Forty-eight percent of US consumers said they plan to shift to online shopping this holiday season, according to a recent McKinsey study on consumer behaviors amidst the ongoing pandemic. A trend toward contactless, digital-first experiences is further illustrated by 73% of US shoppers saying they’ve tried a new shopping behavior this year, with 80% saying they intend to continue the new behavior. These new behaviors include buy online, pick-up in-store or curbside (BOPIS), or purchasing traditional in-store products such as groceries exclusively online.

This study, and many others like it, all point to the online experience rapidly becoming the primary experience for a consumer. Yet even with this flight to digital, consumers still expect brands to recognize them as the same customer across channels. In a recent Dynata survey commissioned by my firm, Redpoint, 70% of consumers said they will shop exclusively from brands that show they understand them this holiday season, with 66% saying they want a personalized experience to be consistent and frictionless, no matter the channel.

Increased Personalization and an Increase in Customer Data

To meet these expectations, brands must deliver deeper levels of personalization, essentially bringing the corner store experience online. If on a 1-10 scale today’s online personalization generally hovers in the low 1-2-3 range (think of an image of apparel that matches a customer’s preference), consistent and frictionless personalization must be more in the 4-5-6 range. This would be on par with real-time open emails, for instance, with a marketer able to change content until the moment of open to ensure a highly relevant, personalized interaction that reflects a customer’s up-to-the-second behavior across all online and offline channels.

Deeper levels of personalization, however, require customer data — far more, in fact, than most brands have that is cleansed, matched, unified and easily accessible in a single platform. With automated machine learning and real-time decisioning applied to a persistently updated unified customer profile, brands are equipped to raise the bar for meeting customers’ expectations for consistent personalization across channels.

Related Article: Personalization Efforts Falling Flat? Look to Your Customer Journeys

Data Privacy and Brand Promise

It follows that brands that take the necessary steps to know everything there is to know about a customer then have an obligation to safeguard customer data. Advanced personalization means little if a brand is careless or disrespectful of customer data, and any goodwill built up from a superior customer experience will quickly evaporate if data is lost, stolen or misused without transparency or consent. To successfully enhance personalization efforts, brands must consider data privacy as an integral component of a brand’s promise.

With consumer behaviors changing in response to the pandemic, it’s clear that customers extract meaning from their brand interactions differently than before. Largely already commoditized, price and product are even more devalued. Customers are placing a higher value on trust. Yes, they want brands to respect their preferences for safe, contactless experiences. And they’re willing to provide more data to make it happen — as long as a brand accepts the responsibility. In a Harris Poll survey on customer experience, 89% of consumers said they’d likely switch brands if their personally identifiable information (PII) was compromised, with 88% switching brands if a brand sold their data without permission.

Related Article: We're All Stuck in the Privacy and Brand Safety Tangle

Learning Opportunities

Keep Data Privacy Close to the Vest

Brands can do several things to enhance a personalized omnichannel experience without having to sacrifice data privacy. First and foremost is to keep customer data, especially PII and other sensitive data, within an organization’s own security perimeter — whether that’s on-premises or in the cloud. This is a basic if often misunderstood tenet. There’s a misconception that SaaS companies can offer indemnity for data loss, but indemnification does not pay for the loss of brand reputation or trust. The bottom line is that data is always at risk when it leaves a company’s perimeter, full stop. If you want maximum control, you don’t let it out of your security perimeter.

Beyond this, however, is bringing advanced levels of security into customer data. This is crucial, especially with the consumer’s web experience rapidly becoming the primary interaction with a brand. Exposing personal data to a website necessarily brings it closer to the edge of the security perimeter, increasing the risk of exposure and misuse. Homomorphic encryption minimizes the risk by essentially never de-crypting the data — even when in use.

Cleansed, matched, and always-encrypted customer data accessible as a unified profile also increases security by reducing the reliance on third-party data and third-party vendors for those tasks. Tools that match data with higher accuracy than outside vendors — while keeping that data inside of an organization’s own security perimeter — is another layer of self-reliance that reduces risk every time data would otherwise have to be moved back and forth.

Related Article: How Clean Data Supports Consumer Privacy Efforts

Data Structure Methodology

Enforcing structure upon customer data upon receipt is another advanced layer of security that should be taken into account. Many marketing systems only enforce a structure on data once it’s queried. The problem, aside from increasing runtime, is that it may produce as many results as there are users who make a query, leading to inconsistency. This of course creates data lineage and data governance issues, which are especially problematic for compliance with GDPR, CCPA and other regulations for which proper data control are a prerequisite. An ephemeral nature to data structure is simply not conducive to the granular level of lineage tracking, GDPR tracking, encryption, predictability — all the necessary components for ensuring that customer data is being used in accordance with a customer’s stated preferences for visibility and transparency, even as it is used to meet parallel expectations for a personalized experience.

The need to increase data privacy and a personalized consumer experience are accelerating down separate tracks, both driven by changing consumer behaviors. When data privacy is in lockstep with a brand’s promise, ambitious marketers do not have to sacrifice one for the other. Rather, paying heed to advanced data security measures makes it even easier to deliver on the expectation for a holistic, frictionless customer experience.

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