Beyond the shopping cart: How personalization powers up e-commerce growth
Beyond the shopping cart: How personalization powers up e-commerce growth

Beyond the shopping cart: How personalization powers up e-commerce growth

E-commerce has come a long way, reshaping the way we shop and transforming the global economy. Especially in the last two decades, it has become a world of endless possibilities, letting people shop for their favorite products from anywhere, in seconds, making personalized recommendations magically appear on any of their screens, tailored to their unique tastes and preferences.

Just to add some numbers to this perspective, according to Statista, “in 2021, retail e-commerce sales alone have amounted to approximately 5.2 trillion U.S. dollars worldwide. This figure is forecast to grow by 56% over the next few years, reaching about 8.1 trillion dollars by 2026.” At the same time, this year smartphones accounted for over 70% of all retail website visits worldwide, and in turn, also generated the majority of online orders compared to desktops and tablets.” Gone are the days of crowded malls and long checkout lines. Today, a single click can bring the world’s marketplace right to your doorstep. But how did we get here? Join us on this insightful journey through time as we unravel the captivating story of how e-commerce has shaped our lives and revolutionized the way we buy and sell.

How it all started…

In the not-so-distant past, the concept of purchasing goods with just a few clicks seemed like a distant dream. It was the early 1990s, when a handful of visionary entrepreneurs saw the untapped potential of the internet and set the stage for what would become the e-commerce revolution.

One of the pioneers is surely Amazon. Founded by Jeff Bezos in 1994 as an online bookstore, Amazon quickly expanded its offerings to include a vast array of products. Bezos’ audacious vision of building the ‘Earth’s biggest bookstore’ paved the way for what would eventually become the world’s largest online marketplace.

Around the same time, another trailblazer emerged: eBay. Started in 1995 as an online auction platform, eBay transformed the way people bought and sold used items. It unleashed the power of the peer-to-peer marketplace, allowing anyone to become a seller and connect with buyers from around the world, thus empowering individuals to turn their unwanted items into cash.

Meanwhile, on the other side of the globe, Alibaba was quietly making waves in China. Founded by Jack Ma in 1999, Alibaba recognized the immense potential of e-commerce in a country that was rapidly embracing technology.

These three are some of the biggest game changers that redesigned the shopping experience and rewired the retailer mindset. They expanded the market reach, set the bar extremely high for customer experience/engagement, streamlined the supply chain management, and capitalized on data-driven insights at unprecedented levels. On the other hand, they also generated fierce competition, pricing pressure, and the need for retailers to constantly adapt to changing consumer expectations and emerging technologies.

The next frontier in e-commerce: it’s personal(ization)

Everyone is different and has certain needs. Thus, providing your customers with relevant products and a more engaging shopping experience is a real challenge. Here’s where personalization and recommendation systems play a major role.

In a vast digital marketplace with countless options, personalization cuts through the noise and helps consumers find products that genuinely resonate with their preferences and needs. This targeted approach increases the chances of conversions and repeat purchases, fosters customer trust, loyalty, and long-term relationships.

Personalization addresses decision paralysis and helps consumers overcome the overwhelming number of choices available. By delivering relevant recommendations, personalized e-commerce platforms save consumers time and effort in searching for products that meet their specific requirements, and thus increases tremendously the quality of customer experience.

It’s all about the data.

Data-driven personalization plays a pivotal role in enabling personalized recommendations in e-commerce. E-commerce platforms should be able to leverage various sources of user data, such as browsing history, purchase behavior, and demographic information, to gain valuable insights into individual customers. This data forms the very foundation for creating personalized experiences that cater to specific preferences and needs.

By collecting and analyzing user data, e-commerce platforms can understand customers’ browsing patterns, product interests, and purchase habits. For example, if a customer frequently searches for and purchases sports equipment, the platform can personalize their experience by suggesting related products, such as athletic apparel or fitness accessories.

The collection of user data can be done through various methods, including cookies, tracking pixels, user accounts, online surveys or even advertising. This is one of the reasons why privacy and data security are of paramount importance in data-driven personalization. E-commerce platforms must ensure they adhere to privacy regulations and obtain proper user consent for data collection and usage.

Collaborative and content-based filtering

Collaborative filtering is a commonly used technique in recommendation systems for analyzing user behavior and preferences. It makes recommendations based on similarities with other users who somewhat share the same tastes and preferences. By examining patterns in user interactions and finding users with comparable interests, collaborative filtering can suggest items that the current user may find appealing based on the preferences of like-minded individuals.

Content-based filtering, on the other hand, focuses on the characteristics and attributes of the products themselves. Algorithms analyze product descriptions, categories, and attributes to understand the content and context of each item. Based on this analysis, the system suggests similar items to users, considering their past interactions and preferences.

Some e-commerce platforms have gone the extra mile combining the two into a hybrid recommendation system which helps them gain even more insight into their customers’ needs, preferences and desires, and act accordingly.

Spotify is one of them. Their algorithm learns from the user’s listening habits, likes, dislikes, and mood to recommend songs and artists that match their taste. Spotify also uses content-based filtering to analyze the audio features of songs, such as tempo, genre, and mood, to create playlists based on different themes and occasions.

AI & ML gain more ground

Artificial Intelligence and Machine Learning can help create customized and relevant experiences for users based on their data, preferences, and behavior. For example, AI and ML can help recommend products, content, or services that match the user’s interests and needs.

Thread is a UK-based fashion company that uses AI to provide personalized clothing recommendations for each customer. Customers take style quizzes to provide data about their personal style. Each week, customers receive personalized recommendations that they can vote up or down. Thread’s AI algorithm uses that data to find patterns in what each customer likes and tailor its recommendations.

Ethics in e-commerce

In recent years, the growing importance of personalization and recommendation systems in e-commerce has raised significant challenges and ethical considerations. Sure, you get what you want and how you want it, but at what cost?

The rising concerns are focused on data privacy, as users’ personal data is often collected and used to tailor recommendations, as well as on the risk of algorithmic biases, which can perpetuate discrimination and create unfair advantages for certain groups.

To address these issues, there is a growing need for greater transparency in how recommendations are generated, ensuring that users have a clear understanding of the algorithms and data sources used to influence their online shopping experience.

Companies should prioritize data privacy, actively address algorithmic biases, and commit to transparency in their recommendation algorithms. By doing so, they can provide more responsible and customer-centric e-commerce experiences that not only boost sales but also build trust and foster long-term customer relationships.


There is no doubt that the future of e-commerce looks bright for those who pay attention to their customers’ needs and interests. The adoption of new technologies, such as AI, AR, voice assistants or chatbots, can enhance the online shopping experience, improve personalization, increase efficiency, and ensure security, but so will the way all of them are handled.

At the same time, companies need to take into consideration the emergence of new business models, such as social commerce (aka. the use of social media platforms), Q-commerce (products delivered fast & convenient), subscription services, and circular economy (using resources that minimizes waste, pollution, and environmental impact), that can cater to the changing consumer preferences, demands, and values.

As e-commerce continues its remarkable evolution, the seamless integration of personalization and recommendation systems remains pivotal, not only as a driving force for industry growth but to empower consumers with tailored, secure, and ethical shopping experiences.