The shift in consumer preferences and technological advancements is transforming the way people shop online. E-commerce businesses are using artificial intelligence to win over customer trust and loyalty through effective personalization. When there are plenty of products on offer, it’s highly important to showcase the right product to the right consumer.
AI helps e-commerce companies to recommend products that perfectly suit the unique needs of individual buyers. It enables customers to search for products through conversational language and images. In this article, we briefly describe e-commerce personalization and discuss the top 10 AI-driven e-commerce personalization examples.
Table of Contents
What is e-commerce personalization?
E-commerce personalization is a method of creating exclusive user experience through customized offers, product recommendations, etc. based on user purchase history, browsing pattern, demographics, and any other personal information. Before, we proceed to the e-commerce personalization examples, here are a few quick tips.
- Customer Segmentation is critical when it comes to personalization. You need to segregate customers according to frequency of visiting, loyalty, and engagement level.
- Implement 'Theory of Positive Reinforcement' by recognizing customers who have been visiting your website quite frequently and making purchases off and on. This encourages users to repeat their actions, which builds brand identity and boosts your revenue.
- Motivate users to sign up by sending customized messages with an exclusive discount for first time users.
Top 10 AI-driven e-commerce personalization examples
1. Sensitivity to seasonal changes
Seasonal changes affect e-commerce sales, site traffic, and conversions. There is undoubtedly a correlation between online shopping trends and seasonal changes. When the weather is hot and sunny, e-commerce companies see a spike in sales for cold beverages, sunglasses, floral shift dresses, etc. Similarly, when it’s chilly and snowing, it will positively impact sales of leather jackets, pullovers, boots, moisturizers, etc.
AI-based personalization helps e-commerce companies to showcase products based on seasonal market demand. Below is an example of products on offer by Dior for Summer 2020.
Here’s a glimpse of Spring forecast by Dorothy Perkins.
2. Browsing Behavior
As you login to an e-commerce site you are suggested with products as per your previous browsing history. So how does this happen? E-commerce sites use AI to collect information about prior browsing behavior. Suppose a user has previously searched for new eBook releases, within the ‘Suspense or Thriller’ category, he will get to see more of it. Here is a screen grab of eBook collection by John Scalzi on Amazon.
3. Personalized emails
AI is used to study and analyze consumer behavior to generate customized newsletters and follow up emails for individual subscribers.
Companies can send tailor-made emails to customers with abandoned shopping carts and encourage them to pick up from where they left. Eg: Spotify Premium sends a customized message offering 3 months of free subscription, this is bound to re-engage existing users, keep customers active, and reduce churn rate.
4. Geo-location targeting
Targeting customers and delivering them content based on their geographical location is Geo-targeting. E-commerce applications are using AI for automatically inferring a user’s Geo-location, thereby facilitating customer segmentation based on buying behavior in a country/city. Based on the user location, e-commerce sites serve content in preferred language. When local needs are addressed in the customer’s native language, it leads to optimal conversions. Hence e-commerce sites target specific audiences based on their location and preferred language.
Another use of Geo-targeting is that it helps customers know whether products can be shipped to their location or not. You need to enter your shipping destination before you make any purchases as some items may not be available for sale in certain regions.
5. Reduce return rates and improve customer satisfaction
As processing return takes time, it increases the financial burden for e-commerce companies. Online fashion brand Asos leveraged AI capabilities to lower instances of return. Asos uses machine learning algorithms to offer optimum size recommendations to reduce chances of return and offer seamless shopping experience.
Similarly Starbucks introduced ‘My Starbucks Barista’ that enables customers to order through a simple message or voice command. This has improved customer satisfaction levels and reduced any kind of food wastage or returns.
6. Virtual shopping assistants
Now, you no longer have to rush to the store early in the morning for milk and cereals. You can just command Alexa and your priorities are sorted. You can also pre-book an Uber for pick and drop from an event using Alexa’s voice recognition capabilities. AI is providing creative solutions to online retailers to improve the shopping experience through ‘deliver-in-moment’ personalization.
7. Automated upselling
Won’t it be great if an e-commerce platform anticipates a customer’s next shopping stage and engage them accordingly? AI has helped e-commerce companies by identifying shoppers with high customer lifetime value and automating customized upsells depending on their buying patterns.
Most people add more products into their cart through personalized suggestions offered before they checkout. Below is an example of how Amazon attracts customers to buy baby products similar to what’s already in the user’s cart. Hence, if a user buys Chicco comb and brush, he/she will be suggested to add other items related to baby grooming.
8. Remind customers about abandoned carts
Shopping cart abandonment is a matter of serious concern for e-commerce sellers. Some people add items to their shopping cart and abandon it. Personalized AI-integrate bots can send frequent reminder messages for faster check-out and boost conversions. Chatbots offer a much higher click-through-conversion rate than emails. Bots use conversational language to build a connect with customers and encourage them to successfully complete their purchase.
9. Use Style Finder
Consumers love to sport a different look each day. So, it’s best to provide them ample options and leave it on them to decide what they will pick. Using AI, different e-commerce platforms showcase the latest trends for each month.
Below image shows offers for the month of March - ‘Women’s Day 2020 Collection’, ‘Editor’s Top 50 picks’, and ‘Best Spring New Arrivals.’
StitchFix uses AI to offer personalized styling for all its consumers every month, all they have to do is take a style quiz.
10. Tackle fake reviews
Customer reviews help in establishing trust for online buyers. Recently, there have been cases of fake reviews or ‘astroturfing’, where customers are made to believe in false online reviews about products through misleading testimonials. Most reputed e-commerce companies, including Amazon implement AI to track fake reviews by focusing on verified customer purchase reviews and product ratings.
To sum up
AI is set to make a huge impact on the e-commerce business in the future. It will revolutionize the way users search and purchase products online. In the age of social media and short attention spans, AI-enabled e-commerce platforms will reinvent the retail landscape. If you are in the e-commerce industry and actively looking to incorporate artificial intelligence and machine learning capabilities, Skyl.ai can accelerate your digital transformation process.
Check out the various solutions that can be built using Sky Platform here.