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Upload Point-of-Sale (POS) Data

The “Point-of-Sale Data” section is where you will upload syndicated Point-of-Sale (POS) data from sources like SPINS and Nielsen.

Point-of-Sale (POS) Data 

The "Point-of-Sale Data" section under Business is where you upload syndicated weekly consumption data from syndicated sources such as SPINS, Nielsen, or Circana. Once uploaded, This data powers several key analytics modules within Vividly, including Bump Chart (for visualizing promotional performance and compliance), Predictive Lift (for forecasting future promotion effectiveness), Actual Lift (for calculating realized promotional impact), and ROI Analysis (for evaluating the profitability of your trade spending). Unlike the Revenue Dollars section which focuses on revenue tracking and forecasting, Point-of-Sale Data requires a different set of measures including base units, incremental units, TDP (Total Distribution Points), and average retail price to provide deeper promotional analytics. The minimum recommended data upload timeframe is one year (52 weeks) for Bump Chart analysis and two years for Predictive Lift functionality. Column header mapping is saved after the first successful upload, so you do not need to re-map on future uploads of the same source type.
 

 

How To Upload Point-of-Sale (POS) Data 

  1. Navigate to Business > Point-of-Sale Data

  2. Review existing data by clicking the settings cog icon to download current data in Excel format (optional, but helpful to verify date ranges already loaded)

     

Upload Process - Step 1: Upload File

  1. Click Load from File to begin your POS data upload

  2. Select your data source type from selection list below the "Upload File" box (SPINS, Nielsen, Circana/IRI, or Other)

  3. Click Choose File and select your Excel or CSV file (must be single-tab format) or drag and drop it in the "Upload File" box.

  4. Click Next to proceed to the field mapping step

     

Upload Process - Step 2: Map File

  1. Map your file columns to Vividly fields:

    • Customer Name → Map to the geography or customer column from your file

    • Product → Map to the UPC or product code column

    • Date → Map to the week ending date or time period column

    • Base Units → Map to base/non-promoted units column (required for lift analysis)

    • Incremental Units → Map to incremental/promoted units column (required for lift analysis)

    • TDP → Map to Total Distribution Points column (optional but recommended)

    • TDP Any Promo → Map to promoted TDP column (optional but recommended for compliance tracking)

    • Average Retail Price (ARP) → Map to price column

    • Stores → Map to number of stores selling (optional)

    • Leave any unmapped fields as "No Match" if not available in your file

  2. Click Next to proceed to the error review step

     

Upload Process - Step 3: Submit

  1. Review any errors (red) or warnings (yellow) that appear:

    • For warnings: Review flagged duplicate entries. If they are legitimate new entries, proceed with upload

    • For errors: Click Show rows with warnings and errors only to filter the view

    • Click Download from current view to export error rows for offline review

  2. Address errors and warnings before proceeding:

    • For Customer Not Found error:

      • Navigate to Manage > Customers

      • Search for and open the relevant customer profile

      • Scroll to Add Alt Names and paste the exact customer name from your file

      • Click on Add Alternative Name

      • Click Save Changes

      • Return to your upload and proceed to the next step

    • For Product Not Found error:

      • Navigate to Manage > Products

      • Search for and open the relevant product profile

      • Add the missing UPC or product code to the Alternative Product Codes section

      • Click Save

      • Return to your upload and proceed to the next step

    • For Duplicate data rows warning: 

      • Delete duplicate rows from your file and re-upload it. 

  3. Once all errors and warnings are resolved, re-upload and repeat steps (or if you choose to proceed with warnings), then click Submit

  4. After uploading, verify your data appears in the Point-of-Sale Data table

  5. Navigate to Insights > Promotion Analytics > Bump Chart to verify your data is populating correctly in analytics

Common Issues

During step 3 of the POS data upload process, Vividly identifies two main types of issues: Errors (highlighted in red) and Warnings (highlighted in yellow). Errors prevent specific lines from uploading, while warnings flag potential issues but still allow the upload to proceed. Common errors and warnings are: 

  • POS Data Upload Error - Customer Not Found: This error occurs when the customer name or geography field in your syndicated data file doesn't match any customer profile or alternative name in Vividly. To resolve this, navigate to Manage > Customers, locate the correct customer profile, and add the exact customer name from your data file as an alternative name in the customer profile.

  • POS Data Upload Error - Product Not Found: This error appears when a UPC or product code in your POS data file doesn't exist within any product profile in Vividly's system. You'll need to either add the missing UPC as an alternative product code to an existing product profile in Manage > Products, or verify that all products in your upload file have been set up in Vividly.

  • POS Data Upload Error - Duplicate Data Rows: This warning (highlighted in yellow) appears when Vividly detects that data for the same customer, product, and date period may already exist in the system. Unlike errors, warnings will still upload if you proceed, but you should review them carefully to avoid double-counting data. If the data is truly a duplicate with identical values, the system will block it as an error; if there are any differences, it will upload as a new entry.

Tips

  • Vividly remembers your field mappings after the first successful upload, making future uploads faster

  • Upload data on a regular cadence (weekly, monthly, or quarterly) to keep analytics current

  • Before re-uploading data for overlapping time periods, verify you're not creating duplicates (delete old data if replacing)

  • For AI-Powered Predictive Lift to work effectively, ensure you upload at least 2 years of historical data with base and incremental units

  • Store your field mapping documentation for reference when training new team members