Supplier guide to unlocking retail data in every department

Learn how to harness clean retail data across every team and system to improve decision-making and drive real business outcomes.

Days at CPG companies are as varied as the products they create, the markets they serve, and the retailer partners they supply. 

Navigating a launch into big-box retail, a successful D2C brand is preparing inventory for its first shipments. Meanwhile, at a snack foods company, everyone is working together to bring a healthy kid’s line to market. At the same time, a legacy household goods enterprise is measuring back-to-school performance by brand and planning its winter product displays.

Despite their differences – in market penetration, number of employees, company stories, missions, and strategic priorities – one thing all these companies share is the resounding need for fast, actionable insights to deliver products into consumers’ hands as efficiently and smoothly as possible. The competitive omnichannel landscape makes this all the more important.

Activating data for every team, in any system

Automated, daily retail data can serve as a backbone of CPG organization operations, offering a unified source of truth for all customer data, right down to the SKU and store level. By ingesting, modeling, and integrating sales and inventory data from serviced retail partners into a data repository, teams across the enterprise gain a real-time pulse on performance and can make data-informed decisions with confidence.

With the right data foundation in place, here are the top ways CPGs can leverage retail data across departments.

By ingesting, modeling, and integrating sales and inventory data from serviced retail partners into a data repository, teams across the enterprise gain a real-time pulse on performance and can make data-informed decisions with confidence.

1. Data-driven supply chain engine

For supply chain teams, centralized retail data creates a real-time feedback loop, providing a stream of insights that fuel optimal responsiveness and efficiency. By accessing daily inventory levels, sales velocity, and demand patterns across every retailer and distribution channel, supply chain professionals can transform operations into a well-oiled, data-driven engine.

• Inventory management: Centralized data helps streamline and balance inventory levels across all channels. This reduces waste and minimizes markdowns, leading to more efficient operations and a healthier bottom line. (See: ZURU Toys sidesteps 50% of potential markdowns)

• Demand planning:  Leveraging accurate, real-time inventory data at the store and distribution center level, demand planning teams can address out-of-stock (OOS) issues promptly, ensuring continuous sales flow. (See: How Carbone saved $500K in prevented OOS)

• Logistics: Data-driven planning allows for reducing transportation costs by optimizing routes and schedules based on real-time information. This makes logistics more cost-effective and efficient while ensuring on-time, in-full (OTIF) success – a critical performance benchmark for leading retailer partners.

2. Seizing opportunities commercial-side

The retail landscape is fiercely competitive, and CPG sales and marketing teams play a critical role in staying ahead. Centralized retail data equips these teams with the real-time insights needed to enhance performance, strategically plan, and seize new opportunities. 

• Sales teams (internal and brokers): When sales teams have access to reliable, real-time insights for the retail customers and territories they serve, they can build compelling sales stories, renegotiate or expand existing points of distribution (PODs) to meet proven demand, and unlock new opportunities by proving business success.  Granular retail sales data supports the entire commercial business with a unified strategic vision and plan of attack. These wins across all regions add up significantly, with international coffee brand Illy reporting a 10% total revenue increase employing a data-driven approach, and ZURU Toys growing distribution at the largest retailer by 55% YOY.
  
  Sales teams also benefit from bringing seasonal data to the table. By proving previous years’ demand to unlock new seasonal opportunities, and navigating the fast-moving holiday season with real-time insights, ZURU Toys saw an 86% YOY sales growth in November and December of 2022.

• Marketing: Timely retail data allows marketing teams to target and measure digital campaigns with precision. Real-time feedback effectively closes the gap between digital marketing campaigns and in-store sales. This is how beverage brand Poppi connected targeted TikTok campaigns to an 80% regional sales boost.
  
  Retail data is also a powerful tool for optimizing campaign efficiency. At the very least, you don’t want to spend advertising budget on an empty shelf. Equipped with key sales and inventory insights, marketing team members, including brand managers, creative directors, strategists, in-store ambassadors, and more, can know what’s flying off shelves regionally and what needs more promotion. (See: Brew Dr. Kombucha leverages performance heatmaps to drive marketing campaigns)

Equipped with key sales and inventory insights, marketing team members, including brand managers, creative directors, strategists, in-store ambassadors, and more, can know what’s flying off shelves regionally and what needs more promotion.

3. A new era for category management

Category managers are entrusted by brands and retailers alike to grow their product portfolios while advising on expanding the category as a whole. 

A new era of retail intelligence, defined by the availability of real-time insights, transforms the role of a category manager today by empowering them with granular, actionable data rather than solely syndicated lookback reports.

• Modular mastery: Timely insights empower category managers to optimize planograms (modulars) by identifying high-performing products, adjusting placements based on sales velocity, and ensuring optimal shelf space allocation.

• Omnichannel chops: Category managers today need to consider the digital sales landscape, including how products perform on platforms like Instacart or retailer websites. This comprehensive view helps them understand and optimize product assortment strategies across all channels.

• Category reporting: Analyze sales trends, market share, and competitive insights to optimize product assortment, pricing, and promotions and ultimately drive category growth and strengthen retail partnerships.

4. IT accelerates insights

IT serves as the steward between data technologies and the end-users in various business departments that benefit from them. When a retail data system is streamlined and deployed across an organization, IT teams save a lot of time and resources for other business endeavors. 

• Avoid DIY data pipelines: Building and maintaining in-house data pipelines can be costly and time-consuming, requiring significant resources and expertise. Building a single retail data connector can cost teams upwards of $100K, not including maintenance. From there, it costs companies an average of $500K per year to maintain all of their data pipelines.

• Eliminate bottlenecks: Automated retail data, seamlessly integrated with a business’s unique infrastructure and intelligence (BI) tools, empowers business users to access and analyze data independently, reducing the reliance on IT for ad-hoc reporting. This not only accelerates decision-making but enhances collaboration across departments, as everyone has access to the same real-time insights. (See: How Nestlé streamlined UNFI reporting for 1500+ SKUs)

• Ensuring data success (and data governance): IT plays a crucial role in ensuring data quality, accuracy, and security. By implementing robust data solutions, IT teams can ensure that data is consistent, reliable, and compliant with relevant regulations. This fosters trust in data-driven decision-making while mitigating the risks associated with data breaches and misuse.

Building a single retail data connector can cost teams upwards of $100K, not including maintenance. From there, it costs companies an average of $500K per year to maintain all of their data pipelines. 

5. Data science dives deeper

For central data teams, retail data offers the key to unlocking deeper, more valuable insights. By leveraging well-structured, clean data, data scientists can drive sophisticated analyses and advanced use cases across the enterprise.

• Data enrichment: Layer sales and inventory data with other internal and external sources such as syndicated market reports, EDI, and weather data, enabling a more nuanced understanding of sales trends and inventory dynamics. Create groupings – like store clusters – to break down market segments and monitor performance. Like PopSockets who integrates Crisp with Snowflake to track regional product trends and analyze performance at Walmart stores with secured glass displays, for example.

• Semantic layer: A semantic layer translates disparate retail data language into streamlined business logic that matches your business’ standard metrics and nomenclature – readying your data for everything from analysis to natural language models.

• AI/ML applications: Crisp’s meticulously structured data sets the perfect foundation for LLM interaction in emerging generative AI tools like Databricks Genie. The same data foundation also aptly fuels next-generation machine learning (ML) models, unlocking unprecedented performance optimization.

6. Executives see the vision

For CPG executives and business leaders, a unified, real-time view of retail data helps steer the company toward its strategic goals. It provides a holistic understanding of market performance around the clock, enabling data-driven decisions that optimize profitability, drive growth, and mitigate risks.

With clear visibility into key metrics across all departments, executives can confidently present a compelling narrative of success to stakeholders and ensure the company’s future-proof foundation in a data-centric landscape.

Real-time data provides a holistic understanding of market performance around the clock, enabling data-driven decisions that optimize profitability, drive growth, and mitigate risks.

Do data your way

Leveraging clean, automated data in the omnichannel retail landscape is not only advantageous but essential for staying competitive. As the future of CPG data analytics evolves with AI and an industry-specific semantic layer solution, the ability to turn disparate data into actionable insights will define the industry’s leaders – and those who fall behind.

Start your data transformation today to harness the full potential of your retail data and drive excellence across your CPG organization. Contact our team to learn more.