The Data Difference: How Data Can Enhance Membership Personalization
Companies that put the “custom” in “customer” often have the competitive edge these days. When it comes to retail, personalization has become an influential factor in consumer behavior—over 80% of consumers say they expect personalization and prefer to conduct business with retailers that provide it, McKinsey reports. In fact, more than two-thirds says personalization should be the service standard, according to a recent RedPoint Global survey.
For subscription brands in particular, personalization should come with the territory. Armed with a wealth of data from recurring customer transactions and behaviors—delivery pauses, product add-ons, and even cancellations—subscription businesses can leverage these unique insights and apply them in a way that makes the consumer feel valued, understood, and seen.
But personalization is a broad term, and there are several data-driven ways to achieve it. From analyzing churn patterns, to simply asking customers what they want, most efforts rely on one of two types of data: passive or active. Strategies built around each of these data buckets can be effective at delivering a personalized subscription experience for customers—but the real advantage these days is leveraging both.
Passive Data: Enabling Brands to Read Between the Lines
Passive data refers to data that’s gathered through actions, rather than data that a brand might explicitly ask for. When a customer cancels a subscription, for example, that action alone unlocks several significant data points, such as the time of month members chose to make their move. If brands analyze cancellation timing across their entire customer base, they may notice a monthly pattern emerging, prompting them to send a re-engagement email with a special offer ahead of an anticipated cancellation surge.
Despite this opportunity, organizations are, on average, using just half of the data available to them. Subscription brands can’t afford to fall into this trap, given the robust data set at their fingertips. Cancellation patterns are just one piece of the puzzle—subscription companies can also consider trends in product bundling to create targeted marketing campaigns, analyze replenishment rates to inform delivery models, and sometimes even evaluate monthly usage to offer pricing flexibility.
HP’s new printing-as-a-service subscription, Instant Ink, offers flexibility based on a usage pattern the company identified. For a monthly fee, the service monitors customers’ ink usage and delivers replenishment cartridges at no added cost and without customers having to place an order. Initially, the caveat was that customers had a predetermined maximum number of pages they could print per month, but seeing a great deal of fluctuation in monthly usage, HP now provides users with another option: any unused pages from one month can roll over into subsequent months, giving high-volume printers some much-needed wiggle room. Customers didn’t ask for this feature explicitly, yet HP’s passive data revealed an untapped opportunity to personalize—and therefore improve—the experience for customers.
Active Data: To Understand What Customers Want, Just Ask Them
While any modern, digital brand should have access to passive data to inform personalization, many are also turning to active data to strengthen their efforts. For companies across industries, much of this active data comes in the form of customer-created profiles, which enable companies to curate content, products, and services based on preferences.
The Wall Street Journal, for example, asks users what they’re interested in reading about when they sign up for the newspaper. The result is a highly personalized WSJ homepage full of news tailored to the consumer in question. “Every user creates their own profile and lists their core interests, including topics like politics, sports, entertainment and international news,” writes Jesus Luzardo for Subscription Insider. “With those insights, the platform can make more targeted recommendations and point customers toward new content that fits their tastes.”
Other industries have taken this approach, too. Clothing subscription box brand StitchFix, asks new customers a series of questions about their preferences across a range of different factors, including style, fit, budget, and more. In return, the subscriber receives a box full of clothing packed according to stated specifications, and then has the opportunity to return items that don’t make the cut for them. When items are returned, customers are again asked a series of questions, this time to evaluate why items didn’t suit their needs—all in an effort to better inform the next box.
The Best Personalization Requires the Best of Both Worlds
Both passive and active data have a crucial role to play with regard to personalization, but when combined, they make a much more perfect pair. To build on an earlier example, while cancellation timing reveals some useful passive data, the data set can be exponentially more informative when customers are also actively asked why they’re cancelling and given a wide array of “select all that apply” options.
Quarterly workout gear subscription box FabFitFun embodies this hybrid approach down to the very core of its business model: members can opt to have the company curate their boxes based on a combination of behaviors, patterns, and other passive data points—but it also provides members the option to actively choose what goes into each box. To accommodate the desire for personalization, FabFitFun even built its pricing structures around it: annual subscribers can customize their entire box, while seasonal subscribers get a maximum of four customizations per box.
Often considered the gold standard of subscription-based service personalization, brands like Spotify and Netflix also demonstrate why a dual approach is so critical. While their finely-tuned algorithms gather every bit of passive data possible, evaluating what content users engage with, for how long, and more, they also rely on active input via customer searches. The result is industry-leading personalization.
When combined, passive and active data types paint a fuller picture of consumer preference than when applied separately. Together, they arm subscription brands with a breadth of insight that makes personalization not only possible, but also significantly more powerful.
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