The continued advancement of retail technology and ecommerce have set new standards for a quality online shopping experience. Todays’ customers expect seamless omnichannel shopping experiences that are highly personalized. In fact, 80% of customers say they’re more likely to purchase from brands that personalize, according to Deloitte.
However, most ecommerce retailers today have already invested in personalizing their online shopping experience — so why are retailers still struggling with customer loyalty and sales? Mass adoption and changing customer expectations have raised the bar. Simple personalization is now an expectation, not a differentiator. And in today’s ecommerce landscape, where retailers are already anticipating a discount-focused holiday shopping season, how can brands stand out and win sales this holiday season?
Retailers cannot keep simply doing what they have done before. To stand out and win customers this holiday shopping season, they need to start delivering hyper-personalized ecommerce search experiences.
What is Search Hyper-Personalization?
Hyper-personalization, also known as individual personalization, aims to provide customers with one-to-one personalized experiences. Traditional demographic segmentation divides customers into large pools based on factors such as age, gender and location, with recent advances starting to look at segments based on user behavior and interactions. However technology is now at a point where individual personalization at scale is able to help retailers dynamically create custom shopping experiences for every user.
By leveraging data such as past purchase history, viewed products and other clickstream data, ecommerce retailers can use advanced data analytics and AI to uncover deep insights into individual preferences, shopping behaviors and interests. In turn, this data can be used to deliver individually personalized experiences at every touch point — from personalized product recommendations to tailored marketing campaigns to search results that are ranked and ordered according to their individual preferences.
For example, suppose a customer is searching for a date night dress. Using traditional segmentation and targeting, that client would be shown a selection of products aligned to their demographics, meaning a female shopper in her 20s would see different dresses than a woman in her 40s. With traditional segmentation, two female shoppers in their 20s would see the same date night dresses, as they’re part of the same segment.
Hyper-personalized search experiences, on the other hand, dynamically rank and re-order search results based on individual customer preferences such as color, brand, style and more. Meaning those same two shoppers in their 20s would potentially see very different results when they type in “date night dress”. One customer may see more classic, little black dress-type results based on her browsing history, while the other may see more flowy, bohemian options that are aligned to her preferences.
This is true personalization, delivering a unique experience to each customer based on their purchasing habits. In some instances, it can even be leveraged to create “upsell” opportunities that did not previously exist. In the example above, in a true 1-to-1 personalized experience, in addition to the personalized search results, these two customers would receive different complementary product recommendations — including shoes, handbags and other accessories — to help them complete the look.
Hyper-Personalized Ecommerce Experiences Rely on Artificial Intelligence
Hyper-personalized search relies on the power of AI. AI-powered solutions have the ability to process data in real time, dynamically updating and adjusting the customer experience for each individual shopper. This allows them to deliver offers and recommendations that match where the customer is in their online shopping journey at nearly any given moment.
However, not all AI solutions are the same — especially when looking at ecommerce search and product discovery solutions. 69% of customers will use the search function on a website, making it the most common way to discover products. It’s also the most underutilized space for delivering a hyper-personalized ecommerce experience.
Legacy search solutions make it harder for ecommerce retailers to deliver individually personalized experiences to their customers because they are built on keyword-matching technology. These older engines require thousands of manually generated search rules to deliver somewhat relevant search results — especially for broad or head-term queries. While some more modern solutions layer AI on top of these legacy engines to attempt to deliver a relevant and personalized ranking of product search results, these solutions are ultimately limited by the legacy technology at their core. And the human tooling provided in these solutions simply is not powerful enough to compete with AI technology in terms of speed, efficiency or scale.
More modern search and product discovery platforms, however, are built solely on AI, with the ability for humans to provide oversight. The search engine they use is completely powered by AI as the foundation, so that merchandisers do not have to create thousands of rules to configure the engine. Trained on vast arrays of data, it possesses a superior understanding of user intent and context. As a result, the algorithms that power AI-first technologies are dynamic. They can learn and update, continually refining their output in real time, based on user data.
It is this technological foundation that allows these modern solutions to deliver the type of hyper-personalized ecommerce experiences outlined above. Each search is run through multiple calculations, including relevance, buyability and personalization, before being presented to the customer in revenue-maximizing order. With the market louder and more crowded than ever, hyper-personalization is a critical way to differentiate your brand experience from the rest of the pack.
Start Hyper-Personalizing for the Holidays Now
When compared to the segmentation and simple personalization strategies we see today, hyper-personalization may sound like an invention for the future. However, the technology to deliver hyper-personalized ecommerce shopping experiences already exists, and forward-thinking retailers are using it today.
Early holiday spending estimates are currently hovering at around $1.3 trillion this year. As such, it is a critical time to invest in next-gen solutions to deliver a quality shopping experience. Retailers must turn to hyper-personalization to meet customer expectations and avoid losing sales to the competition this holiday season. By prioritizing individual personalization now, retailers can future-proof their businesses for the holidays and beyond.
Arv Natarajan is Director of Product at GroupBy, helping to craft the vision and direction of the GroupBy product discovery platform. Natarajan brings over 15 years of experience working with enterprise customers in project delivery, customer success and product management across various industries.