Using Syndicated Data

December 12, 2018
Shari Steinbach
Retail Industry Insights

By Shari Steinbach, MS RDN, RDBA Contributing Editor

You may have heard your retail leadership talk about analyzing syndicated product data but may not fully understand what it is and how this data can impact purchasing, merchandising and advertising decisions. This consumer package goods (CPG) sales data derived from multiple retailers is pulled together by third-party vendors, namely IRI, Nielsen and SPINS, to give brands and retailers a complete picture of how and when products are sold. Brands and retailers can use this data to identify trends such as competitor growth and market share, and compare store-level sales by product. Mark McKeown, from IRI, provided some insights on ways this data may prove useful to retail dietitians:

1.  What type of sales data might a retailer purchase and have on hand for a retail RDN to use?

Retailers will integrate their own point of sale (POS) data, consumer shopper loyalty card information and supply chain statistics, with data from IRI that provides a view into shopper behaviors/purchases at other retailers and channels.  To benchmark their performance, retailers purchase POS data for their respective markets. Most of this is now available via a web-based platform that has prebuilt templates that can specifically address business questions.

2.  How can a retail dietitian obtain this data from their retailer? 

Depending upon the retailer the information could be housed with the shopper marketing team, specific category merchant, or an IRI on-site team member. Some retailers may also have an insights or business information/analysis team.

3.  What data might a retail dietitian use to enhance their work and drive sales?

Start with the retailer’s shopper loyalty card data. This information is typically from the most valuable shoppers and is segmented into 4 or 5 groups to help you understand their purchase trends within key store departments and aisles (OTC, products that have intrinsic wellness benefits, fresh department, and “clean label” products). In addition, product attributes, sourced from on package descriptions and the Nutrition Facts Panel can help to identify purchase trends and which brands/products within the store are available. Dietitians can use this data to build product awareness for shoppers and provide guidance in the aisles. 

4.  How can this data be used on an on-going basis?  

Dietitians could use data to better understand the needs of specific shopper segments (baby boomers) and have the ability to target their on-line educational content to engage shoppers. Also, the insights gained on the latest consumer food trends will help them develop ways to assist retailers with delivering solutions on specific nutrition/food topics while advising specific departments on product assortment. To take it to a more personal level, RDNs can help their customers build a shopping list that supports their dietary preferences, find needed products easier, and offer preparation tips, meal plans and recipes.

5.  Can you briefly discuss the IRI and SPINS partnership and how this may help retail dietitians?

SPINS is a provider of retail consumer insights and analytics reporting for the Natural, Organic, and Specialty Products Industry. We have two-way partnership with them where IRI has integrated 35 of SPINS most in demand health & wellness product attributes into the IRI Verified Audiences Solution that allows CPG manufacturers and retailers to effectively target consumers using verified purchases instead of demographics. SPINS is integrating POS and household panel data from IRI into their solution set for Health & Specialty Retailers. The information can help dietitians identify and promote products that support their healthy living initiatives.

6.  Any resources you can recommend to learn more?

Visit the IRI website and click on Insights where we post our white papers/industry research that will help dietitians. I also recommend they sign up to receive advance notice of webinars we host. Past examples include Generation Z and Self-Care Consumers.