Trends Reshaping Ecommerce Personalization in 2024

Trends Reshaping Ecommerce Personalization in 2024

As we head into 2024, there has been an enormous amount of excitement and conversation around Generative AI.  

Development in this arena exploded in 2023, but it’s not the only trend we’re keeping an eye on in 2024.  

Monetate predicts 5 key eCommerce personalization trends to watch in 2024, including: 

  • Getting Ready for Generative AI 
  • The beginning of the cookieless future 
  • Increased adoption of Centers of Excellence 
  • Greater collaboration between merchandisers and machines 
  • Improved feedback loop between testing and merchandising experiences 

Let’s further explore the 5 eCommerce personalization trends we’ll be watching at Monetate in 2024. 

Top 5 eCommerce Personalization Trends for 2024 

While we’ll see eCommerce personalization continue to evolve in 2024, we predict key advancements in the following areas: 

#1: Getting Ready for Generative AI 

It’s the poppy buzzword that has the whole world talking – Generative AI.  

But while there is a great amount of hype and enthusiasm from brands to embrace generative AI in the future, the technology itself is not quite ready for prime time yet. And this is backed up by practices we’re seeing across our client base. 

So while it’s clear that AI is already impacting how we operationalize business, far fewer companies have actually found a way to reliably serve their customers better with generative AI in its current form due to a number of concerns. 

This is a trend that we at Monetate will be keeping a close eye on in 2024, but let’s look at a few reasons why we might not be there yet as we close out 2023: 

  • Speed of Development: Generative AI developed at a breakneck pace in 2023. Unfortunately, generative AI is moving faster than brands are able to integrate the technology into their businesses.
  • Output Quality: While the outputs from generative AI are impressive, they aren’t quite at enterprise-quality yet. Sometimes the output misses the mark or isn’t quite what a brand would want to use to represent them (especially when selling goods to shoppers). There still needs to be some tweaking of models before the outputs are ready and are dependable.
  • Data Privacy: Data is precious, and customers don’t want to risk generative AI having access to their private information. Could this data be leaked? What are the implications of customer data being used by generative AI to learn? It’s a lot to consider.
  • Price: Generative AI requires a lot of computing power. At present a lot of enterprises are not ready yet to build the infrastructure and fund the needed technology. 

Based on the speed of enhancements to Generative AI in 2023, we cannot wait to see what 2024 will bring. We’ll be watching!  

#2: Stepping in to the Cookieless Future 

The increased focus on data privacy in the last few years has prompted online brands to respond quickly to what’s coming in 2024. By that we mean, the elimination of third-party cookies, aka, the “cookieless future.” 

In response, there has been a big expansion in the number of companies that have data privacy or compliance officers and data teams, including significant increases in the budgets of privacy programs. 

While Google had previously announced that they would stop the use of third-party cookies in 2022, they delayed the ban twice (although Firefox and Safari had already started blocking them). Google is now scheduled to end its support of third-party cookies in Q3 2024. 

Eliminating cookies is an issue for brands who wish to create digital experiences tailored to individual site visitors – a cornerstone of effective personalization – due to the role of cookies in tracking visitor behavior. 

Even though this type of tracking is confined to the user’s session within a particular site, it is still in many cases considered a form of a third-party cookie and so usage is being increasingly constricted and finally, eliminated. 

To meet this challenge, and to comply with customer expectations around privacy, an augmented approach to the generation of personalized experiences will be required by mid-2024.  

This is the line in the sand that marks the moment when companies and brands will have to rely on cookieless personalization moving forward. 

Without user session information from third-party cookies, companies will rely on other forms of data and indicators to continue to build tailored experiences for customers. 

Examples include: 

  • Geographic location 
  • Time of day 
  • Page-specific behavior 
  • Time of year 
  • Local weather conditions 

These contextual pieces of information, sensitively and intelligently used, can still create powerfully personalized experiences moving through 2024 and beyond.  

#3: Increased Adoption of Centers of Excellence 

As customer expectations from personalized experiences continues to increase, digital and merchandising teams are pressed to keep up with consumer needs.  

To achieve true personalization, teams need technology to get the job done efficiently and to achieve fast and trackable ROI.  

As companies mature and become more sophisticated, they are increasingly moving toward building Centers of Excellence in their respective organizations.  

By building a Center of Excellence teams can make sure they are working efficiently, cross-department, and are sharing data and information to excel.  

Leadership and open communication are key in building a Center of Excellence. When everyone is aligned across an entire organization, innovation and embracing new technologies in personalization will be easier to achieve as it will be a shared initiative.  

#4: Better Feedback Loop Between Testing and Merchandising 

What experiences are working, and what experiences are not?  

It’s a popular question marketers and merchandisers ask. While machine learning can help create experiences suited for various personas and segments automatically, it is traditional testing and the learnings that come from seeing what is moving the needle and what isn’t that can yield unexpected success. 

Merchandising tools like product recommendations are built to exploit, while tests are built to explore. And oftentimes, personalization practitioners treat them as disjointed elements in a wider personalization program as a result. This, despite the two needing to inform the other.

A new merchandising container on your PDP needs to be optimized for messaging, page layout, product badging placement, recommendation strategies at a slot level, to just name a few elements. And testing is the best tool for guaranteeing optimal results (and avoiding subpar ones). 

In 2024, we predict that merchandisers will build a more informed feedback loop in their pursuit of their industry’s best customer experience. Then they will know and constantly be improving on what’s working across their digital merchandising through the power of constant testing.   

#5: Better Collaboration Between Merchandiser and Machine 

Sure, savvy retail merchandisers know what clothing and accessories pair well together. Manually they could sit down and build out different looks and collections that are shown as recommended products (or looks) to customers. But that’s quite a time-consuming process. And they have enough on their plate as it is. 

So, in 2024, we expect to see merchandisers working smarter by taking their unmatched knowledge and expertise and combining it with a machine-learning driven tool, such as Monetate Dynamic Bundles, to scale the curation of product sets and other digital merchandising tasks  

It’s now possible to quickly build collections to “Complete the Look.” Using machine learning to scale this process saves time for merchandisers, while still helping customers pick out what items go best together, opening opportunities for improved product discoverability and customer engagement. 

How Monetate is Preparing for 2024 and Beyond: AI and Data Privacy 

We’ve predicted that the growing interest in AI would continue to play an increasingly important role in personalization, and that has proven to be the case.

However, the role AI plays in providing personalized experiences will come under increasing scrutiny from regulators and authorities as concern grows for how this innovative technology handles consumers’ personal information and feeds it into wider data-gathering and decision-making processes. 

As the commercial application of AI in areas like eCommerce is still in its infancy, data best practices and privacy laws are playing catch-up with the industry.  

But given the spotlight on data privacy in general, consumers and governments will soon expect brands to incorporate oversight of AI data handling into their data compliance processes and standards. 

Online retailers who can offer customers a simple and unambiguous way to check what data a company holds on them and how they use it will have a competitive edge when it comes to building and maintaining trust in their brand. 

Monetate’s personalization platform takes a unified approach to data, AI, and personalized experiences. Our user-friendly dashboards make it easy for teams to see what data is being collected and how it’s being used. 

A big trend of the last few years has been the widespread adoption of an opt-in model of data usage, where sites and companies are obliged to gain the explicit consent of visitors before using their data. 

Marketers should welcome this: customers have shown themselves happy to share their data, as long as they can see a clear benefit from it. Rather than see this as a threat to business models, online retailers should view it as a way to build trust and brand loyalty with their customers. 

As we move forward, the gathering and use of first-party and zero-party data will become more important than third-party data in personalization.  

Data that comes directly from your customers and that they have willingly shared with you is more valuable than third-party data and can be used to generate truly individualized experiences. 

Monetate Personalization combines first-party data with in-session behavior and out-of-the-box targets so you can achieve 1-to-1 personalization at scale.  

Creating these unique digital experiences not only satisfies the personalization needs of consumers but also uses their data sensitively and transparently in 2024 and beyond. 

We cannot wait to see where 2024 will take us on our personalization journey!