How Personalization Leads to Delightful User Experiences – 5 Companies Doing It Right

People like to be recognized. People enjoy being seen, acknowledged, and remembered. Can you recall the feeling of walking into a neighborhood store or restaurant, and having the staff call you by name? “Emily, so nice to see you again!” or “Will it be the usual, Mr. Sawyer?” It’s satisfying. More than that, it implies a bond between the customer and the merchant. Even if you don’t recall their name, even if you don’t remember giving them your name, the assumption that builds in your head is one of familiarity, closeness and trust. This is both a way to indicate respect for a customer AND a way to make the customer trust the merchant.

Digital experiences work best when they emulate human experiences. According to research from Salesforce.com, more than half of all online consumers expect offers to always be personalized.

Personalization goes much deeper than pre-loading the customer’s name on an email, or at the top of the webpage after sign-in. Here are some examples of some great personalized customer experiences:

Pinterest’s first feed

Pinterest

Pinterest has a unique way of wowing its audience in the first impression. As a new user creates an account, they’re asked a series of questions Pinterest uses to identify their interests, their location and their demographics, and the app uses this to deliver a very personalized first board experience. Faced with this, a new user feels immediate value from the brand, feels at home, and is much more likely to stick around and continue expanding their interaction, which further feeds Pinterest’s AI – leading to more personalization. It’s a self-feeding satisfaction loop.

A couple of years ago Pinterest added a whole new layer to this by creating a personalized shopping hub, with curated product recommendations based on user pins.

Shutterfly places your photos on its products

Shutterfly

Shutterfly is an app that allows photography lovers to create photobooks, frames, coasters, calendars, canvas bags, mugs and other merchandise with their own photos on them. And the app has a terrific way to entice the user to participate. As you create an account, the app asks you for permission to access your photos on your phone. It then looks for photos with faces on them, and shows you what these photos would look like on mugs, bags and other items. It’s assumptive closing; it’s predicting your wishes; it’s a solicitous retail manager saying to you, “no, no, it’s no trouble at all, let me show you…”

Target targets expecting moms

Target

People like routine. Once a consumer’s shopping habits are ingrained, it’s difficult to change them. However, big changes in your life, such as life events, create the need for new patterns. Target marketers know this, so they assign new customers a Guest ID number and track interactions with the brand. They look at ethnicity, demographics, job history, and buying behavior. Buying behavior allows Target to identify customers planning a wedding, or in early pregnancy. During such events, buying habits are disrupted, as people are buying products they hadn’t needed in the past. This allows Target to present these buyers with personalized special offers.

This could be a two-edged sword. Such a high level of personalization could greatly alienate a user if the predictions are inaccurate, or could spook a consumer if the offers are too “on-the-nose,” making them feel they’re being spied on. So far, Target has been able to walk this line with grace – which has increased their bottom line.

Spotify’s customized user accounts

Spotify users can create their own playlists. In fact, the app encourages this practice. Over time, users acquire an ‘equity’ on the app – the app ‘knows’ them. In fact, the app recommends new music to them based on their interests. This creates a stickiness and an emotional commitment that makes Spotify users very loyal to the brand. Users don’t want to let go of the customized experience they are served based on the intellectual equity they have accrued.

Spotify takes this even further. Using machine learning, it woos its user base with the app’s “Discover Weekly” feature, presenting the user with music they’re likely to love. Who needs a boyfriend when Spotify gives you a new mixtape once a week?

It’s this unique combination of what you know, what they know about you, and what they guess about you that you didn’t know about yourself that can lead to moments of delight. Like a grandma guessing the perfect gift or a good friend suggesting a movie, good personalization has an element of gamification, which Spotify captures perfectly with their ‘Discover’ feature. Oskar Stal, VP of Personalization, nails it in this article. Stal says they could “play your favorite 20 songs on a loop – but that would mean you’re not discovering anything.” He says, “you enjoy Spotify more if you discover more.”

Amazon’s recommendations

Amazon

When it comes to personalized recommendations, Amazon remains the GOAT (greatest of all time) – at least for now. “If you liked that, you might also like this” has been a staple of Amazon user interactions for over a decade – and it keeps improving.  

The ultimate win-win

Personalization

This level of personalized, curated experience increases satisfaction, creates loyalty, and boosts revenue – as it affects consumers’ buying habits. Users do not buy what they haven’t thought of. When a website does the thinking for them, and suggests a song, a clothing item or a gadget the user may like, it creates a certain level of delight in the user – similar to receiving a gift. It’s the “I didn’t even know I needed it” kind of satisfaction. Done gracefully, this feels like added value in the consumer’s mind. Consumers reward such value with a fuller shopping cart, increased buying frequency, positive word of mouth, and an overall higher consumer lifetime value. It’s the ultimate symbiotic win-win: Give them what they want, and they’ll keep coming back for more. Give them what they didn’t even know they wanted, and they’ll never leave you.

Yes, But How?

You might be thinking that all of these examples are of multi-billion dollar companies with vast resources for machine learning and artificial intelligence. And you might wonder how your small or medium-sized ecommerce company can match such efforts. Think about the fact that all of these robotic efforts are intended to replicate organic interactions between humans. You can create a delightfully personalized experience by segmenting your content, in emails, interfaces and web pages. For this, you’ll need user research data. 

Bizrate’s Voice of Customer Solutions can help you better understand your customers and what they want, at no cost. You can then use what you learn to improve your customer experience, and even personalize it by segment. This segmentation can be demographic (by gender, by age, by geo location) or behavioral (shopping frequency, items purchased, etc.). 

The more that you indicate you SEE and UNDERSTAND the customer, the more delighted and committed they will be to shopping with you.

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