CDPs Help CPGs Get the Data They Need to Compete - Treasure Data Blog
CPG Brands: Use CDPs to Get the Customer Data You Need for DTC Success

CDPs Supply the Missing Customer Data CPG Marketers Need to Compete

If you’re a marketer or brand manager at a consumer packaged goods (CPG) company, you know you’ve long been fighting blindfolded as you’ve struggled to understand your customers’ changing habits and needs. Sure, you get aggregate data about prices and units sold, but most of the customer data you need goes directly into the retailer’s systems and only gets to you if the retailer feels like sharing it—something that’s on-again, off-again at best.

But smart CPG marketers, who live in the real world—where COVID-19 has made it even more urgent to understand customers and the way they buy now—are using advanced martech to end-run the retail systems that have mostly kept customer data to themselves. CPG brands like Nike, PepsiCo, and Clorox, whose management teams were already eying or investing in developing DTC capabilities—have stepped up their DTC game since the pandemic began.

Key to a strong DTC strategy is a Customer Data Platform (CDP), which uses AI and machine learning to unify data from many different sources and create detailed customer profiles. These huge datasets describing customers can then be used to personalize everything from advertising to offers to targeted, tailored customer journeys that increase the odds of purchases and repeat buying.

“We’ve been seeing increasing importance and demand from CPG companies to be able to leverage customer data to improve their marketing activities,” The Boston Consulting Group’s Partner and Director of Personalization and Digital Marketing Stefano Fanfarillo told marketers during a webinar this summer.

This ability to personalize advertising, promotions, and customer experience (CX) for different market segments has the promise to transform how companies build brands and sell their wares.

“I’d say digital itself in fact has opened a number of opportunities for CPG companies to be able to collect and leverage customer data. Some CPG companies have built capabilities to deliver specific customer experiences to collect customer information and establish that direct consumer relationship.”

Fanfarillo says a pertinent example is Ready Refresh by Nestle. This subscription-based, direct-to-consumer delivery service of products like water and sodas creates an opportunity to build customer relationships and collect customer data. And many CPG companies are using CDPs to power similar programs.

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For example, Anheuser-Busch InBev is using a CDP to understand its beverage customers despite a “wall of separation” representing the lack of communication and data flow through retail channels, in markets that span the globe.

“One of the biggest challenges for CPG companies like us, is really how to connect directly to consumers and how we can break this wall [of separation between us and] them,” says Lucas Borges, senior manager, consumer data strategy at AB InBev. “To support this effort, we have been building our own publications, direct-to-consumer channels, loyalty programs, and much more.”

That “wall of separation” is about to get even bigger, as new privacy regulations force marketers to operate in a “cookie-less” world—or at least, a drastically “cookie-reduced” world. How can CPG brands survive if the relatively scant data they already collect is reduced even more?

When it Comes to CPG, Marketing Architecture (Marchitecture) Matters

One reason AB InBev can reach its customers is that there’s finally a marketing architecture—or “marchitecture”—that gives CPG brands the data they need to better understand customers and provide more targeted, personalized advertising and customer journeys. For CPG brands to be successful at DTC, three technologies are critical—a customer data platform, a logistics platform, and an ecommerce platform as illustrated below.

CPG Brands: Use CDPs to Get the Customer Data You Need for DTC Success

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How to Thrive in the CPG Data Desert

Many of the data sources on the left-hand side of the diagram—syndicated and retail-direct product and shopper data—represent data that’s often either not available to CPG companies, incomplete, or anonymized, as in the case of DMP data. In other words, the information can’t be associated with an individual without further processing, or without data-sharing agreements with retailers, which can be difficult to get.

For example, a grocery or department store might collect a tremendous amount of data in the purchase histories of customers who use a loyalty program or store credit card. Some stores even use sensor data to understand individual customers’ routes through stores, or whether they picked a product up to look at it, but then thought better and put it back. Such data helps to redesign displays and foot-traffic plans.

More importantly, these stores can associate individuals with their purchases, and often gain insights about each consumer that suggest which offers, experiences, or merchandise combinations might induce repeat purchases.

But most CPG companies never receive most of that data. They often get only summary information centered around which products sold, and when, but that’s about all. How much more effective could CPG manufacturers be if they had access to that information, and could combine it with other data sources—web-browsing histories, mobile app usage, social media use, ad consumption, and more?

COVID-19 added to the severity of the data desert in which most CPG companies already lived. With many stores closed or only open limited hours, CPG marketers were suddenly lacking contact with their customers.

CPG Companies Use CDPs to Make an End-run Around Retail

Some made the choice to open new direct-to-consumer channels. For example, when COVID-19 hit South and Central America and forced store closings and short hours for those that could stay open, Anheuser-Busch InBev set up a mobile app for Colombians that told consumers where they could buy its beverages. The company’s senior management attributes its ability to reach its customers directly to its CDP, which takes incomplete data from the sources on the left of the diagram, enriches that data with ecommerce and logistics data (from the platforms shown in the middle) and resolves customer identities to come up with unique, identifiable customer profiles. Those profiles—typically hundreds of thousands or millions of customers—can then be used with predictive scoring, segmentation, real-time targeting of offers and experiences. As a result, CPG brands gain rich customer insights and a better understanding of their customers.

CDPs Unify Customer Data to Provide CPG Companies the ‘Missing Middle’ Data

CDPs Unify Customer Data to Provide CPG Companies the ‘Missing Middle’ Data

It’s an approach that’s transforming AB InBev, helping management not just with the immediate need to get the “missing middle” information from ecommerce and logistics, but powering long-term digital transformation at the company.

“Here at ABI, the CDP is our single source of truth talking about our consumer data and it is in a strategic place in our martech stack,” says AB InBev’s Borges.

“With all our data, ABI needs to have a way to connect data from all channels into a single database, where we will be able to build a unified consumer understanding and have the opportunity to learn more about our customers,” Borges adds.

Borges adds that the company’s emphasis on CDP-powered digital transformation, long before the pandemic struck, has helped it roll with the punches as shutdowns of many retail outlets made it more difficult to keep the channel open for purchases. For example, the company was able to quickly pull together apps and open up limited new direct-to-consumer channels to show consumers where and how to buy their favorite beverages, something that probably would not have been possible pre-digital transformation.

How CPG Companies Can Use Their New CDP-Driven Capabilities

Of course, simply having a lot of data does not a marketing plan make. But CDPs are used not just to resolve identities and create complete profiles, but also with the analytics and AI algorithms of the CDP shown in the middle of Figure 1—to orchestrate the initiatives on the right. So, for example, CDP predictive analytics could be used to segment customers for actions in social media channels, content affinity for new articles, or new promotions carried out over email and mobile apps. The CDP can even be used to trigger different actions—to orchestrate the actions of other martech, based on the consumer data and analytics that the CDP provides. And because CDPs can compile very detailed behavioral profiles over time, the customer data gets better, and the predictive analytics become even more accurate.

This approach also helps with the problem of marketing in a “cookie-less” world. Not only do CDP analytics resolve each customer identity—by combining first-party and third-party data using predictive analytics and machine learning—but CDPs can keep track of privacy preferences as well. After all, privacy preferences are a type of customer data, and each contact or data point collected about a customer is also a type of customer data. CDPs are therefore so important to implementing privacy and data security controls that CDP Institute founder and director David Raab has called them “foundational to privacy.”

How CPG Companies Can Fight Back

Clearly, CPGs have long had to go to market with far less data than the retailers with whom they work. CDPs provide an excellent martech solution that not only helps CPGs get the data they need, but also orchestrates campaigns and other marketing initiatives to reach customers, personalize customer experiences, and provide insights and customer data analytics for better decision-making. For more on how CDPs can help CPGs, check out our CPG solutions page or watch this digital transformation webinar featuring The Boston Consulting Group and AB InBev.

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Lisa Stapleton
Lisa Stapleton
Lisa Stapleton is a former editorial director at IDG and former senior editor for InfoWorld and InformationWeek. She has written extensively about enterprise IT, business and environmental topics, and now serves as a senior marketing content manager for Treasure Data. She holds an MBA from Santa Clara, an Applied Math undergraduate degree from UC Berkeley, and an MA in journalism from Mizzou. She also enjoys being a Toastmaster.
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