Project Title
Project Title
Project Title
Simplifying hyper-personalisation with “drag&drop-ing” & AI
Simplifying hyper-personalisation with “drag&drop-ing” & AI
Simplifying hyper-personalisation with “drag&drop-ing” & AI
Description
Executive Summary
In today's marketing landscape, the gap between consumer expectations and technological capabilities has created a $136 billion annual loss for U.S. businesses due to poor customer experiences.
This case study presents the design of an AI-powered journey builder that bridges this gap, enabling marketers to create hyperpersonalized experiences at scale while reducing operational complexity.
In today's marketing landscape, the gap between consumer expectations and technological capabilities has created a $136 billion annual loss for U.S. businesses due to poor customer experiences.
This case study presents the design of an AI-powered journey builder that bridges this gap, enabling marketers to create hyperpersonalized experiences at scale while reducing operational complexity.
Context
Beyond Traditional Segmentation
Have you ever unsuccessfully tried to target your customers to reach higher sales or acquire new customers?
Probably not.
Me neither.
But others have this problem... they are marketeers. Modern marketers are under pressure to deliver real-time, individualised experiences across multiple digital touch points and mediums. The digital marketing ecosystem has reached an inflection point. McKinsey research reveals that 71% of consumers expect personalized interactions, while 76% become frustrated when this doesn't happen. Yet, traditional marketing automation platforms remain rooted in outdated segmentation models that treat customers as demographic buckets rather than dynamic individuals.
Have you ever unsuccessfully tried to target your customers to reach higher sales or acquire new customers?
Probably not.
Me neither.
But others have this problem... they are marketeers. Modern marketers are under pressure to deliver real-time, individualised experiences across multiple digital touch points and mediums. The digital marketing ecosystem has reached an inflection point. McKinsey research reveals that 71% of consumers expect personalized interactions, while 76% become frustrated when this doesn't happen. Yet, traditional marketing automation platforms remain rooted in outdated segmentation models that treat customers as demographic buckets rather than dynamic individuals.
"71% of consumers expect personalized interactions, while 76% become frustrated when this doesn't happen."
"71% of consumers expect personalized interactions, while 76% become frustrated when this doesn't happen."
"71% of consumers expect personalized interactions, while 76% become frustrated when this doesn't happen."
McKinsey
McKinsey
Problem
User Pain Points
Great ideas get lost in slow processes, and customer experiences fall flat. Why? Mainly because the marketing teams often struggle with the following problems:
Great ideas get lost in slow processes, and customer experiences fall flat. Why? Mainly because the marketing teams often struggle with the following problems:
More Context
The Hyperpersonalization Imperative
The distinction between segmentation and hyperpersonalization represents a fundamental shift in marketing philosophy. Where segmentation creates broad categories like "Millennial Women in Urban Areas," hyperpersonalization leverages individual behavioral patterns: "This user browsed sustainable activewear three times this week, abandoned cart twice, and typically shops on mobile between 9-11 PM."
The distinction between segmentation and hyperpersonalization represents a fundamental shift in marketing philosophy. Where segmentation creates broad categories like "Millennial Women in Urban Areas," hyperpersonalization leverages individual behavioral patterns: "This user browsed sustainable activewear three times this week, abandoned cart twice, and typically shops on mobile between 9-11 PM."
Example
How Netflix Does It
Netflix exemplifies this approach, generating $1 billion in annual savings through AI-powered personalization. Their recommendation engine, which influences 80% of content consumption, demonstrates the transformative potential of real-time behavioural intelligence.
Netflix does this perfectly. Its entire experience is built around dynamic personalization—from the thumbnails you see to the order of titles, all based on your behavior. That’s not segmentation. That’s real-time intelligence.
Netflix exemplifies this approach, generating $1 billion in annual savings through AI-powered personalization. Their recommendation engine, which influences 80% of content consumption, demonstrates the transformative potential of real-time behavioural intelligence.
Netflix does this perfectly. Its entire experience is built around dynamic personalization—from the thumbnails you see to the order of titles, all based on your behavior. That’s not segmentation. That’s real-time intelligence.
Solution
Why Data is the Answer
Hyperpersonalization runs on data—clean, connected, and real-time. It’s the only way to understand customer intent, behavior, and timing. The problem? Most marketers don’t have tools that let them act on data at the speed of the customer. Marketeer decision should be based on real-time campaign data such as budget allocation, campaign revenue, and allocation control, to name a few.
Hyperpersonalization runs on data—clean, connected, and real-time. It’s the only way to understand customer intent, behavior, and timing. The problem? Most marketers don’t have tools that let them act on data at the speed of the customer. Marketeer decision should be based on real-time campaign data such as budget allocation, campaign revenue, and allocation control, to name a few.
Impact?
Quantifying Success
How do we know that what we design has an impact? The following are the metrics that I see as most relevant to answer this question:
How do we know that what we design has an impact? The following are the metrics that I see as most relevant to answer this question:
P.S.
Project Takeaways
Conclusion
The Future of Marketing
This case study represents more than a product design—it's a strategic response to fundamental shifts in consumer behavior and technological capability. By applying user-centered design principles, behavioral psychology, and systems thinking, we've created a platform that doesn't just automate marketing—it augments human intelligence with AI-powered insights.
As we look toward the future, the principles that should guide design projects are —empathy-driven research, data-informed decision making, and iterative improvement—these remain the foundation for creating products that truly serve human needs in an increasingly complex digital landscape.
This is the challenge and opportunity for the next generation of UX designers: building technology that makes us more human, not less.
This case study represents more than a product design—it's a strategic response to fundamental shifts in consumer behavior and technological capability. By applying user-centered design principles, behavioral psychology, and systems thinking, we've created a platform that doesn't just automate marketing—it augments human intelligence with AI-powered insights.
As we look toward the future, the principles that should guide design projects are —empathy-driven research, data-informed decision making, and iterative improvement—these remain the foundation for creating products that truly serve human needs in an increasingly complex digital landscape.
This is the challenge and opportunity for the next generation of UX designers: building technology that makes us more human, not less.
