Creating hyper-personalized customer experiences to align with dynamic business goals

As business leaders prepare for CES 2026, one technology trend is reshaping customer experience strategies: AI-driven hyper-personalization. In a world where choices are infinite and attention is fleeting, winning brands make every interaction feel personal through real-time, predictive intelligence that anticipates needs before customers articulate them. The era of one-size-fits-all programs is over.

For B2B leaders in the device lifecycle ecosystem, hyper-personalization is a strategic imperative powered by data analytics, machine learning, and intelligent automation. When implemented effectively, hyper-personalization can be a powerful difference maker in the consumer retail journey.

The business case for AI-driven personalization

Personalization has evolved from a marketing tactic into a strategic priority. According to recent research, 82% of customers say personalization directly influences brand choice. But achieving personalization at scale requires data fluency, AI-powered automation, and seamlessly integrated technology ecosystems.

This transformation is evident in the lifecycle of connected devices. From protection enrollment to proactive support to predictive trade-in offers, AI-driven personalization is changing how customers experience the technology that powers their lives. Companies are shifting from static, rules-based programs to dynamic systems that adapt in real time. The business outcomes are measurable: stronger customer relationships, higher attach and persistency rates, and demonstrable gains in lifetime value. A recent BCG study shows that personalization leaders are growing revenue 10% faster than laggards. For enterprise partners, hyper-personalization drives operational efficiency, automating complex decisions and optimizing resource allocation across millions of interactions.

Real-time personalization through intelligent data platforms

As customer expectations evolve, businesses need platforms that make flexibility effortless. Advanced data platforms powered by machine learning enable brands to integrate partner benefits and empower customers to personalize their selections in real time.

Behind the scenes, AI engines process multiple data streams: customer demographics, device specifications, historical behavior, parts inventory, and market conditions. These systems create instant enrollment decisions, surface relevant opportunities at the right moment, and manage fulfillment automatically. For businesses, this means strengthening relationships while streamlining operations and reducing unnecessary complexity. For customers, it means personalized experiences that simply work.

Assurant by the numbers:

Operating at this level of sophistication requires proven scale and trusted partnerships. Assurant's intelligent data platforms have a track record that supports this shift.

65M mobile devices connected and protected serves as a strong foundation for real-time personalization across tens of millions of simultaneous customer interactions.
7 of 10 global telecom brands partner with Assurant, which is proven expertise in working with the world's most demanding B2B partners to represent their brands and anticipate what their customers expect next.

Predictive analytics: from reactive support to proactive care

Traditional tech support operates reactively, stepping in only when something goes wrong. AI-driven hyper-personalization changes this by using predictive analytics to anticipate customer needs before they reach out for help.

The power of telemetry makes this concept a reality. Real-time data collection and analysis from network devices provides continuous insights into device performance and potential problems. Think of a process that begins when a customer's printer first connects to a new network. An intelligent system automatically triggers a personalized SMS with setup instructions tailored to that specific device model, preventing frustration before it happens. Or imagine being able to avoid a disastrous fire by monitoring a device’s operating temperature and recommending immediate action or shutting it down when readings are outside of normal parameters.

This is proactive care powered by real-time data and machine learning, analyzing device health signals, usage patterns, and behavioral indicators to predict friction points. The business impact is transformative: Support evolves from a cost center into a loyalty engine, improving customer satisfaction and retention while reducing support ticket volume.

Assurant by the numbers:

These aren't theoretical benefits. They're results that are beginning to happen at enterprise scale:

34M customers supported globally informs the development of proactive, predictive care models that can work across diverse markets, device types, and customer segments.
4.85 average customer satisfaction rating demonstrates that AI-driven personalization can integrate with human interactions without a loss in satisfaction, helping turn more support interactions into loyalty-building moments.

AI-powered service and repair optimization: precision at scale

In service and repair, hyper-personalization means delivering precision at scale. Modern intelligent platforms process thousands of data points per claim in seconds, analyzing device type, warranty terms, parts availability, customer location, technician proximity, and service history to determine the optimal solution path instantly.

This intelligent orchestration delivers what customers experience as “magic” personalized service designed specifically for their situation, delivered at the speed they expect. Whether it's a same-day repair at a nearby authorized repair center or an expedited replacement, customers receive faster resolutions that feel effortless.

The business results are compelling: higher operational efficiency through automated decision-making, reduced logistics costs, and increased customer confidence. In 2024, Assurant serviced over 1.4 million devices, with most repairs completed in under an hour through its AI-enabled Authorized Repair Network.

Assurant by the numbers:

The speed and precision of AI-powered service optimization is only possible with extensive physical infrastructure and proven operational excellence.

1.4M+ devices repaired annually, volume that feeds the AI decision engine's ability to consistently route the right solution to the right customer at the right time
925+ Authorized Repair Centers across the US, the physical network that makes same-day, localized service a reality rather than a promise
Majority of repairs completed in under one hour, a promise that’s directly powered by AI intel regarding parts inventory, appointment scheduling, and more to deliver repeatable customer experiences

Machine learning in trade-in: personalization meets market intelligence

The trade-in and resale market shows how hyper-personalization and predictive analytics intersect to drive business value. By analyzing millions of device valuations across global programs, machine learning data enables businesses to deliver trade-in offers that optimize competitive positioning, customer satisfaction, and profitability.

Predictive analytics play a crucial role in timing. AI systems identify signals that indicate when customers are most likely to upgrade and trigger personalized trade-in offers that feel timely rather than random. This precision improves conversion rates while strengthening brand engagement.

On the backend, intelligent disposition systems leverage machine learning to evaluate market conditions, demand fluctuations, and resale channel performance, optimizing when and where to sell refurbished devices.

In recent years, mobile operators’ annual spending on device purchases and trade-in subsidies has begun to rival their investments in infrastructure and spectrum — costs that accumulate year over year. To address this, partners like Assurant must leverage technology to help carriers maximize the value of collected devices, with AI- and robotics-based automation playing a key role.

Assurant by the numbers:

The scale of these machine learning systems reveals the complexity of personalization in trade-in and resale.

22M trade-ins processed globally annually, generating the massive dataset required to train predictive models to accurately anticipate customer upgrade timing and optimize disposition strategies across diverse markets
$4.5B returned to consumers through trade-in and buyback in 2024 sets a benchmark for personalized offers to support competitive positioning, customer satisfaction, profitability, stakeholder value, and sustainable circular economy practices

Connected ecosystems, consistent value

True hyper-personalization thrives in connected ecosystems that integrate data, platforms, and expertise across every customer touchpoint. These ecosystems allow businesses to adapt quickly and deliver consistent value throughout the customer journey.

Looking ahead: how will personalization become a competitive advantage?

As we head into CES 2026, the next evolution of customer experience will be defined by foresight. As AI capabilities advance, personalization will become increasingly predictive, enabling businesses to anticipate behavior and create experiences that evolve alongside customer needs.

Hyper-personalization isn't just about knowing customers better. It's about building intelligent systems that listen, learn, and act in ways that make technology feel more human. The brands that succeed will understand one truth: Personalization isn't a promise. It's a practice.

For B2B leaders in the device lifecycle ecosystem, the question isn't whether to invest in hyper-personalization, but how quickly you can deploy the platforms and capabilities required to compete. The organizations that act now will define the future of the industry.

Ready to explore how AI-driven hyper-personalization can transform your device lifecycle programs?

Connect with us to arrange a meet up at CES 2026 in Las Vegas or schedule a consultation to learn more.

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