CPG Analytics 101

A resource for those beginning in CPG Category Analytics

This website is intended to help those new to the world of CPG Category Analytics. Job titles vary by company, but can be titles such as Category Manager, Business Analyst, Market Analyst, Consumer insights, etc. There are also levels based on your knowledge and expertise in Analytics that may include Associate (beginner), Senior, Manager, Insights Consultant, Director (advanced & leads a team), VP and so on. I refer to what we do as "Data Scientists". Based on the business question or request, we might set up a hypothesis or theory about what may be happening related to the request. We explore a vast sea of numbers in the data, thus mining the data to seek the true insights, trends, and realities of the business / consumer landscape that may or may not support our initial hypothesis. Either way, we support and answer their business question(s) or request with our fact based findings.

Job descriptions and responsibilities will vary too, depending on the scope of your work. But if you are going to be engaged in using programs or portals provided by data suppliers like IRI or Nielsen, then you will need to understand the fundamentals of interpreting the data, what it is telling you, what measures and specs you need to derive to a conclusion or meaningful insight.

Most times, your role may demand cross collaboration among Sales, Marketing, Trade, Finance, and senior management.Each of these departments will request and look at the data differently with different goals in mind. For example, Sales might weigh their brand or item performance based on distribution which is a standard measure called %ACV, which we will cover off on later. Marketing might look more into Penetration which is a standard Homescan / Panel measure that looks at the percentage of households for a given geography and period (depending on the time frame you select) that purchased your brand or item.

When you are tasked with pulling data you must at least ask and understand the very basic specs or needs of what the requester is asking for which include:

  1. What category, vendor, brand, or item a.k.a Sku or UPC are you looking for?

  2. What time frame or set of periods do you need?

  3. What geography or market, channel, retailer do you need to analyze?

  4. What measures or facts do you want to use in your analysis? This may be    

      looking at dollar sales, units, average unit price, ACV/distribution, velocity, base or

      incremental sales.....the point is what measures of facts do you want to use to

      size up your business?

Try to gather as much detail from the requester as possible. Also ask them what is the business question they are trying to answer? The reason we ask these questions, is so we do not end up pulling data again, and again, and again for the same question if the outcome doesn't look right for the requester.

In the Basic Analytics portion of this site, we will explore types of data, sales decomposition, trended data and a typical sku ranking that address the fundamentals of analytic data reports. Analytics will always continue to evolve as new types of analysis are developed. We have provided various

example analysis in this site that go beyond the standard sales analytic tree structure.

When you receive a request to analyze a category or product, make sure the requester answers all your questions in order to do your analysis. However, other questions to ask is "What is the business question you are trying to answer?, What are they looking for in the data results, and How do you intend to use this data?"

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