What is CPG Data Analytics?

CPG analytics is the collection and interpretation of data from various sales and marketing sources. Without analytics, it’s nearly impossible to turn raw data into actionable insights. For example, knowing your percentage of all commodity volume (% ACV) or total distribution points (TDP) is helpful, but analytics help you determine what to do with this information.

CPG data analytics can be divided into sales data, action data, and observational data. Each provides valuable insights into your brand’s current performance and potential areas for growth. For instance, if your TDP is lower than expected in a specific market, you can analyze areas of improvement. Are there key retailers you’re missing? Are your products adequately promoted in the stores you do have a presence in? Until you analyze the data, your strategy may be missing key opportunities.

Retail Measurement Data vs. Panel Data

When working with CPG data, there are two primary types you’ll encounter—retail measurement data and panel data.

Here’s a quick overview of each classification:

Retail Measurement Data

Retail measurement data gives you information from every transaction at the register, offering insights on price, volume, promotions, and more. This point-of-sale (POS) data is valuable for understanding key metrics, including how your products perform relative to competitors.

POS data provides real-time insights into how your products are performing in the marketplace. By analyzing POS data, you can track sales volume, pricing trends, and the impact of promotions. It also helps identify the best-selling products, understand customer preferences, and spot regional trends. POS data enables you to assess how your products are moving in different retailers, whether your promotions are effective, and where there may be opportunities for growth or adjustments in pricing strategies.

Panel Data

Retail measurement data only tells part of the story. To understand who’s buying your products and their shopping habits, panel data steps in. This type of data gives you a more comprehensive view of consumer behavior, providing insights into demographics, shopping frequency, and basket size.

For example, panel data can reveal:

• Penetration: How many households are purchasing your product?
• Buying Rate: What is the total spend per household over a period?
• Purchase Frequency: How often are customers buying your products?
• Purchase (or Basket) Size: What is the average spend on your products during each shopping trip?

How can CPG Analytics Improve Efficiency?

Predicting shopper behavior can be challenging. Focus groups may not reflect real-world decisions. But CPG data analytics offers real-time insights into actual consumer behavior, allowing you to refine your strategy for continuous innovation and growth.

The process works like this:

• Sell products
• Collect retail measurement and panel data
• Make adjustments
• Repeat

This cycle ensures that your brand stays focused on what sells. If a product isn’t performing well in a specific market, you can either remove it or replace it with a better-selling item to streamline operations.

What are some important CPG data analytics KPIs?

Key performance indicators (KPIs) are essential to understanding the success of your brand’s data analytics.

Here are some critical KPIs:

How to Use CPG Analytics

On a brand level, CPG data analytics should inform you of growth opportunities and where to cut losses and expenses. Remember the cycle of continuous improvement? You can only deploy that with data-driven analysis. Otherwise, you could make adjustments that hurt your brand more than they help. On a more specific level, here are some tips on how to use CPG analytics:

• Focus on Losses – Rather than tinkering with products or categories that are performing well, focus your attention and investment on sections that are losing money. This way, you can determine whether to cut or correct them and streamline your operations accordingly.
• Start Small – Don’t try to incorporate analytics into every part of your operations at once. Instead, begin with a specific KPI and figure out how to use it to improve operational efficiency. As you go, make changes to ensure smoother sailing as you move forward. Once you have that process dialed in, move onto the next KPI.