How to use Syndicated Data

This page will provide examples for how to leverage syndicated data effectively to drive brand strategy, monitor performance across key accounts, and identify key insights & compelling data stories.

What is Syndicated Data? Syndicated data provides competitive category information at both the UPC and category levels. This data allows brands to monitor market trends, analyze category performance, and benchmark against competitors across retailers and regions. It plays a crucial role in informing product development, promotional strategies, pricing tactics, and brand positioning.

Note: Syndicated data from providers like SPINS, Nielsen, and Circana includes non-additive metrics, such as Max ACV and Number of Stores Selling, which cannot be accurately aggregated from weekly data to longer time frames like Year-to-Date (YTD) or Rolling 52 Weeks.

To ensure accuracy, Daasity provides both Weekly and Aggregated Period versions of all syndicated and URMS (Unified Retail Market Schema) explores. For more details on distribution metrics and the importance of ACV in retail sales analysis, refer to our article “Demystifying Distribution Metrics.”

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Core Use Cases for Syndicated Data

1. Sales Performance Analysis

   • Analyze sales over various time periods to identify growth trends, seasonal variations, and the impact of marketing initiatives.

2. Promotional Effectiveness

   • Evaluate the success of promotional activities by comparing baseline sales with incremental sales during promotions.

3. Distribution and Velocity Metrics

   • Monitor the breadth of distribution and sales velocity to optimize product placement, anticipate opportunities for expansion, and refine pricing strategies.

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Available Reports and Explores

• Reports:

  • Omnichannel Dashboard

  • Data Source Dashboard (SPINS, Circana, Nielsen)

  • Data Source Scorecard (SPINS, Circana, Nielsen)

  • Data Source Ranking Reports (SPINS, Circana, Nielsen)

  • Category Analysis Reports (URMS)

    • Brand and Category Performance

    • Key Drivers Analysis

    • Distribution Opportunities

    • Pricing Analysis

    • Promotional Evaluation

• Explores:

  • Data Source Explore (SPINS, Circana, Nielsen)

  • Unified Retail Market-level Sales Explore (URMS)

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Key Metrics

These metrics are featured in our Dashboard and Scorecard report templates:

• Dollar Sales: Total dollar sales.

• Unit Sales: Total number of units sold.

• TDP (Total Distribution Points): Combination of distribution breadth and depth.

• Max ACV: Maximum percentage of stores selling, weighted by All Commodity Volume (ACV).

• Stores Selling: Number of stores selling the product.

• Avg # Items: Average number of items sold per store.

• $/S/W: Average weekly dollar sales per store per item.

• U/S/W: Average weekly unit sales per store per item.

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Important Details

Required Filters for Reports:

• Time Period: Always apply a specific time frame.

• Geography: Filter by location or retailer market.

• Product Level (SPINS-specific): Filter by UPC, Brand, or Category level to ensure accuracy with non-additive metrics like ACV.

Quick Tips:

• Default to "UPC"-level when using SPINS data, as most product attributes are available at this level.

• Ensure all necessary filters are in place when working with syndicated data to avoid inaccuracies, especially in overlapping retail markets.

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Standard Metrics and Dimensions

URMS.Products:

• Brand Name, Product Name, UPC, Category, Subcategory, Product Type, Size, Unit of Measure

URMS.Locations:

• Geography Name, Retailer Name, Market Level, Channel

URMS.Sales:

• % on Promo, ARP (Average Retail Price), Base Dollars, Dollar Share, Max ACV, TDP

These metrics and dimensions, along with Daasity calculations, enable advanced analysis and benchmarking across your syndicated data sources. For a complete list of metrics and definitions, refer to the Integration documentation for each data source (ex: SPINS "How to use" page)