Data collection and analysis are both new and tried-and-true ways for companies to discover ways to stand out from competitors and increase sales. By analyzing comprehensive cross-channel reports on retail consumer patterns, companies create more competitive strategies for the marketing and sales departments to succeed in the Consumer Packaged Goods (CPG world. These data reports are developed and syndicated by three major research marketing companies: Nielsen, IRi, and SPINS (for the healthy foods sector of CPG).

Although these reports provide immense value to the CPG companies, incorporating store data is highly useful for quicker and more accurate information turnaround.

Syndicated Data vs. Store-Specific Data

These two types of retail data are closely tied but provide very different information for companies to analyze. Understanding how to use each type gives brands increased ability to fit their products to a diverse set of consumers.

Syndicated data

In short, syndicated data provide an overview of any market or category for brands. Third parties purchase point-of-sale data collected by retailers. The sale data are collected at the time of purchase and sometimes referred to as “scan data.” The information about the shoppers and the store is then used to give a snapshot of the overall market so that brands can better understand how to reach consumers in the general public.

The numerous reports on different channels and industries are highly valued by brands. Third parties sell individual reports for a few thousand dollars or offer an assortment of ongoing subscriptions with custom tools that can cost millions per year. These subscriptions may also include data analysis tools to help brands further understand the data.

A subscription to Nielsen can range from yearly to weekly reports. Many large brands can upgrade their plans and receive information every few weeks on the current state of the market and their competitors. These frequent subscriptions allow for quicker fixes or faster awareness of emerging trends.

Store data

Store data can come directly from retailers or third-party sources to better understand geolocated pinpoints of information. Combining the knowledge from each source results in better understanding of ways to increase sales.

Retail-direct data, which are collected by stores, give CPG companies information on the supply chain. This information can be useful to understand geographic subsets of consumers and their purchasing decisions, but it will often not include information on competitors or the full categories. The data are also in the format of the specific retail chain and not usually easy to export so brands can consolidate and analyze them.

Observa gives real-time visibility of products on the shelf using store data. As soon as the information is collected, it is available for the brand. It is useful to determine a consumer’s actions in a particular moment at a particular store under a particular set of market conditions. Using this data helps brands to understand retail-direct statistics, so they can target changes in regions or stores.

Incorporating store data into syndicated data

One of the biggest issues with syndicated data is the delay between collection and receipt of information. Reports from syndicated data, even the ones sent on a biweekly basis, take a minimum of two weeks to collect, compile, and send. Even the most expensive subscriptions will always be two weeks behind.

Another problem faced when solely using syndicated data is the lack of specific information on stores or regions. Syndicated data, although extremely useful for an overall snapshot of the market, doesn’t take into consideration how to fine-tune the different markets. Consumers in Alabama are not necessarily going to make the same decisions that consumers in Washington make, and store data can provide these answers.

Because syndicated data comes only from retail chains that cooperate, there are possible limitations in the data. Aldi and Trader Joe’s, for example, do not give information to Nielsen, IRi, or SPINS. Whole Foods refused for a decade to share information but finally began cooperating with SPINS. All of the marketing companies claim they have statistical projections to account for missing chains and retailers.

By aggregating store data with syndicated data, brands can target their consumers more quickly and accurately.