesses requiring more detailed reporting, such as sales at the category level, this information can be found in the Revenue Category tile.
• Additionally, for breakdowns of sales by payment method, the Payment Type Details tile provides insights into sales by card type and other payment methods (virtual currency, custom payment types etc)

Reconciling DataNow Totals and LTM

After devices have synced, you can further validate the settlement details using the Settlement by Processor report in DataNow:

• Navigate to the Settlement by Processor Report.
• Enter the Effective Business Date: This is the date the order was created on the device. If this date is NULL, it represents the date the transaction was synced to the server. The Effective Business Date logic provides the most accurate comparison to the LTM reporting.
• Enter the Processor: Shift4 will default as the processor in this filter.

You will receive the Settlement Amount for the specified Effective Business Date. To complete the reconciliation:

1. Log in to LTM: Select Archived Batches from the Transactions section in the top banner.
2. Select the Business Date: Choose the date/s of your event. You'll see the Net Amount on the far right side of the screen. This Net Amount is the total dollar amount processed for the selected date/s.

Note: Some batches may settle days after an event due to factors like offline orders. Always refer to the Business Date when reconciling funds. If there is a mismatch in the dates between DataNow and LTM, this can indicate a variance requiring further investigation.

Reconciliation

• If the totals match or fall within our KPI threshold of 0.1%, the reconciliation is complete.
• If the totals do not match, please specify the variance amount and the percentage of total sales this represents when contacting support.

Key Definition Fields

Please follow the link to this DataNow Key Definitions article for explanations of each calculated field (net sales, gross sales etc), along with an example. 

Historical Data | Data Retention

In January 2025, we will implement a new data retention policy, to align with Shift4's corporate policy. 

Key Changes:

• Data Retention Limit: Beginning in January 2025, DataNow users will only be able to load data from the past 2 years (730 days). Data older than 730 days will no longer be accessible for reports.
  
  
• Rolling Data Retention: The system will automatically remove data older than 730th day each day, ensuring a continuous, rolling 2-year window of data is always available for reporting.
  
  

To assist in preparing for the new retention policy, we will provide resources and guidance on how to export historical data beyond the 2-year window before it becomes inaccessible. Please refer to the Historical Data Best Practices article and the Scheduling Exports article on our support page.