Go Deep: Why a First-Party Data Strategy Needs to Incorporate Depth

Whether it’s diamonds from the deepest ocean or a famous Ansel Adams photograph, depth provides a richness of context and value, real or perceived. As it concerns a first-party data strategy, depth is the difference between providing a hyper-personalized, relevant, and meaningful customer experience that is consistently in the cadence of a customer journey, or a fleeting, inconsequential experience that is quickly forgotten.

Consider a recent Dynata survey where 52 percent of consumers surveyed said that a brand makes them “feel understood” when they provide relevant product/service recommendations. Furthermore, 41 percent indicated that a brand expresses an understanding of them as a unique individual through sharing the right amount of information, and 37 percent said it is when a brand communicates on the channels a customer prefers.

That depth of experience which resonates with customers is made possible only through a deep, rich contextual knitting of first-party data, which requires precise levels of data quality and identity resolution. Surface-level personalization is possible without it, but customers are keenly aware of the difference.

Perils of Surface-Level Personalization

With the use of third-party cookies as a proxy for customer understanding going by the wayside, there has been a renewed interest and focus on first-party data as the foundation of a CX strategy. Real-time website personalization illustrates why depth matters in a first-party data strategy. With basic demographic data and perhaps some recent behavioral data – recent as in that exact website session – a brand might provide what passes for personalization, showing one image or text field out of perhaps a choice of a half dozen or so.

For many brands, such an action might constitute “personalization,” but showing a customer a certain image only because the customer clicked on a link to a specific product page can just as easily be done through the use of a third-party cookie, with the only real difference that the customer just happens to be on the brand’s own website.

But, as the Dynata survey and other research shows, that surface-level personalization does not drive revenue. A short-tail record of a customer’s transactions and/or behaviors lacks the needed context that is derived from knowing the entirety of a customer’s behaviors not just over time, but across channels, and across all devices and identification proxies, known and unknown.

A Record’s Depth and Breath Provide Opportunity

A brand’s approach to an abandoned shopping cart illustrates the power of depth through a long-tail customer record that captures all behavioral and response data and hundreds of attributes across every channel, and having this record fully accessible in real time.

With a full, contextual understanding of a customer, a brand will know with a far greater certainty a reason for the abandoned cart and will be able to craft a real-time response in the context of an individual customer’s buying journey. The brand will know, for example, what channel to engage the customer on, the appropriate waiting time, and the optimal frequency of contact. Is an immediate, real-time response the most effective way to re-engage every customer, for instance? Perhaps a next-best action might be to instead wait two days before sending an SMS, not with a reminder of the cart abandonment, but with an offer for a similar product the customer expressed interest in during a call with a call center agent. With this granularity, brands can also act on partially abandoned carts.

By contrast, with only a short-tail record to help guide a customer journey, a brand’s response to an abandoned shopping cart might be limited to an automated, instantaneous “Don’t go yet!” email reminder. Again, a brand might consider this to be personalized – and in real-time, no less – but the approach has no connection to an individual customer journey or insight into a customer’s purchase intent.

Embrace the Art of the Possible

Depth may also be understood in the context of the history of a customer record – how far back a long-tail record goes. A retailer needs flexibility here: they might want a complete record to include every lifetime transaction or website behavior to improve the customer’s online experience, but may act on aggregate data and/or only more recent data for a call center agent.

The point is, an unwavering focus on first-party data creates unlimited possibilities for enriching a unified customer record to help a brand guide an individual customer journey to its logical, optimal conclusion. In whichever direction a customer proceeds, the deeper the record the more a brand is positioned to move with the customer.

Orchestrating real-time decisions and an omnichannel customer experience around a long-tail record exponentially increases the art of the possible, and all with first-party data. The Redpoint golden record is the pulse of the rgOne CX platform that our data-driven clients use to animate omnichannel experiences tailored to an individual customer.

For more on how Redpoint can help your organization capitalize on the “bottomless” opportunity afforded by rgOne in the orchestration of real-time experiences at scale using only first-party customer data, click here.

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