In the last decade, Daiya Foods has ridden the natural foods wave on the back of their vegan cheese products, growing from half a million in revenue in 2007 to an impressive $168 million in 2018, with distribution in every major grocery and natural food store.
Their number one secret to accelerating that growth? Data.
“Data is our biggest selling tool,” says Barry Anderson, Director of U.S. Retail Sales at Daiya.
“Most grocery retailers don’t want to talk about vegan cheese. But once we’ve got the data to show them the incredible growth, reach, and velocity we have, it opens their eyes.”
CPG sales data – or more specifically, syndicated sales data – has evolved to become one of biggest competitive advantages for growing brands in 2018. With competition for shelf share at an all-time high, sales data makes it easy for brands to prove just how much of a lift they bring to the store when given the opportunity.
In this article, we’ll walk through three creative ways brands are using syndicated CPG data to maximize their velocity off the shelf.
Syndicated CPG data includes sales data from multiple retailers, pulled together by third-party vendors to give brands a complete picture of how and when their products (and their competitors’) are sold.
CPG brands can use this data to identify trends such as market share and competitor growth, and compare store-level sales by product.
Syndicated CPG data is one of four major types of retail sales data, which are defined by both their source and their focus, according to CPG Data Insights.
Let’s talk about data source first.
Syndicated CPG data contains sales metrics from multiple retailers, which are gathered together by a syndicated partner like Nielsen, IRI, or SPINS. (Retailer direct data, on the other hand, comes directly from a single chain, like Whole Foods or Kroger.)
On the other axis, syndicated CPG data focuses on sales at the store-level (syndicated shopper data focuses on the purchasing behaviors of individual shoppers). This means syndicated CPG data gives brands a complete picture of of all of the transactions that happened at each store.
The chart below from CPG Data Insights does a great job of visualizing the relationship between the four types of retail sales data:
(Source: CPG Data Insights)
So how are brands using syndicated CPG data (AKA “market data”) as a selling tool? The most straightforward way is the model Anderson described above, to prove your brand’s success when pitching retailers at the corporate level. Armed with data, you can cut through any preconceived notions a buyer may have about your product or your category and make them face the numbers and make a business decision rather than an emotional decision.
As the market becomes more competitive, however, CPG brands are using their syndicated data to power their retail strategies in new ways. Here are four of our favorites:
While leading CPGs have been using market data to fuel trade negotiations for years, innovative brands are finding success using their sales data to influence purchasing at the store level.
When sales reps have access to POS data from the stores they call on, they’re equipped to build a data-driven narrative about why your brand deserves a better spot on the shelf, why the buyer should increase their order size, or why they should pick up your newest SKU. Similarly, they can use indications in the data to prove voids or out-of stocks, fueling their case to get more product in the store.
Here are just a few examples of how top teams are using sales data to secure even higher sales at their top-priority chains:
Beyond the traditional sales function, a huge part of improving your sales velocity is ensuring flawless retail execution in your key accounts. While CPG displays have the potential to move the needle on sales by as much as 193%, they’re executed to compliance less than 50% of the time.
As a result, poor retail execution can cost brands as much as 25% of their potential retail sales, according to the Category Management Association.
Innovative CPG brands can use syndicated data to identify noncompliance and win back those sales. By keeping a close eye on sales in stores where you’ve negotiated and delivered a secondary display, you’ll be able to establish baseline metrics for the sales lift you can expect certain promotions to produce in certain accounts. With those baselines in hand, it’ll be clear just a few days after a scheduled promotion whether there’s something wrong with the display setup or location.
From there, data-driven teams can deploy their field team to take action at those target accounts. Armed with POS trends, they’ll be able to start data-driven conversations with the retailers and take the necessary steps to correct the displays and win back those sales.
(To learn more about how to set up this workflow for your field team, check out our webinar on how to fight retailer noncompliance.)
Any experienced sales manager knows the promotions that drive the most sales in one retailer won’t necessarily work for another. When combined with data about the promotions or merchandising activities your field team is completing in their accounts, syndicated CPG data can give brands insight into exactly which merchandising and trade promotion activities have the biggest effect on sales. (Read more about the power of combining POS data with field activity data in our eBook here.)
For example, Repsly’s retail execution dashboards associate field activities (new facings, demo events, secondary displays, end caps, etc.) with the sales lift you see in each specific account. Over time, CPGs can assign a dollar value to the promotions and merchandising activities their teams complete in the field, allowing them to proactively prioritize the highest-impact activities to move the needle in key accounts.
There are a few big players in the syndicated data landscape, namely IRI, Nielsen, and SPINS. While their products vary slightly, all three data providers are relatively similar.
All three give brands a cross-channel view of product sales, as well as the analytical tools they need to conduct trend analysis by category, product attributes (“cage-free” vs “free range,” etc.).
The major difference lies in the store types they source data from. IRI and Nielsen take a broad approach, covering everything from Food, Drug, Mass, Convenience and Club to Military and Dollar.
SPINS, on the other hand, fits into a smaller niche, covering Natural Grocery and Specialty Gourmet. Notably, however, Whole Foods doesn’t make its data available to any syndicated data provider (you have to get Whole Foods scan data directly from the retailer). So while SPINS provides the most comprehensive view of natural channel sales, brands who sell primarily through Whole Foods would need to supplement their SPINS market data with Whole Foods’ retailer direct data.
That’s not to say IRI and Nielsen cover an exhaustive list of retailers either. Trader Joe’s, Costco, and Aldi are among a handful of other large retailers that also limit the use of their data through third-party data services.
If you’re sold in a fast-moving category in the Natural channel, there’s a good chance you’re covered by all three data providers. In that case, you best bet is to simply compare price. If you care exclusively about Natural Grocery or Specialty Gourmet, you may be able to find a less expensive deal through SPINS, since that’s what they cover exclusively.
If you’re sold in a lower-velocity category or smaller retailers, CPG Data Insights reports the vendor may not have your data as well organized and easy to use as more popular channels. So to be sure, contact all three providers and ask to see how your data will be presented. You might find significant differences in clarity and ease-of-use for your category.
Whichever vendor you choose to work with, remember you can do far more with your syndicated CPG data than just performing market analysis or populating product locators. Winning brands use POS data as the backbone of a data-driven sales and retail execution strategy to get a competitive advantage at the shelf.
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