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Personalization 2030:
What does the future hold?

Vector illustration of athletes on a running track

Personalization is a tightrope act for brands. If your recommendation engine simply recycles past purchase information, you’ll quickly frustrate customers. But if you’re too on the nose, they’ll think you’re snooping on them and betraying their trust.

For retailers, smarter personalization is a huge opportunity, as 65% of consumers surveyed by Salesforce say they’ll remain loyal to companies that offer a more tailored experience. The challenge? Less than 20% of retail leaders told Kin + Carta that this was a critical need in 2024.

Preparing for the future of personalization requires finding a smart balance—seamlessly integrating data-driven recommendations that are highly relevant, while helping customers feel like they’re in control. To thrive in 2030, you’ll need to understand how personalization is evolving, including how artificial intelligence (AI) will accelerate the ability to customize, tailor, and automate customer experiences.

From automation to anticipation

Personalization has come a long way from auto-populating someone’s first name in an email. Today, it’s about using data to deliver personalized experiences that truly anticipate customer needs. The coming years will see this evolve. Brands will create experiences that feel organically linked to customer's thoughts and desires, delivering smoother, more satisfying interactions.

Underpinning this evolution will be technology that speeds up, automates, or replaces countless activities. "What can people do when the tech gets rid of all those mundane, time-consuming tasks?” says Heather Ryan, Lead Data Consultant at Kin + Carta. “What additional value can these people bring to their businesses and industries?”

Personalization is becoming increasingly predictive and proactive, helping brands anticipate customer needs and preferences even before they’re expressed. You can see this in platforms that offer product suggestions based on sophisticated analysis of browsing history or viewing habits.

Consider AI personalization in digital marketing. Suddenly, analyzing customer preferences and behaviors is easy, yielding deeper and faster insights than ever before. Marketers can be more confident in creating highly targeted campaigns that resonate, drive engagement, and deepen loyalty.

 

Your data foundation determines your fate

The success of your personalization efforts will depend on how well your data is orchestrated across platforms and touchpoints.

"Do you have your data in the right place? Do all of these tools that you're using that are trying to add personalization have data to pull from to create meaningful personalization?"

says Jared Johnson, Strategy Director at Kin + Carta.

This starts with having the right data infrastructure to make sure data is accessible, accurate, and actionable. Without this foundation, even the most sophisticated personalization tools will fall short. Effective data orchestration involves integrating various data sources, validating data quality, and making this data available in real-time to personalization engines.

The synergy between data and personalization is crucial. Retailers will need to seamlessly connect customer purchase histories, browsing behaviors, and engagement metrics to offer product recommendations that truly resonate.

Dream beyond retail

While personalization has become a cornerstone in retail and digital marketing, nearly every sector should be exploring its potential.

"While personalization has become a cornerstone in retail and digital marketing, nearly every sector should be exploring its potential," explains Mona Champaneri, Senior Vice President of Experience and Product at Kin + Carta. “We are likely to see its expansion in industries where it’s not yet standard, such as healthcare, education, and legal services.”

In education, personalized learning paths could significantly enhance student engagement and outcomes by adapting to individual learning styles and paces. Imagine a classroom where each student receives assignments and resources tailored to their progress and preferences. This approach makes learning more engaging and equitable, allowing instructors to continuously refine their methods based on real-time feedback and student progress.

In healthcare, personalization can mean AI analyzes patient data to recommend specific treatments, monitor health trends, and even predict health issues before they become critical. The key lies in making decisions based on a patient's medical history and ongoing health data, not just generalized recommendations based on high-level demographics. Healthcare professionals can spend less time reacting to unexpected health issues and more time focusing on prevention and early intervention—leading to better outcomes and patient satisfaction.

The key will be for business leaders to understand why they’re adding personalization, says Ewan Nicolson, Director of Data & AI at Kin + Carta. “Are we recommending for discoverability? Are we recommending for a better experience?” he says. “That's the sort of thing that I'd love to be doing more of in the industry and not just slapping personalization on because you can.”

 

Zooming in on your ‘best customer’

In the future, loyalty programs won’t just be about discounts and rewards; they will be about understanding and meeting customers' real-time needs.

Understanding your "best customer" is an approach in which you target the group or individuals who best represent your target consumer. By modeling how to move customers along the “best customer path,” you can zero in on the actions most likely to trigger and deepen interactions.

At Kin + Carta, we worked with a leading international coffee chain retailer to tap propensity modeling—a statistical approach that uses data to predict behavior—to analyze and optimize its rewards program. This approach helps the business better understand and segment existing customers and consider different scenarios, such as whether the program incentivizes cross-selling in different categories without losing recurring sales.

As businesses continue to evolve their personalization strategies, the focus will become increasingly granular and precise. You’ll need to know which customers to target and how to customize your content and communication methods based on detailed customer profiles and sophisticated analysis.

“Customization in the future doesn't mean everyone's going to get an email or everyone's going to get an update, it's going to be targeted and it's going to be personalized,”

says Richard Bownes, Principal - Data & AI at Kin + Carta. “There's going to be a lot more tailoring of which customers are activated to receive content, what that content is, and how the body of customer communications or the presentation of the experience can be fine-tuned for them.”

Instead of generic messages to your entire audience, personalization is evolving into making sure each customer receives only information that's highly relevant to their needs and interests.

Vector illustration of athletes on a running track

Make way for AI

Personalization and AI are a natural pair, as AI tools can analyze enormous amounts of data in real time to predict customer behavior, recommend products, and create personalized content.

Across industries, AI-driven personalization will go beyond simple recommendations based on past behavior and start predicting what people want in the future. For instance, streaming services like Netflix use AI to recommend shows and movies based on viewing habits, but the future will see this extend to interactive and immersive experiences.

One opportunity for brands in the coming years will be to integrate AI into personalization efforts while overcoming consumers’ concerns about privacy and data security. One way to do this could be a "digital twin" that manages personalization on your behalf.

“Use all of your personalization algorithms, target me as much as you like, but you're only going to get to speak to my AI,” says Karl Hampson, Chief Technology Officer of Data & AI, at Kin + Carta. “My AI is going to know what I'm in the market for at the moment, what my preferences are, and I get a beautifully filtered view of the world.”

Under this model, personalization is smart and based on personal information, but it’s also filtered and less invasive. Customers only receive the best, most relevant offers tailored to their needs and preferences.

 

Designing digital interactions that become seamless and intuitive

By 2030, personalization will be so integrated into digital interactions that it'll feel seamless and intuitive. Technologies like augmented reality (AR) and virtual reality (VR) will continue to evolve, offering increasingly immersive, personalized experiences. For example, virtual try-ons in retail or personalized home tours will become commonplace.

Personalization will also emphasize real-time adjustments based on customer interactions. Imagine walking into a store where digital displays change to show products you might like based on your online browsing history and behavioral data.

The benefits of intuitive personalization are obvious. “In terms of what's virtuous with personalization, the idea that it removes steps, it's intuitive … it gets very sticky and addictive for people,” Hampson says. “I love personalization being used for that.”

Seamless personalization also goes well beyond the purchase point. Businesses should tap into both first-party and third-party data to gain a comprehensive view of customer behavior and preferences. By combining these data sources, companies can provide value from first touch through to post-purchase support, ensuring a cohesive and intuitive customer experience.

 

A highly personalized future

Personalization will continue to evolve, driven by AI, high-quality data, and a relentless focus on earning and securing customer trust. The winners in personalization won’t bombard people with offers that are little more than guesses. Instead, they'll shape a “best customer path,” delivering memorable, engaging moments that support meaningful business growth.

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