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Syndicated Data Analysis: What CPGs Need to Know

CPGs that want to make decisions based on data are likely to have heard about data that is syndicated.

Syndicated data is market information that’s not specific to a specific customer. A combination of product and retailer data typically, syndicated data is taken by market research companies and later purchased by companies that have a stake to the markets.

For CPGs syndicated data can provide an overall view of the performance of retailers and products beyond the reach of single brand or company. For CPG manufacturers the data that is syndicated can offer the necessary insight into consumer behaviour (one which isn’t tied to specific retailers or their ways for framing information).

In order to reap the benefits of syndicated data, organizations require business intelligence tools that are able to analyse it. In the end, data is only as valuable as the information it offers. Syndicated data provides crucial context for CPGs and other sectors however, it should be actionable for the executives who make the decisions.

Let’s look at the fundamentals of syndicated data analysis , and how your business can begin.

Syndicated Data Providers, and Their Function in Analyzing

Before data from syndicated sources can be analysed, companies require partnerships with market research firms that collect the data.

The two largest syndicators of retail information include Nielsen IRI and IRI.

They collect the syndicated measurement of retailers and panel information, which are in the following form:

Retail measurement refers to the data that stores collect through the POS system and software for e-commerce.
Panel data refers to the consumer level information. Data is collected through surveys or via hardware or applications given to households to ensure that they can scan items when they shop. Nielsen as well as IRI have collaborated to collect data from the panel through the National Consumer Panel.

Together with these data sources, they can reveal how consumers behave in relation to the items they’re buying.

The two Nielsen and IRI both offer partnership and analytics capabilities which allow companies to dig into data and create real-time insights.

Nielsen developed The Connect Partner Network in order to link external tools for analytics and data to its rich data source on shopper behavior.

For instance, AnswerRocket connects to Nielsen data and allows Nielsen customers to study market information by asking questions. This simple connection is an aspect of Nielsen’s commitment for an open ecosystem of data with a user-friendly analytics and data tools are able to effortlessly access Nielsen data using an intuitive user interface.

In its most basic sense, the connection between AnswerRocket and Nielsen lets users ask an inquiry based on data and get a visual and insights back. Simple questions such as “what is the growth in market share this year” or “brand penetration across states” are answered in a matter of seconds (in this instance, the responses come in forms of language insight that are displayed in a graph and provide key elements of the narrative data in plain English).

But, these are only the beginning of what the syndicated data analysis could be. One of the most significant advantages of Connect Partner Network Connect Partner Network lies in the capability of analytics platforms to adapt their abilities to meet the needs of the CPG and retail industry by leveraging the huge amount of data. These platforms that rely on AI or machine learning could create algorithms to answer the complex issues that CPG professionals have to ask each day.

Although most analytical tools are equipped to calculate sales numbers but the next stage of analysis of syndicated data appears closer to “how do you think Brand A do last quarter?” with a complete and in-depth explanation on the other hand.

Let’s further break it down by examining the full potential of data analysis that is syndicated.

What Syndicated Data Analysis Does Its Work AI

Syndicated data gives the context needed to evaluate business data within the larger market.

If, for instance sales are falling across the country businesses can view their own loss as a result of a geographic economic decline instead of as a result of their own strategies or campaigns. The company could turn their attention to opportunities, such as the growth of market opportunities in international commerce, as well as then adjust plans to steer clear of dangers of falling sales for categories and products.

With AI data analysis, syndicated data can give these kinds of detailed, actionable information that can be based on issues such as “why sales are declining?”. In the end, it requires the most advanced algorithms for machine learning to sift the syndicated data sources and comprehend how various indicators, such as value of sales, relate. Machines can show the way sales value is affected by other metrics, such as market penetration and volume, and also establish an order of relationships until the reasons for the reduction in value of sales are clearly clarified.

Therefore, the analysis of brand health is much more accessible to business professionals and syndicated data gives the needed context to comprehend the health of a brand in the wider market and AI is able to conduct the extensive analysis that pinpoints the root reasons behind the health of a brand.

With this knowledge Business people are more likely to take action as opposed to when they had to rely on the individual retailer’s data, or didn’t use analytics tools that have the latest AI technology.

Brand health is certainly essential for CPGs But another benefit of data that is syndicated is the insights it offers to other brands of the same size and competitors. What areas are the competitors achieving great success? What are the areas they are ignoring? Which areas can your own business fill the gaps, or even surpass the competition?

The data syndicated provides the data required to conduct this kind of market research and help answer these questions. Additionally, AI is well poised to recognize the most profitable opportunities for companies that want to outdo their competition and get an edge on the marketplace.

The opportunity is huge to frame the understanding of a company’s personal performance inside a wider context in order for business professionals to make better decisions based on more data.