Three eCommerce brands that nail hyper-personalisation

When 80% of shoppers are more likely to buy from a company that offers personalised experiences, eCommerce brands need to take note. Personalisation has become one of the biggest buzzwords in marketing in recent years, but there’s good reason for this when 74% of online shoppers say they feel frustrated when experiences aren’t personalised.

The leading eCommerce brands have reacted to this demand by creating entire consumer experiences that are personalised every step of the way. Welcome to the age of hyper-personalisation, which is shaping up to be the biggest breakthrough in consumer marketing since mobile.

What is hyper-personalisation?

Back in July, Jeff Rajeck answered this question in his article written for Econsultancy, entitled Are marketers ready for hyper-personalisation? His definition of this relatively new trend in marketing is this:

“Hyper-personalisation is a marketing tactic which leverages artificial intelligence (AI) and third-party real-time data sources to enhance brand messaging with relevant, context-sensitive information. For example, an email may be personalised with the customer’s name, but it could then be hyper-personalised by dynamically changing its content depending on the receiver’s past purchase history, physical location or even the time of day when the email was opened. Ads, too, could be hyper-personalised with CRM data and in-store experiences with a shopper’s online behaviour.”

That’s a pretty good summary of hyper-personalisation and Jeff goes on to offer some practical examples of how to implement it in your marketing strategies. However, the brands that are making big things happen with hyper-personalisation have moved beyond using data to target users and customers with more relevant messaging.

As you’ll see from the examples we’re looking at in this article, the most impressive cases of hyper-personalisation are creating customer experiences that engage with people on an individual basis, add genuine value to the consumer journey and entice people to keep coming back for more.

#1: Use AI to make hyper-personalised recommendations

Amazon’s AI product recommendation system is probably the first example of hyper-personalisation that comes to mind for most people. This is no surprise, considering how prominently it features on the world’s biggest eCommerce platform, but this isn’t unique to Amazon.

Spotify, Netflix, YouTube and countless other content platforms have developed their own AI recommendation engines to suggest new content to people based on what they’re already listening to/watching and what people with similar interests are enjoying.

In the case of Spotify, the goal is to keep users engaged with a software platform (hyper-personalisation isn’t only important for eCommerce), whereas the goal with Amazon and other online retailers is to maximise sales.

By recommending products that might interest individual users, Amazon is able to increase the number of transactions per customer, maximise the value of each customer and turn them into repeat buyers. By 2013, Amazon recommendations were generating 35% of all sales on the eCommerce giant’s platform.

#2: Build a hyper-personalised brand experience from the ground up

While the Amazon recommendations model relies heavily on artificial intelligence, not all hyper-personalisation structures are so dependent on the technology. Stitch Fix is the perfect examples of how you can build a hyper-personalised brand experience from the ground up without relying on heavy algorithms.

We’ve looked at Stitch Fix before in our best eCommerce landing page examples article. The brand offers a truly personalised online clothes shopping experience for its users.

Upon signing up, users provide information about their style preferences and Stitch Fix matches their profile with one of its (almost) 4,000 stylists who make hand-picked recommendations for individual users. This means customers get human recommendations from expert stylists for clothes, shoes and accessories – all of which should match their personal styles, fit perfectly and work together as complete outfits.

Stitch Fix isn’t only creating a personalised shopping experience here, it’s solving many of the problems inherent with buying clothes online; size inconsistencies, viewed products not being available and not being able to try clothes on before you buy them.

Crucially, Stitch Fix doesn’t rely purely on algorithms to crunch user data; it connects people with human stylists who make informed recommendations from genuine expertise.

#3: Bridge the online-offline gap with hyper-personalisation

Starbucks was an early pioneer of hyper-personalisation and also one of the biggest mobile app success stories.

While most retailers have struggled to get mobile apps widely adopted by users, Starbucks’ app has become an integral part of the customer journey, bridging the online-offline divide between customer engagement and in-store orders.

Starbucks’ app is so popular in the US that it handles more payments than Apple Pay, Google Pay and Samsung Pay.

Customers can order before arriving at a store, pay once they arrive using the app, meaning they can simply pick up their order without waiting in line. Convenience aside, Starbucks has also created a real-time personalisation engine that creates special offers for individual customers, based on their order preferences, and a rewards system that regularly gifts customers with a free drink after spending a certain amount.

Turning data into hyper-relevant, useful and engaging experiences

Marketing personalisation has always revolved around targeting users with more relevant messages and this is still a key principle with hyper-personalisation. Artificial intelligence and big data make it possible to target individuals with highly-specific messages and even predict which kind of offers they’ll respond to as they progress along the consumer journey.

For marketers, this is probably the most compelling aspect of hyper-personalisation.

However, the brands we’ve looked at in this article go much further than targeting users with relevant messages. They build an entire customer experience that revolves around personal interactions – an infrastructure that makes those personal messages genuinely valuable to the end user.

By creating these environments, customers are highly-engaged between purchases and more receptive to the targeted messages they’re being sent. Relevance is crucial here but the wider customer experience these brands have created make their messages more compelling. This is what marketers should be striving for with hyper-personalisation.

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