Customer data strategy: Solving the direct to consumer puzzle

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Jigsaw puzzle solvers start with a vision and then apply a strategy in order to piece the whole picture together.

In the consumer products (CP) industry, digital native start-ups have painted a vision of direct to consumer (D2C) success. They deliver simple, contextually relevant experiences that deepen customer relationships and drive revenue. Investors have taken notice. Globally, D2C startups have raised between $8 billion to $10 billion in known venture capital across more than 600 deals since the start of 2019, according to Crunchbase data.

In response, established CP companies are scrambling to execute their own strategies for piecing together the D2C puzzle.

What does this strategy look like? While no two CP companies are the same, a common theme should be an obsession with customer data insights. A deeper understanding of customers’ behaviors, sentiments, and preferences can inform everything from customer acquisition tactics and digital marketing to mobile engagement and the post-purchase fulfillment experience.

How can they put this strategy into practice? Here are three keys.

Look beyond e-commerce

We all know the jigsaw puzzle mantra, “Start with the edges.” It’s good advice, but true aficionados know there’s an even more important step that comes first: Picking a space that provides enough room to operate.

Along these same lines, many established CP brands have tied their D2C initiatives firmly to their e-commerce strategy. While e-commerce is a vital component, there’s an even more crucial decision that should come first: Formulating a customer data strategy that can turn anonymous online visitors into known, loyal customers.

This strategy comes first because it helps inform every step of the customer’s journey, from their first marketing communication to their first purchase, loyalty program offer, and engagement with subscription and continuity selling. In addition, it informs product development and fulfillment decisions.

For instance, collecting sentiment data from surveys and social posts, connecting it to a customer identity, and analyzing it at scale can offer key insights about products and/or services. Decisions based on these insights can drive more sales, refine business models, and reduce costs.

Data: The foundation for customer acquisition

There’s no question the global pandemic has impacted the D2C movement among consumer products brands. New shopper attitudes, behaviors, expectations, and channel preferences have led to an e-commerce explosion to the tune of 10 years’ growth in just a three-month period.

In this fast-changing environment, competition is fierce. So, brands need to reimagine how they market and sell their products. This is why CP brands are investing heavily in digital marketing to drive their propositions and create more customer awareness. In fact, according to a Gartner report, a whopping $55 billion in CP trade spending will migrate online.

As consumers shift to browsing digital shelves rather than physical ones, CP promotional spend is following the shopper audience. Specifically, they’re spending money on tactics such as paid search advertising, paid social media promotions, and SEO initiatives.

What makes these tactics successful? It comes back to a solid customer data strategy. With quality consumer data at their disposal, they’re better able to target and optimize these programs.

This is a new perspective for many established CP brands. In the past, their retail and media partners collected more customer data than they did. Now, thanks to the allure of D2C success, they’re realizing the value of their own customer data strategy.

Just like the famous puzzle proverb – “It’s always the small pieces that make the big picture” – CP leaders are starting to create rich, permission-based customer profiles based on their marketing, e-commerce, and service interactions. Then, through artificial intelligence (AI) and machine learning (ML) technologies, they can identify insights needed to acquire their own customers, instead of relying on retail, marketplace aggregator, or media partners.

Smart sorting: Creating actionable views of customers

The average consumer products company has 15 – 98 silos of customer data (see below). This fragmentation represents a fundamental problem. How can you deliver a great customer experience if you don’t have a holistic view of your relationship with them?

Customer data strategy bridges silos for D2C initiatives.

It also represents a fundamental risk. With too many silos to manage, a CP company is at a high risk of breaking the customer’s trust. They also risk data privacy compliance issues by using questionable data collection and processing practices throughout the journey.

To bridge data silos, mitigate data privacy risk, and put the complete puzzle together, enterprises are turning to customer data platforms (CDPs). These systems centralize customer data from all sources, including back-office systems, into robust profiles. They also make permission-based data available to customer engagement systems in real time.

While many of the early CDP solutions focused on marketing use cases, a new generation of CDPs is changing perceptions and providing operational use cases as well. This means they can offer actionable customer views during commerce and service engagements. Built with data privacy at their core, they can feed AI/ML solutions with clean, reliable, and compliant customer data.

As a result, a global CP business can scale hyper-personalized engagements through elevated automated decision-making, adaptive modeling, and data utilization.

Customer data strategy: The big picture

The time is now for established CP companies to evolve digitally. With D2C models proving to be an area of massive growth, they need to shift their mindset to a consumer data obsession in order to compete and win against their smaller, digitally native competitors.

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Paul Smith

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