CPG Data Trends for 2022 Come Down to One Thing: Simplify

It’s almost a cliché to mention that the pandemic has changed everything. Consumers have changed their shopping habits, and hiccups in the supply chain have created impossible situations for retailers and their suppliers. These challenges happened quickly and without much warning, prompting industries of all kinds to reexamine long-held beliefs about operations, data, and security.

Consumer Packaged Goods (CPG) is one such industry. These past few years have disrupted the norm for CPG with consumers altering their expectations and priorities shifting more quickly. One thing the pandemic made very clear is that data is the lifeblood of operations, and maintaining the flexibility to pivot quickly is key to remaining in business. Let’s take a look at what’s at stake for CPG.

 

Bringing more real-world data into analytics

Customers have expressed uncertainty about what they want and how they want to receive it. While lifting Covid restrictions brought some relief, many consumers are reluctant or unsure about returning to the public sphere. In addition, they want the multitude of choices for shopping and delivery to remain even as physical locations get back to business as usual.

Real-world, real-time data offers insights into customer behavior that companies can’t get anywhere else. Focus groups often can’t predict their own behavior in a physical store, and historical data doesn’t account for trends or disruptions. Real-world data allows companies to pin down customer behavior in the now.

Traditional analytics sometimes uses theoretical data to run queries, but companies must respond to events happening now. When companies use actual, observational data from their own operations instead of data created in a controlled experiment or situation, they can make better decisions. Real world data includes:

• Sales data from specific geographic locations
• Analysis of common customer journeys for the top repeat customers
• Customer service data from call center logs

And many more data repositories collected from both CPG internal operations and those of partners. Companies can ask questions like:

• Why are consumers buying my product?
• What is their path to purchase?
• Where are they buying it, including competitor stores?
• What new products should we launch to offer more value and satisfy customer needs?
• How do we predict demand?
• What are coming economic trends, and how do they play into pricing strategy?

As answers shift, real-world data is the only way companies can maintain a close relationship with customers and capture customer behavior that may not be apparent with any other research type. Change is the only constant, and data should reflect that change.

 

Accelerated digitization improves processes but also fragments them

Another byproduct of the pandemic was accelerated digital transformation. Companies scrambled to operate in a world that was different overnight, adopting data and technology strategies in a piecemeal approach to account for the rapidity of the changes occurring.

A piecemeal strategy allowed many companies to survive. But now that the pandemic is two years in, security and integration challenges stemming from this approach are more apparent. CPG companies also rely heavily on partner data to understand and capitalize on customer behavior. Many of these avenues directly result from pandemic shopping behavior—subscription boxes, direct-to-consumer (DTC) sites, and others.

CPG companies can thrive in these new e-commerce choices, but only if they can capitalize on data analysis and digital transformation. Companies need a way to integrate data input from multiple sites and account for nuances site to site.

Finding innovative strategies to connect to customers through digital channels is key. And as those channels and trends evolve, data will become a critical factor in identifying where customers are sooner. But companies can only wield that data if they can connect the dots with the right infrastructure.

 

Governance is a multilayered consideration with far-reaching consequences

Data governance has always been a significant factor in data strategy. But as global commerce becomes more complex, creating a new era of governance is critical. CPG and multi-brand organizations must wade through governance questions with an exceptionally critical eye because now governance involves multiple layers reliant on outside or third-party participants such as:

• Privacy laws extend beyond the organization. Data collection strategies must comply with ever-changing regulations in the company’s home location. The company must outline a plan for data collection in regions with different laws and regulations.
• Who can gain access to what data must also be well-defined. For a single brand company, that’s already a complex concept. For CPG and multi-brand organizations — with potentially dozens or hundreds of groups — ensuring clear and consistent access is a delicate dance.
• Consumer focus. Research indicates that customers are willing to share their data with companies that offer real value in return. Building a governance strategy that puts customers at the center of operations builds trust and helps keep governance on the right path.

A unified governance strategy may be a challenge, but it’s something companies cannot neglect. CPG and multi-brand can finally use data — instead of merely gathering and storing it — with a governance strategy that:

• Considers the unique needs of CPG. Data should flow freely between CPG companies and their partners, but follow regulatory guidelines.
• Allows granular control over who can access what information and when
• Maintains the integrity and quality of all data without creating new silos

 

A simplified data operating system unites complex CPG data and tools

CPG and multi-brand companies must leverage data to provide customer value, but it’s a challenge with the many intricacies of data collection. A data operating system that integrates with all tools and platforms can offer a lifeline.

Upgrading analytics capabilities would allow CPG to engage in predictive analytics. This enables companies to:

• See a trend before it happens and shoring up inventory for a matching product to prevent the dreaded out-of-stock message
• Predict how different pricing strategies could change the outcome of a particular quarter or business relationship
• Understand supply chain red flags and pivot more quickly so that customers experience less disruption

The Modern Data Company’s DataOS offers CPG companies the opportunity to simplify their data despite the odds and launch real-time, predictive analytics that could move operations from reactive to proactive. It’s a chance to build comprehensive governance strategies and harness the true potential of data without replacing legacy systems. It’s an upgrade without rip-and-replace or data movement and enables the next generation of CPG data analytics.

Find out how DataOS is transforming data for retail and CPG companies with our eBook “Shaping the Future of Business With Advanced Analytics”.