How to Use Hyper-Personalization Without Creeping People Out

Personalization is a big deal in modern marketing. Research has shown that nearly three-quarters (72%) of consumers only engage with personalized messaging and 80% of shoppers are more likely to make ecommerce purchases from a company that offers effectively personalized experiences.

It's clear that if you get personalization right, it can make a big difference to everything from initial lead generation to long-term customer loyalty.

The benefits can be even greater with hyper-personalization, which uses cutting-edge technologies like AI to deliver the most relevant and contextual experiences to customers in real time.

However, this approach does bring certain risks, such as coming across as intrusive or 'creepy'.

What is hyper-personalization?

More advanced than standard personalization, hyper-personalization harnesses the potential of AI, real-time data and behavioral indicators to help you achieve maximum relevance when providing content suggestions, product recommendations and service information to customers.

Conventional personalization involves practices that should now be viewed as the norm, like addressing people by their first name in emails and recommending products based on their previous purchases.

Hyper-personalization, on the other hand, seeks to be more responsive and relevant in real time, with the help of accurate data that gives you an in-depth understanding of the customer and their unique habits and preferences.

One example of how hyper-personalization can work is if a retailer wants to send a follow-up message to a customer who has spent time browsing or searching for specific products online, but hasn't completed a purchase.

Analyzing data on this individual could show:

• If they have a preference for a particular brand
• When they spend the most time browsing and purchasing
• The communication methods and channels they use most

The company can then send a personalized message, in the customer's preferred channel, at the time they're most likely to engage with it, highlighting current offers or products available from their favorite brands.

Hyper-personalization success: two great examples

Some of the best-known and most successful brands in the world are powerful examples of what can be achieved with effective hyper-personalization.

Two companies that have got their strategies down to a fine art are Amazon and Netflix, with the former reportedly gaining more than a third of its conversions from its carefully calibrated recommendation engine.

Amazon presents every registered user with a personalized homepage and also uses tools such as its 'Frequently bought together' section to make recommendations to customers and drive sales.

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Netflix has also spent years refining an advanced recommendation system that uses behavioral data, predictive analytics and other methods to build detailed pictures of what individual users like and what they might want to watch in the future.

Every time the company makes a relevant, useful suggestion, it demonstrates the value of its service and strengthens its relationship with the customer.

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How do you avoid being creepy?

Personalization is an undeniably important feature of the modern marketing landscape, and when it's done well it delivers huge benefits. But it's also an area that comes with certain challenges and potential risks.

This is a complicated and sometimes contradictory space to navigate. Nine out of ten consumers say they're willing to share behavioral data for a cheaper and easier brand experience, but according to SmarterHQ’s Privacy and Personalization report, 79% also have concerns that companies know too much about them.

Research by Gartner has also shown that, while most marketers are aiming for high standards in one-to-one personalization, they often fall short, and the price of failure can be steep. More than half of the 2,500 people surveyed by the firm said they would unsubscribe from brand communications and 38% would stop doing business with a company if they considered its personalization efforts creepy.

One of the most important steps you can take to avoid this problem is to demonstrate how use of data and personalization can provide genuine value to the customer. This could be through highly relevant and timely recommendations - as demonstrated by Netflix or Amazon - or what Gartner calls ‘tailored help’.

The company defines tailored help as targeted messages that provide maximum assistance with as few data dimensions as possible, striking a balance between "too inaccurate on one hand and too creepy on the other".

The risk of coming across as creepy is particularly high when people simply don't understand or aren't aware of how brands know so much about their browsing and buying activity. It's therefore crucial to be completely transparent about how you go about collecting people's information and tracking their online behavior.

Here's one example of a simple way to be upfront and honest about how you use cookies and other methods to track user activity and consequently deliver personalized experiences:

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Prioritizing transparency and the delivery of value to the customer will significantly improve your chances of success in hyper-personalization, which in turn could lift your company to new levels of marketing success and ROI.