Direct-From-Consumer Data (DFC)

Direct-From-Consumer Data (DFC): Anatomy Of A Future-Proof Brand

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Third-party cookies have crumbled. The IDFA is DOA. GDPR stopped being generous. In just a few short years, marketers have seen the tables turn nearly 180° — from an age where black box data ran amok and digital fingerprints littered the web to a point where consumers emerged victorious in a quest to have their cake and eat it too. The cake is data privacy protections… and the eating? Well, that’s the ever-increasing demand for personalization and engagement in spite of all the newly-crippled marketing models. But marketers always find a way – and the way ahead is zero-party data, willingly offered up by conscious consumers.  Rather than calling it “zero-party,” we prefer to dub this new era of data “Direct-From-Consumer Data,” or DFC. So how do we get there?

The Defining Traits of DFC

First, transitioning to DFC data principles requires a change of mindset. Many marketers will need to rethink their value exchange for every piece of data they collect and start to imagine how they can improve that exchange to drive mutual benefit and sustainable customer relationships.

It’s often difficult for marketers to distinguish between data a customer wanted you to have versus data a customer surrendered in pursuit of a different goal (e.g., providing an email address to place an order). The former is transparent and evergreen — both parties know the score. The latter, well… ask Facebook how that’s going these days.

To understand this value exchange, let’s explore the defining traits of DFC:

  • Participatory. The consumer willingly offers their data to a brand in exchange for value.
  • Transparent. The consumer knows why a brand wants a data point and how it will be used. They know this not because they scoured the Terms Of Service but because the brand clearly communicated its intent within the user experience.
  • Non-judgmental. DFC marketers don’t buy shady demographic data for pennies and then stereotype their customers. They let the customers self-identify.
  • Reciprocating. The user experience, and the brand at large, consider where, how, and why the consumer would want to offer their data and how that exchange of value can yield trust, not just transactions.
  • Accessible. The consumer trusts a brand in part because they know what data the brand has about them, how they can update it, and how they can take it with them if the need ever arises.

Putting DFC into Practice

Necessity is the mother of invention. As direct-to-consumer (DTC) brands found the traditional retailer model to be a recipe for disaster, they have been the first to develop a mastery of the DFC data approach.

A few of the powerful tactics they are using to get invaluable information directly from their audiences include building gated customer communities, developing two-way conversational commerce and AI chatbots, running on-site quizzes and post-purchase surveys, and more. This newfound DFC data sheds light into purchase intent and history, attribution, demographic data (e.g., household makeup), psychographic data (e.g., personality traits), product preferences, competitive research, and so much more – all information that can shape marketing strategy and product development, but, more importantly, future-proof the brand by serving as a foundation for building consumer advocacy and trust.

Trust is, of course, the most valuable asset brands get in return for honoring these DFC principles. Trust is the next-gen currency for brands… because you can’t build lasting relationships on ad spend ROI. Brands that know their customers well enough to scale trust-based value exchanges will triumph for years to come. So, as we watch direct-from-consumer data gain steam with each waking industry, the question must be asked: Do you know your customers better than a third-party platform does?

Matt Bahr is a co-founder & CEO at Fairing. Shopify's leading post-purchase survey tool. Having spent a decade in ecommerce helping brands master attribution and analytics, he built Fairing to operationalize zero party data at speed & scale.