Integration Setup

Getting started with the SPINS Integration setup.

1: Daasity Extractor Setup

  1. Do the initial data pulls, determine if any product attributes are required beyond the standard (required) product attributes

    1. Ensure data files are available in the specified format.

    2. Use the filename and date patterns to load historical data accurately.

    3. Configure the initial setup to include historical data in your analysis.

  2. Navigate to the Integrations page in the Daasity platform.

  1. Select the SPINS / Circana / Nielsen data source.

  2. Follow the on-screen instructions to authenticate and connect your data source.

  3. Configure the custom attribute columns (up to 10)

Setup SPINS Data Extracts

  1. Go to

  2. Login using access credentials

  3. Once logged into Satori - go to Extracts Tab at the top of the screen

  1. Starting on the Universe Tab - Select Total Product Library

  1. Next go to the Products Tab - Select all Departments, Categories, and Subcategories you would like to include in the dataset

  1. Next go to the Time Frame Tab - To start we will select the following

    1. Time

      1. Aggregated

        1. 4 Weeks

        2. 12 Weeks

        3. 24 Weeks

        4. 52 Weeks

        5. YTD

      2. Comparison Period: YAGO

        1. optional to also include "Prior Period" Comparison Period for your LP Data pulls; this incurs a minor charge due to the substantial data volume increase and requires use of the "Prior Period" Reporting templates.

  2. Next go to the Geographies Tab - Here you will select all geographies that you would like to see in the data.

    1. Under Geography Level - Red Fox recommends using Total US and Region for each Channel/Outlet. If CRMA and Market are also required select these as well.

  1. Next go to the Measures Tab:

    1. Select the following measures that Red Fox requires (note: +/- Change or % Change metrics are not required)

  1. Volume

    1. Dollars

    2. Units

  2. Distribution

    1. Max % ACV

    2. TDP

    3. Number of Weeks Selling

  3. Promo/Non-Promo Volume

    1. Dollars, Promo

    2. Units, Promo

  4. Base/Incremental Volume

    1. Base Dollars

    2. Base Units

  5. Store Performance

    1. of Stores

    2. of Stores Selling

  6. Merch Volume (Conventional)

    1. Dollars, Display Only

    2. Dollars, Feature Only

    3. Dollars, Feature & Display

    4. Dollars, TPR

  7. Base Volume, Promo

    1. Base Dollars, Promo

    2. Base Units, Promo

  8. Next go to the Format Tab - Select the following:

    1. Export Settings

      1. File Format: CSV

      2. Table Format: Standard

    2. Reporting Levels: UPC, optional: Brand

    3. Columns

      1. Select all that are unlocked

    4. Attributes (ten total attributes)

      1. Daasity requires the following β€œoptional” attributes:

        1. Size

        2. Product Type

        3. Positioning Group

        4. Pack Count

      2. Up to 10 additional attributes can be added as you would like to see included in the data. Make sure that these attributes are added to each extract.

  1. Next on the Summary Tab -

    1. Review the selections to confirm you have added everything that is required as well as any additional attributes that you would like to include in the data

    2. Name this extract as LP_DATA

2: Create WxW / Quads

  1. Once this extract is completed, we will use it to create a Week by Week (and Quad Week if necessary) extract

Go to the Saved Extracts page and click the edit icon on the extract

  1. After clicking edit continue to the Time Frame tab and make the following selections:

    1. Time: Trended

    2. Time Period: Weeks (or, Quad Weeks)

    3. Length: 1 Year

    4. Include Year Ago: Yes

  2. Continue to the Summary Tab: Rename the file to β€œWxW_Data”

  3. Click SAVE AS

  1. Repeat process to create Quad Weeks Extract, if desired (Quad Weeks is optional).

    1. Selections

      1. Time: Trended

        1. Time Period: Quad Weeks

        2. Length: 1 Year

        3. Include Year Ago: Yes

    2. Rename: β€œQuad_Week_Data”

Last updated