Predictive Personalization: How Far is too Far?


Predictive personalization, also referred to as digital hospitality, is one of the rare marketing practices that offers nearly equal benefits to both the consumer and the brand – if it’s done right. But, marketers need to be careful they don’t take this valuable tactic too far and cross the line into invading customers’ privacy.

Predictive personalization provides the ability to predict consumer behavior based on their previous online actions, allowing marketers to create entirely personalized customer experiences. Perhaps a testament to the true value of predictive personalization is the fact that in the fleeting world of marketing and advertising trends, it has remained both significant and increasingly popular. To execute a predictive personalization strategy, marketers must observe the types of activity that consumers are engaging in online. They have to identify a consumer’s implicit behavior and then determine that consumer’s next step and explicit behavior, which could include making an online purchase, filling out a contact form, signing up for a newsletter or spending a certain amount of time on a given web page.

This level of personalization is possible due to the advanced technology available to marketers today. Analytics is much more than simple data collection and dashboards. It opens up a huge opportunity to build personal website experiences that are based on how the visitor uses the website. What’s more, predictive modeling enables behavioral segmentation, which is advantageous not only for marketing but also content design. This trend will only continue to rise in the coming year.

However, marketers should take pause and ask themselves – how far should they take analytics to create individual experiences? At what point does gathering and analysis of personal information stop being useful to the consumer and enter the realm of Big Brother?

While the advanced technology and insights that analytics provide are invaluable to marketers and content designers, there comes a point when it’s important to consider the consumer. Do visitors really want websites that adapt and predict the outcome of their visit? There is no question that the insights and data marketers can obtain via predictive personalization are huge, but using that data is risky because consumers are still wary of targeted ads and marketing that knows too much about them. The average user doesn’t want to be watched, tracked and analyzed as they browse the web.

Marketers need to be smart about learning how to balance the needs of the consumer with their own. They should make a conscious effort to ensure they’re offering something of value in return for gathering personal data. In this way, predictive analytics can benefit everyone involved—consumers experience the tangible benefits of providing personal data, and marketers aren’t perceived as Big Brother.

How does this balance look when applied to a real life customer experience?  A consumer could receive related offers and relevant products via email after a purchase, or see ads featuring content they have already read, or even be offered savings on desired items. All of this improves the online shopping experience, making it easier and cheaper. As long as marketers can demonstrate to consumers that sharing their data will improve their lives, predictive personalization will be viewed in a positive light, as opposed to a potential problem or privacy issue.


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