Scaling AI for Personalisation: How Companies are Building Unique Experiences for Billions

The Rise of AI in Marketing Personalisation

From one-size-fits-all campaigns to highly targeted individualised strategies, marketing has come a long way. The modern user seeks personalisation, they want to feel “heard”. According to McKinsey's research, 71% of consumers expect personalised interactions from companies, and 76% become frustrated when their expectations aren’t met. This is what pushes businesses to adopt AI-driven solutions for real-time campaign optimisation. AI tools can predict consumer needs, automate content delivery across multiple channels and refine precise messaging for your consumer base. 

This is driven by AI’s ability to process vast amounts of data and deliver personalised experiences. AI can analyse customer behaviours, preferences and interactions such as online browsing habits, purchase histories and social media activity to create a detailed profile of each user. This helps marketers create campaigns that resonate with their niche audience on a personal level.

The adoption of AI in marketing is growing, with the global AI marketing market expected to reach US $107 billion by 2028. This rapid growth is driven by investments from companies of all sizes, from leading companies like Netflix and Amazon to new-age small startups. Every business is now willing to adopt AI to improve customer experiences at scale. 

Messi Messages 

One of the most prominent examples of AI in personalisation is the “Messi Messages” campaign by Lays. Partnering with Synthesia, Lay’s launched a global interactive campaign featuring Lionel Messi’s dubbed messages. This initiative allowed fans to create personalised video messages where a synthetic Messi addresses their friends by name, speaking in 8 different languages. 

To bring this vision to life, the company recorded Messi for just five minutes in a green screen studio, speaking in his native Spanish. Synthesia used this footage to train its deep learning algorithms, creating a synthetic Messi avatar capable of delivering messages in 8 languages. The experience offered over 650 million possible video variations for a highly personalised interaction for each user. 

The business outcomes?

• The campaign generated 1.43 million messages in just 2 days which could have been impossible for a human team to manage. This led to massive user engagement. 
• The campaign achieved a 12.8% bounce rate, which is “super low” as mentioned in campaign results indicating that users stayed engaged with the experience. 
• On average, fans spent 3.53 minutes on the site, reflecting strong interaction. 

The campaign reached 1000s of names, 12,000 video variations and over 650 million total possible variations, showing its massive scale and impact. The campaign was also awarded a Cannes Lion Award in 2021. 

How Companies Are Using AI for Personalisation

The Messi Messages is not the only way companies are scaling AI for personalisation. From product suggestions to targeted outreach, companies are adopting AI-driven solutions to improve customer engagement across industries.  

• Personalised Product Recommendations: AI analyses customer data like purchase history and browsing behaviour to suggest relevant products, improving decision-making and satisfaction. It predicts preferences, reducing choice overload in crowded markets. Yves Rocher’s AI-powered recommendation engine uses this approach, boosting an 11x increase in the purchase rate of recommended products by offering personalised beauty product suggestions.

• Targeted Email Campaigns: AI can create personalised emails by analysing recipient data and optimising content for higher engagement. It ensures messages align with individual interests, improving open and click rates.

• Dynamic Content Suggestions: AI curates content in real time based on user behaviour, adapting to preferences for a seamless experience. This keeps users engaged with relevant media. Netflix recommends shows by viewing user habits, delivering personalised entertainment that retains subscribers and sets a standard for streaming platforms.

• Predictive Shopping Assistance: AI predicts complementary purchases by analysing shopping patterns, and suggesting items that enhance the buying experience. It drives sales through timely, relevant prompts. Amazon’s “Customers also bought” feature suggests add-ons based on user data, scaling personalisation to boost revenue across millions of customers.

How to Scale AI for Personalisation

Scaling AI to deliver personalised experiences for billions isn’t just about advanced algorithms, it requires a robust infrastructure to ensure efficiency, speed and reliability. You need to prioritise several critical components to meet the demands of personalisation at scale, ensuring your organisation remains competitive and responsive to customer expectations.

Right Generative AI Solution

Generative AI is essential for creating tailored content at scale, such as personalised email subject lines or video messages. This is crucial for personalisation because it allows you to dynamically generate content that resonates with individual preferences, maintaining engagement across diverse audiences while reducing production costs and time. At Nexgen Labs, we help you choose the right generative AI solution for your needs.

Cutting-Edge Hardware

Scaling laws describe how the performance of AI systems improves as the size of the training data, model parameters or computational resources increases. This makes advanced hardware non-negotiable for companies looking to scale AI. GPUs handle the parallel processing needed for machine learning models to analyse vast datasets and deliver real-time insights. Without this, your systems will struggle to process the scale of data required for personalisation, leading to delays and missed opportunities to connect with customers. We offer optimised NVIDIA hardware like the NVIDIA HGX H100, NVIDIA HGX H200 and the upcoming NVIDIA Blackwell GB200 NVL 72/36, built on reference architecture. Our cutting-edge hardware ensures your organisation can handle AI at scale.

Low-Latency Networking

Real-time personalisation such as serving a tailored ad the instant a user lands on your site depends on rapid data transmission. Low latency networks ensure AI systems respond instantly. This is imperative for personalisation because delays can frustrate users, leading to drop-offs and lost conversions. Our optimised GPUs are equipped with NVIDIA Quantum InfiniBand up to 400Gbps for faster networking and low latency to tackle your AI workloads scale. 

High-Performance Data Storage

Efficient data management is critical for AI to process and retrieve user information swiftly. Companies must opt for scalable storage solutions to handle the volume and velocity of data from billions of interactions. In personalisation, this matters because quick access to customer profiles enables timely, relevant recommendations. With our high-performance NVIDIA-certified WEKA storage with GPUDirect Storage support, your AI systems can avoid slowing down response times and degrading the user experience.

Scalable GPU Clusters 

As your user base expands, so does the computational load. Scalable GPU clusters for AI allow you to dynamically adjust resources. This is key for personalisation because it ensures your infrastructure can handle peak demand such as during a global campaign without crashing. Flexible compute resources mean you can maintain consistent performance, delivering personalised experiences to millions simultaneously, which is essential for global reach and customer satisfaction. We offer scalable GPU clusters for AI so you can expand your AI campaigns with ease. If you have fluctuating demands, you can also use our integrated on-demand Hyperstack GPUaaS platform with additional compute products for inferencing or bursting.

Conclusion 

AI-driven personalisation is changing how businesses engage customers at scale. From marketing to eCommerce, AI helps brands to deliver hyper-personalised experiences through real-time data analysis and content generation. However, achieving this requires a robust infrastructure comprising high-performance GPUs, low-latency networking and scalable storage. Investing in the right solutions ensures seamless performance, increased engagement and customer satisfaction. Our AI Supercloud offers a scalable platform with cutting-edge GPUs, storage and networking to support AI at scale. By adopting the right infrastructure, businesses can experience the full potential of AI while maintaining high performance at any scale.

FAQs

What is AI personalisation?

AI personalisation tailors content and recommendations based on user data, improving engagement by delivering relevant experiences. It analyses user behaviour, preferences, and interactions to create customised marketing, product suggestions, and digital experiences in real-time.

How does AI improve marketing campaigns?

AI enhances marketing by optimising audience targeting, automating content creation, and analysing customer behaviour. It predicts trends, personalises messaging, and maximises campaign effectiveness through data-driven insights, improving engagement, conversion rates, and overall marketing ROI.

What hardware is needed for AI personalisation?

AI personalisation requires GPUs for rapid data processing, low-latency networking for real-time interactions, and high-performance storage for handling large datasets. These components ensure smooth AI model training, inference and scalable deployment across various business applications.

How does AI generate personalised product recommendations?

AI analyses user browsing history, purchase behaviour, and preferences to predict and suggest relevant products. Machine learning models identify patterns, adjust in real-time, and refine recommendations based on customer interactions, enhancing personalisation and increasing conversions.