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How eCommerce leaders use AI to woo their customers with personalization

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Once upon a time, customers simply walked into stores and met a friendly shopkeeper who helped them out. No one hears you walking the halls of those buildings… not anymore. The world shifted to online shopping.

Unprecedented growth occurred in the eCommerce sector amid the COVID-19 crisis. And Amazon has spoiled us to the point that we expect extreme personalization. If we don€™t get it, we just go elsewhere.  

If you don’t have a personalization strategy, you are losing 75% of shoppers who leave your website because they get frustrated by irrelevant offers. Website personalization helps to make the purchasing process faster, get better deals, and curb information overload. Before we dive in, let€™s make sure we€™re all on the same page.

What is personalization?

Personalization is the process of creating customized, pleasing experiences for visitors. Every customer sees a slightly different version of your website which is defined by the particular audience segment the shopper falls into. These segments are based on:

  •         Past purchase history and average order value 
  •         Demographics (age, ethnicity, location, income level)
  •         Psychographics (interests, habits, emotions, attitudes)
  •         Visitor type (new visitors or returning visitors)
  •         Traffic source (referral sites, social media, direct or from paid link ads)
  •         Site engagement (browsing time or number of pages viewed)
  •         Current cart profile
  •         And so much more

  

When a store suggests products that supplement the items in your cart, that€™s personalization. It allows you to create unique shopping experiences tailored to each particular user. 

7 brilliant eCommerce personalization examples to boost sales

Ever hopped on a website and thought: €œThat€™s exactly what I was looking for!€ There€™s a good chance that the retailer knew who you were, why you were visiting, and what you were seeking. Let€™s take a look at eCommerce personalization done well.

  • Amazon uses personalization every step of the way

Amazon goes above and beyond to understand customers€™ buying habits. By taking a page from Amazon’s book, brands can leverage winning strategies for their personalization efforts.

Amazon uses deep learning to determine which products a customer is likely to purchase next. The items customers have bought, viewed, and reviewed are taken into account. Amazon weaves seasons and holidays into its recommendation algorithms. It indulges with clients on a personal level €“ every time they land on the site, they€™re greeted with a homepage that seems to be specially designed for them. 

  • Everything Netflix does is driven by smart AI algorithms

80% of what people watch on Netflix comes from their personalized recommendation algorithms. Machine learning algorithms process multiple data points and recommend shows/movies that match users€™ tastes.

The platform strives to display the right content at the right time. It uses time as a strong variable to recommend shows. For instance, Netflix suggests shorter shows when users log in late at night.

  • Spotify€™s Discover Weekly playlists

€œDiscover Weekly€ helps to find new music based on a person€™s taste. Spotify collects data about the songs people listen to and creates unique playlists. This playlist combines personal listening data with data from users that have similar listening tastes. If Spotify notices that two of your favorite songs tend to appear on playlists along with a third song you haven€™t heard yet, it will suggest that song to you.

The algorithm ignores temporary spikes in listening activity since many people share their logins. All new listening activities do not lead to immediate changes in your playlist.

  • Chubbies uses comedy to build a base of die-hard customers

Fast-growing retailer Chubbies combine retargeting ads with a boosted video. But instead of using video to highlight their products, the brand entertains their shoppers. Chubbies don€™t create content just to get a sale €“ they want to get a laugh out of their customers.

Chubbies€™ videos are designed for the brand€™s target customer. The brand takes into consideration what kind of videos their shoppers would find funny, and what would be timely. The company gathers behavioral data to discover trends and share videos that are more likely to resonate with their customer base. 

  • Levi€™s chatbot assistance

One of the drawbacks of online shopping is being unable to speak to an assistant. Levi€™s navigate this problem with its chatbot, Ask Indigo. It suggests clothing items based on the user€™s preferences.

By speaking to customers directly, even through a voice chat, the brand enhances interaction and offers customers relevant products.

  • ASOS changes the whole website navigation based on past user engagement

ASOS employs dynamic interfaces, which change depending on what pages users have visited before. For example, if a customer viewed items in the women€™s clothing part of the site, then the next time the women€™s section would be automatically presented, without having to click through.

  • EasyJet got emotional with personalization

For its 20th anniversary, EasyJet released a personalized ad campaign that was built around data on each customer€™s journey throughout the years. Emails contained images and links that showcased each customer€™s story from their first-ever EasyJet flight to their flights to come.

EasyJet transformed customer data into emotional anniversary stories to creatively display customer€™s individual travel history over the last 20 years. To make it truly personal, the company created a model that profiled all of the destinations customers had been to and suggested similar ones based on easyJet€™s destination profiles, and also where other users with similar travel patterns had been. The extract that powered this campaign contained over 1,000 lines of code, resulting in 12 million-plus emails that were completely unique. The result? EasyJet saw open rates over 100% higher than that of their average newsletter. And 7.5 percent of customers made a booking in the next 30 days.

Critical success factors of a personalized customer journey

It€™s so much more than just product recommendations or using someone€™s {firstname}. When it comes to selecting an eCommerce personalization strategy, here are 3 crucial abilities:

  • In-depth behavior tracking

The ability to respond in real-time to actions customers have taken is vital for a successful personalization strategy.

  • Dynamic content generation

Your eCommerce personalization tool should also enable you to generate dynamic content. By offering relevant content, you enhance the shopping journey of your customers.

  • Powerful analytics & segmentation

It should be able to segment and group your visitors based on their web behaviors and target them with relevant information.

 

To wrap up

How effective is eCommerce personalization? The study by Segment revealed some truly impressive numbers:

  • 49% of shoppers purchased a product they didn€™t originally intend to buy after receiving a personalized recommendation.
  • 44% of consumers said they would likely become repeat customers if their experience was personalized.
  • 40% of customers purchased something more expensive because their recommendations were personalized.

Personalization allows you to create an exceptional shopping experience tailored to each customer. It enables you to offer more relevant product information, leading to increased conversion rate, improved average order value, time savings in your sales department, and boosted ROI. No matter what industry you€™re in, personalization seems to be the way to your customer€™s heart.