Syndicated data is market data that a research company collects once and sells to many subscribers. In consumer goods it usually means retail sales data and household panel data from providers such as Nielsen and Circana. It is the shared source of truth that brands, retailers, and brokers use when they talk about category performance.
Syndicated data comes in two main forms. Store data is built from retailer point-of-sale feeds and shows units, dollars, price, distribution, and promotion activity by product, retailer, and market. Panel data comes from a sample of households that record their purchases, and it is used to estimate measures like household penetration, buying rate, and how shoppers move between brands.
The providers clean, standardize, and project the data so that everyone in a category is looking at the same numbers. Brands buy access by category, market, and retailer, and the cost grows with the level of detail. Many brands also rely on brokers or retail partners for some of their views.
Coverage has gaps, because not every retailer shares its data with syndicated providers. Some large retailers keep their point-of-sale data inside their own supplier portals, and brands have to pull it separately.
Syndicated data is the language of line review. When a brand argues for more shelf space or defends the space it has, the retailer expects the case to be made in syndicated numbers like share, velocity, and ACV. Data from any other source is usually treated as supporting color.
It also shows a brand where it stands against competitors, which no internal system can do. A brand can see its own shipments, but only syndicated data shows how the whole category moved and who gained share.
The limit is that syndicated data describes the market in aggregate. Brands are not blind, since they can see their business clearly. What they can't see is the household. Store data has no buyer attached, and panel data is a projection from a sample, so a brand cannot email, segment, or reward the people behind the numbers.
A personal care brand prepares for a line review at a drugstore chain. Its syndicated data shows the brand gaining share in the category while private label grows faster, and the brand can show the buyer exactly how its items performed by week and by store cluster. When the buyer asks who is buying and whether they come back, the brand can only point to panel estimates for the whole market, because it has no direct view of the households behind its own sales.
Treating member data as a substitute for syndicated data. Loyalty and member data skews toward a brand's most engaged buyers, so it is not a representative sample of the category. It will not stand up in a line review against Nielsen or Circana numbers, and brands get further by using it to understand their own buyers while leaving category claims to syndicated sources.
Where TrueLoyal fits: Syndicated data shows a brand its business. Receipt scanning adds a view of the household for members who opt in, showing who bought, where, and what, and it sits alongside the syndicated numbers without replacing them.
Nielsen and Circana are the two best-known syndicated data providers in consumer goods. Both offer retail store data and household panel data across many categories and markets.
POS data is the raw record of sales at the register, usually from one retailer. Syndicated data combines and standardizes POS feeds and panel data across many retailers so that a brand can see the whole category.
No. Syndicated store data carries no buyer information, and panel data is an estimate based on a sample of households. A brand can see how its business performs, but it cannot identify or reach the individual households buying from it.
No. Loyalty data comes from opted-in members, who skew toward a brand's most engaged buyers, so it does not represent the category. It is useful for understanding and reaching those members and belongs alongside syndicated data.
POS data is the record of sales captured at the point of sale, which is the register or checkout where a transaction happens. It shows what sold, in what quantity, at what price, in which store, and when. For brands selling through retail, it is the most direct count of how many units actually moved to shoppers.
ACV, or all commodity volume, measures how much of the market a product is available in, weighted by the size of the stores that carry it. It is based on each store's total sales across all categories, so a large store counts for more than a small one. A product with 80% ACV is sold in stores that together account for 80% of total retail sales in the market being measured.
Purchase velocity is how fast a product sells, measured as units sold per store per week. It is the same measure that retailers and brands simply call velocity, and it shows how well a product sells in the stores that already carry it. Because it divides out the number of stores, it lets a brand compare performance fairly across retailers, regions, and time periods.
Household penetration is the percentage of households in a market that bought a brand at least once in a given period. It answers how many people are buying rather than how much they are buying.
Buying rate is how much each buying household purchases of a brand or category over a set period, usually a year. It is measured in units, dollars, or purchase occasions per buying household. Together with household penetration it explains where a brand's volume comes from, because penetration times buying rate equals volume.
A line review is the meeting where a retailer decides what it will stock in a category for the coming period. Every item in the category is assessed, some are kept, some are cut, and new items are considered against the ones already on the shelf. For a brand selling through retail it is the single highest-stakes event of the year.
Category management is the way retailers run each product category as its own business unit, with its own goals, assortment, pricing, and shelf plan. A category manager at the retailer decides which items get space, how much, and at what price, based on what grows the whole category. Brands work inside that process and are judged by what they add to the category.
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