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Website Personalization: the Impact of AI on CX

Website Personalization: the Impact of AI on CX

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Website Personalization: the Impact of AI on CX

Website personalization works to create unique customized experiences for individual visitors, aiming to move them further along the customer journey. With statistics showing that 80% of customers are more likely to buy from a company that provides a more tailored experience and 66% of customers expecting brands to have an understanding of their individual needs, the demand for greater personalization is not one to be ignored.

Personalizing digital experiences helps visitors navigate website information more easily, improves engagement and reduces friction. AI-driven experimentation and personalization achieves this by learning from what visitors are clicking on as they navigate a website and serving relevant experiences that encourage progression in the funnel.

In the past website personalization has been largely limited to recommendations based on past buying behavior or consumer segmentation. This approach has worked well for market leaders such as Amazon that have vast resources and the ability to leverage customer data quite accurately. Many companies that have tried a similar approach have not had the same level of success. These failed attempts at personalization have often alienated and annoyed customers instead of getting them to buy and become loyal brand advocates.

This is just one of the reasons customers are calling for more personalization. They’re frustrated and tired of being targeted with information that’s irrelevant. They know companies have significant amounts of data on them and their buying behavior and they expect better digital experiences as a result.

Trying to achieve personalization at scale using manual tools is both time consuming and impractical. Fortunately artificial intelligence (AI) is a technology that excels at handling complexity. A key element of AI-driven experimentation and personalization is its ability to learn from online behavior. This generates actionable insights that serve to guide personalization strategies.

Website personalization examples

Personalization is often a key focus area for brands that are customer obsessed. Market leaders such as Netflix, Amazon and Tesla are in part responsible for increased demands in website personalization. They have shown consumers what’s possible when technology and strategy combine with a focus on improving customer experience. Despite not having the same resources available, there is still much to be learnt from their personalization success:

How Tesla disrupted the automotive industry with personalized CX

Tesla didn’t go after personalization just because it was emerging as a consumer trend. Rather they saw personalization as a way to generate better connections with customers and retain customer loyalty, disrupting the automotive industry in the process. Tesla identified that gaining a better understanding of what customers really wanted as an important driving factor of personalization. This required leveraging customer data more effectively and investing heavily in technologies to better understand what the motivations are behind buying decisions.

What many brands are only just discovering, Tesla saw as a primary challenge to solve for. This is that regardless of product or industry, the marketplace is highly dynamic. If a brand is not finding ways to keep track and generate insights from customer responses in real time as customers progress in the journey, there’s a strong possibility of getting personalization wrong. On closer inspection it quickly becomes apparent that just about everything Tesla does is about making better use of customer data to enhance and personalize customer experiences.

Here are two examples of how Tesla approached personalization:

Discarding traditional industry distribution channels Tesla chose to go direct-to-customer (DTC) instead. Part of this was to place Tesla showrooms inside shopping malls to meet consumers where and when they’re in a shopping mindset. This is complemented by optimizing digital experiences across all channels. With the majority of consumers starting their buying journey online, offering detailed product information that’s easy to navigate is very important. The convenience of being able to find relevant information quickly and easily helps to reduce buying anxiety. This clearly demonstrates a respect for what’s important to customers, which is their time. Modern life is incredibly busy; no one wants to waste time searching for information to help them make a decision. Understanding that even the smallest point of friction has the potential of resulting in a negative experience, Tesla focusses on each small detail that serves to continually improve personalization for customers.


In the customer journey, Tesla seeks to empower potential buyers by providing different channels of contact to use to ask questions or even book a test drive.The aim of a test drive is to experience what it's like to own a Tesla car and this goes far beyond just the driving experiences and special features that personalize it. The aim is to consistently deliver more value to customers with no effort to them. Post purchase touchpoints include a detailed orientation of the car and basic maintenance and any software upgrades happen automatically. Everything is designed to be effortless and this makes the buying (and owning) experience feel more personalized.

How Amazon wrote the book on website personalization

In terms of e-commerce and personalization of the customer experience, there’s little debate that Amazon is one of the companies that set the benchmark others aspire to achieve. A prime example was seeing how their revenues soared when the pandemic hit. While most brands were still trying to navigate out how to take their product and service offerings online, Amazon shifted into cruise control and watched the millions roll in. While Amazon may be one of the first websites consumers go for online shopping, the website took years to achieve the position of market leadership.


It took many years to turn the customer experience dream into reality but it was a deliberate effort focussing on creating memorable customer experiences so that customers would return to buy more and be so impressed they’d refer friends too. This would result in more customers buying more. The more customers bought, the more suppliers would want to sell. The greater the variety of products and more competitive pricing. This would then come full circle in the ability to improve CX. The huge range of products meant finding ways of matching these to customer needs and preferences. Honing in on what influenced buying decisions Amazon introduced customer reviews and recommendations. These seemingly simplistic strategies were highly successful in personalizing e-commerce experiences because Amazon had the data infrastructure in place to make it work.

How Netflix redefined TV with personalization

Netflix took comments such as “200 channels and nothing to watch” to heart and set about personalizing media consumption. Instead of having to surf TV channels to find something suitable to watch, Netflix enables users to create personalized profiles aligned to specific interests, making it easier to find something of interest to watch. Building on the idea of personalization, Netflix learns from what consumers are watching and makes additional recommendations based on changing interests over time. While many new and existing media companies have entered the competitive space of media streaming, few have achieved the market leadership position of Netflix.

What a website personalization strategy looks like

To be a market leader consistently delivering personalized digital experiences requires more than just a customer-centric focus. It’s a good start as a strategy but requires enablement that comes in two forms:

  1. Technology capable of delivering on customer expectations

  2. A mindset of experimentation and continual learning

Artificial intelligence (AI) enables personalization through its ability to keep pace with the many dynamic market factors that influence customer buying decisions. It does this by identifying what information is relevant to unique users and when to present specific ideas and experiences in the customer journey. 

Companies recognize the importance of personalization and have a wealth of data but often are too focused on achieving specific key performance indicators (KPIs) and too siloed to bring everything together. There are goldmines of relevant information that never get shared, especially with regards to existing customers. Which means actual customer needs and preferences don’t get heard and personalization efforts fall short of consumer expectations.

With this siloed approach, building connections with customers has the aim of creating product or brand awareness rather than genuinely understanding consumer needs. It becomes all about the brand instead of focusing on the consumer and their needs. When applied to website personalization efforts, it fails to deliver  because it fails to connect with the target audience. This highlights that unless brands work at building genuine connections with customers for the purpose of understanding them better, data will remain under-utilized and personalization is nothing more than a guessing game.

To achieve website personalization success, companies need to be able to identify what customer data is important and why. Additionally they need the technologies to analyze specific data quickly, track how data relating to touchpoints changes over time and generate actionable insights. Trying to achieve this manually and even with traditional A/B testing tools is impractical as it takes too much time and resources, and results are often inconclusive. More advanced technologies such as AI-driven experimentation are far better suited to advancing personalization strategies.


AI-driven experience optimization personalizes website experiences by identifying and serving relevant information at the right time and at every touchpoint. This helps to reduce friction and move customers further along the journey with the ultimate goal of making a purchase. More significantly AI-driven experimentation generates insights quickly so that companies can respond to changing customer needs with ideas and information that is relevant. This is critical as personalization isn’t just about meeting customer needs today. True personalization success goes a step further by anticipating customer needs and creating engaging experiences that enhance customer lifetime value.

The best strategy to deliver consistently personalized experiences is to continuously experiment with as many ideas as possible. This is important because while consumers might be segmented into different personas they are never truly identical. Each customer has their own motivations for wanting a particular product and this could be tied to any number of factors; current needs or aspirations, social influence, emotional attachment or personal values. To complicate matters, motivations and market influences are constantly evolving causing buying behavior to change.

The takeaway is that learning is never done. Optimizing to improve customer experience and personalization doesn’t have a tick box, it’s an ongoing process. Finding winning ideas is only the beginning. Experience optimization truly comes into its own when more ideas are added to improve top performing experiences even more. To optimize resources, non-performing ideas can be paused so that all traffic is leveraged towards the top performing experiences.

A sound website personalization strategy leverages advanced technologies such as AI-driven experimentation to serve increasingly personalized experiences to consumers and continually learn from browsing and buying behavior. Consumer preferences are constantly evolving, strategies aiming to improve website personalization need to be agile enough to accommodate rapid changes in direction to remain relevant.

The best way to keep track of trends is to tap into real website visitor data. AI-driven experience optimization can validate and analyze data quickly. It is also able to use the insights generated to predict the next best experiences to serve. These experiences may hinge on a single idea, variations of that idea or combinations of different variables. AI has the ability to experiment with all of those options, serving more unique experiences to more visitors. This broadens experimentation capabilities enabling website personalization at scale - something that until now has been deemed impossible. AI-driven experimentation and personalization is the key to achieving desired outcomes in e-commerce and is the best bet for gaining a competitive advantage.

Website personalization best practices to utilize

Website personalization requires a focus on 3 key elements in order to be successful.

  1. The ability to scale personalization for millions of website visitors
  2. The capability to experiment with thousands of idea and variables
  3. Be able to identify clear winners and generate actionable insights quickly

Scale is possibly one of the biggest challenges when it comes to website personalization. It’s not difficult to personalize customer experiences when they’re interacting in person with a sales assistant in-store. There are visual and verbal cues that the sales assistant can use to determine what’s important to that specific customer and then tailor their approach to what they’re looking for. On a website there are no verbal or visual cues, only clicks, views and browsing behavior. This requires brands to get smarter about how they collect and use customer data.

Traditional A/B testing may be a proven methodology but existing testing tools aren't very useful for website personalization because they can only find the best of a small number of options. This makes trying to scale personalization efforts very challenging. By contrast AI-driven experience optimization can identify key visitor interactions on a website and find the experience they’re most likely to respond to as an individual, based on active learnings. This makes website personalization at scale possible.

The capability to test more than just one or two variables is essential for effective website personalization. Experimenting with hundreds of different variables and thousands of combinations of any number of ideas is what moves personalization forward. Most specifically because insights generated indicate which experiences resonate most with website visitors while they’re browsing. Being able to serve up a variety of unique experiences requires the ability to see how visitors are browsing and interacting on a website in real time, and to respond to those actions with relevant contextual information.


Expanding the volume of experimentation to both mobile and desktop has additional advantages. Visitors browse differently and experimentation highlights how often the top performing experiences on mobile differ from desktop. Only optimizing on one platform and assuming all experiences are the same, reduces the effectiveness of personalization efforts.

Personalization best practice involves understanding AI-driven experimentation delivers on personalization. AI tracks visitor behavior on a particular website and serves up experiences in response to their browsing behavior. It can even identify and respond to possible points of friction to prevent visitors from abandoning the journey.

For example: If a particular visitor seems to be taking unusually longer to progress in the customer journey, a prompt to assist with a customer service chat may pop up. This intervention gives the visitor an opportunity to get questions answered and can reduce their frustration, moving them forward with completing their purchase.

For existing customers, personalization is also possible based on their account details and known prior purchasing history. If the customer is due for an upgrade, past purchase information can be used to suggest upgrade options. This type of personalization requires limited data and can make a larger contribution to the customer lifetime value (CLV) of that customer.

Website personalization in e-commerce

In e-commerce it’s becoming increasingly difficult to complete on product or price. Instead consumers are choosing to shop where the experience stands out. This includes personalizing offers and gearing interactions to meeting specific needs.

Consumers no longer pay much attention to marketing messages because by default they’re generic and brand focussed which rarely aligns with what consumers are looking for. They don’t want to spend significant amounts of time searching for what they want. Convenience now expands to the whole customer journey.

Consumers now expect e-commerce retailers and brands to serve them better shopping experiences. They want relevant information served to them at the right touchpoints. The problem in trying to meet these expectations is that no two customers are the same and neither is the customer experience that will get them to buy. This also changes over time. Repeat customers don’t always have the same needs and preferences so the number of dynamic variables is constantly evolving. This means that website personalization in e-commerce needs the ability to evolve alongside these ever changing dynamics to remain relevant.

While humans may struggle to keep up with the many changing variables, technologies such as artificial intelligence (AI) don’t have the same constraint. By contrast AI thrives on complexity. The more touch points, the more data, the more combinations or variations, the more efficiently AI delivers answers. This is what makes it so well suited to personalizing experiences in e-commerce.

AI learns from live website visitors to identify patterns that translate into intent. These patterns help predict the next best experiences to serve that’ll resonate with visitors while they’re browsing. It becomes possible to see how a new visitor starts the journey and predict where they intend to go. This enables brands to get better at website personalization and meet customer expectations in e-commerce.

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