The Ultimate Beginner’s Guide to CPG Data Analytics

The consumer packaged goods (CPG) industry is undergoing a seismic shift. With increasing competition from e-commerce, changing consumer behaviors, and fluctuating retail growth, brands that rely on guesswork are falling behind. In response, forward-thinking companies are turning to CPG data analytics to drive growth, optimize sales, and improve marketing efficiency. It's not just big brands; smaller CPG companies and startups are turning to data to help solve some of their biggest challenges.

Yet despite the clear benefits, many brands still struggle to harness the full power of data analytics. Research shows that while some companies dabble in analytics, only a small percentage have fully integrated predictive insights into their decision-making. Instead, many remain stuck in reactive analysis—looking at what happened instead of predicting what will happen next.

At Matz Analytics, we specialize in turning raw consumer and market data into actionable insights that help CPG brands scale. This guide breaks down the fundamentals of CPG data analytics, including its benefits, key metrics, and how brands can use it to gain a competitive edge.

What is CPG Data Analytics?

CPG data analytics is the process of collecting, analyzing, and interpreting data related to consumer behavior, product performance, and market trends. By leveraging this data, brands can make informed decisions about pricing, distribution, marketing, and product development.

At its core, CPG data analytics focuses on two primary data categories:

Product Performance Data:

• Sales trends of individual products

• Competitive analysis within product categories

• Price fluctuations and promotion impact

• Distribution and retail availability

Consumer Behavior Data:

• Customer demographics and buying habits

• Store and brand loyalty trends

• Purchase frequency and repeat buying patterns

• Abandoned cart rates and checkout behavior

When combined, these insights allow brands to identify opportunities for growth, optimize pricing strategies, refine marketing efforts, and even predict future sales trends.

Why CPG Data Analytics Matters

Brands that implement data-driven decision-making consistently outperform their competitors. Some key benefits include:

Higher Conversion Rates – By analyzing consumer behavior, brands can refine messaging, optimize ad spend, and increase conversions.

More Effective Product Launches – Predictive analytics help brands gauge demand, identify ideal pricing strategies, and mitigate the risks of failed launches.

Stronger Retail Relationships – Retailers favor brands that use data to support stocking and promotional decisions, leading to better shelf placement and more strategic partnerships.

Optimized Marketing Spend – Data-driven marketing eliminates waste, ensuring that every dollar is spent reaching the most valuable customers.

Competitive Advantage – Brands that track competitor performance and market trends can position themselves effectively and differentiate from the competition.

Key CPG Data Analytics Metrics (KPIs)

Not all data is equally valuable. Focusing on the right Key Performance Indicators (KPIs) is crucial. Here’s a breakdown of the most essential KPIs based on different sales channels:

Retail-Focused KPIs:

• Units Sold per Retailer – Tracks product movement in specific retail locations.

• Weeks of Inventory on Hand – Measures how long stock will last at the current sales rate.

• Retailer ROI & Trade Spend – Evaluates the profitability of trade marketing investments.

• Stock-Out Percentage – Identifies lost sales opportunities due to inventory shortages.

Direct-to-Consumer (DTC) KPIs:

• Conversion Rate – Percentage of site visitors who make a purchase.

• Customer Lifetime Value (LTV) – Total projected revenue from a customer over time.

• Cart Abandonment Rate – Tracks how often customers leave without completing a purchase.

• Return on Ad Spend (ROAS) – Measures the effectiveness of paid advertising campaigns.

By focusing on these data points, brands can pinpoint revenue leaks, improve targeting, and drive sustainable growth.

Where Does CPG Data Come From?

To build a strong analytics model, brands need a combination of first-party and third-party data sources. Here’s an overview of the most commonly used sources:

First-Party Data – Directly collected from a brand’s website, CRM, or sales records. This includes customer purchase history, engagement metrics, and email interactions.

Retail Syndicated Data – Aggregated market data from third-party providers like Nielsen, IRI, and SPINS. These sources provide insights on category trends, pricing benchmarks, and competitor performance.

Consumer Research & Surveys – Direct customer feedback through surveys, focus groups, and A/B testing to understand purchase motivations and barriers.

At Matz Analytics, we combine these data sources to deliver a clear, actionable roadmap for sales and marketing success. For insight on how to turn this data into strategy, click here.

The Right Tools for CPG Data Analytics

To extract the most value from your data, you need the right tools. While large firms rely on in-house teams, many growing brands lack the resources for a full analytics department. That’s where specialized partners like Matz Analytics come in.

We provide CPG brands with:

• Consumer & Competitive Research – Find out what’s stopping customers from buying and how to fix it.

• Conversion Optimization Strategy – Implement high-converting messaging for websites, ads, and retail.

• Sales Growth Acceleration – Guaranteed revenue impact through data-backed strategies.

  
  

Rather than drowning in spreadsheets or investing in expensive data software, we deliver insights you can act on—without the complexity.

Making CPG Data Analytics Work for Your Brand

The brands that win in today’s CPG landscape aren’t guessing. They’re using data to refine their messaging, improve marketing efficiency, and scale their sales faster.

If your brand is looking to turn data into real revenue growth, we can help. At Matz Analytics, we’ve helped 60+ brands in the last year optimize their marketing and product strategies, leading to measurable sales increases.

Ready to stop guessing and start growing? Let’s talk.