{"id":4688,"date":"2025-02-10T08:00:00","date_gmt":"2025-02-10T16:00:00","guid":{"rendered":""},"modified":"2025-07-03T04:05:03","modified_gmt":"2025-07-03T11:05:03","slug":"personalization-at-scale-how-cloud-and-ai-are-redefining-customer-engagement","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/microsoft-cloud\/blog\/2025\/02\/10\/personalization-at-scale-how-cloud-and-ai-are-redefining-customer-engagement\/","title":{"rendered":"Personalization at scale: How cloud and AI are redefining customer engagement"},"content":{"rendered":"\n

In today\u2019s digital-first world, personalization has become a business imperative. According to a study by McKinsey & Company, 71% of consumers expect companies to deliver personalized interactions, and 76% become frustrated when this doesn\u2019t happen. Businesses that get personalization right, however, see revenue increases of 10% to 15%, with company-specific gains ranging from 5% to 25%\u2014highlighting the clear link between personalization and business growth.1<\/sup> From curated entertainment recommendations to seamless healthcare solutions, personalization drives loyalty, boosts revenue, and sets industry leaders apart. <\/p>\n\n\n\n

But achieving personalization at scale requires more than AI and data analytics\u2014it demands a powerful, secure, and adaptive infrastructure that enables you to deploy AI. Without a scalable, high-performing cloud foundation, businesses face challenges like latency issues, fragmented data, and high operational costs\u2014all while grappling with the growing importance of data security and compliance. For organizations ready to embrace the future, building the right infrastructure foundation is the first step toward achieving personalization at scale\u2014empowering them to innovate faster, respond in real time, and deliver transformative, trustworthy customer experiences. <\/p>\n\n\n\n

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Customer Stories<\/h2>

Learn how organizations are achieving more with Microsoft<\/p>

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Overcoming barriers to personalization at scale <\/h2>\n\n\n\n

Achieving personalization at scale comes with its share of challenges. Businesses often contend with fragmented data systems, privacy and compliance concerns, and the complexity of acting on data in real time. While these hurdles can seem daunting, understanding them is the first step toward finding solutions. <\/p>\n\n\n\n

Fragmented data is one of the most common obstacles to personalization. Customer information is often scattered across systems, departments, or even physical locations, making it difficult to gain a unified view. For example, PointClickCare found that siloed healthcare data across providers delayed critical care decisions, highlighting the importance of breaking down these barriers to enable better insights. <\/p>\n\n\n\n

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It\u2019s common for people to work with multiple healthcare professionals for different treatments and prescriptions, for the best care, everyone needs to access, use, and trust the most current, accurate information.<\/p>\nAndrew Datars, Senior Vice President of Engineering at PointClickCare<\/cite><\/blockquote>\n\n\n\n

Real-time data processing adds another layer of complexity. Personalization requires immediate insights and responses, but many businesses struggle with legacy systems that can\u2019t handle fluctuating demands. MediaKind, for example, encountered difficulties delivering real-time media experiences during peak events\u2014putting customer satisfaction at risk. With the increase in competition in the industry and the pace of innovation around engaging with customers through video, they needed to find a way to match their current demands and innovation needs. \u201cPeople get really upset when their entertainment is offline. Seconds of downtime costs broadcasters and streamers millions of dollars in advertising and brand revenue<\/em>,\u201d Allen Broome, MediaKind\u2019s Chief Executive Officer notes. <\/p>\n\n\n\n

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MediaKind improves video delivery in minutes with move to Azure<\/a><\/div>\n<\/div>\n\n\n\n

Privacy and compliance can create significant challenges for businesses aiming to deliver personalized experiences. Analyzing sensitive customer data requires navigating a maze of strict regulations, such as ensuring data residency, meeting regional compliance requirements, and safeguarding user trust. These challenges are particularly pronounced in industries like legal, where the sensitivity of data and the complexity of workflows add additional layers of difficulty. Harvey, a platform designed for the legal sector, faces these exact hurdles. Security is paramount for Harvey due to the need to comply with varied regional security requirements and ensure that data never crosses regional boundaries. \u201cThe reason it\u2019s been so hard to build technology for industries like legal is the workflows are so varied and complex, and no two days are the same<\/em>,\u201d explains Gabe Pereyra, Co-Founder and President at Harvey. By prioritizing security and compliance from the ground up, Harvey provides a trusted solution tailored to one of the most demanding industries. <\/p>\n\n\n\n

While these challenges are real, they are manageable with the right strategies. Recognizing and addressing these barriers allows businesses to take their first steps toward achieving personalization at scale, turning these obstacles into opportunities for growth. <\/p>\n\n\n\n

Redefining customer engagement with cloud and AI technologies <\/h2>\n\n\n\n

Scaling personalization to meet modern customer expectations is a complex challenge, but cloud and AI technologies make it practical. Together, they empower organizations to process vast amounts of data, generate actionable insights in real time, and deliver tailored experiences at scale. <\/p>\n\n\n\n

For many organizations, data is scattered across disconnected systems, creating silos that prevent a unified view of customer behaviors and needs. Overcoming this barrier requires modernizing infrastructure to centralize data, enable seamless integration, and provide real-time access to actionable insights. Cloud platforms like Microsoft Azure<\/a> make this possible by offering secure and scalable solutions that unify fragmented data sources into a single, comprehensive view. For example, PointClickCare leveraged Azure to consolidate siloed healthcare data from multiple systems into a unified network. PointClickCare modernized their infrastructure by deploying a cloud-based solution with key Azure products like Windows Server<\/a>, Azure SQL Managed Instance<\/a>, and Azure OpenAI Service<\/a> to securely integrate data, streamline workflows, and enable real-time access to critical patient information. This transformation provided healthcare providers with actionable insights, improved operational efficiency, and enhanced patient care.  <\/p>\n\n\n\n

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PointClickCare migrates siloed healthcare data to Azure to be AI-ready<\/a><\/div>\n<\/div>\n\n\n\n

Personalization hinges on immediacy, and AI-powered cloud platforms enable businesses to process massive streams of data in real time, offering insights and actions when they matter most. Overcoming this challenge requires infrastructure that can handle both the scale and speed of data processing without delays. LALIGA achieves this by leveraging cloud-based AI and machine learning to analyze over 3 million data points per match, all processed in real time. Operating within a hybrid environment, they ensure consistent performance by distributing workloads intelligently across on-premises and cloud systems using Microsoft Azure Arc<\/a>. This allows LALIGA to deliver engaging digital and in-stadium experiences, from detailed match statistics to personalized player insights, enhancing how fans connect with the game. <\/p>\n\n\n\n

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LALIGA delivers seamless fan experience and AI insights with Azure Arc<\/a><\/div>\n<\/div>\n\n\n\n

To ensure real-time data provision, cloud infrastructure must be capable of adapting to variable demands. Cloud solutions provide elastic scalability, ensuring organizations can handle varying workloads without compromising performance. With 30 teams, more than 500 players, and each team playing 82 games per season, not including playoffs, the NBA have an enormous amount of player data to collect and analyze. In exploring how AI could help them process data on all on-court players\u2019 specific live body movements, analyzing things like speed, dunk height, number of passes and dribbles, and even injury risk, simultaneously, can create a need for elastic scalability. The NBA used a Microsoft Azure solution, based on Azure Kubernetes Service (AKS)<\/a>, that can manage and process up to 16 gigabytes of raw data per game, not including RGB video signals\u2014sometimes more if the game goes into overtime. The new solution is deployed and operational, and the data being collected is already helping the NBA better understand players\u2019 strengths and weaknesses and improve their performance.  <\/p>\n\n\n\n

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NBA players are improving performance with AI on Azure AI infrastructure<\/a><\/div>\n<\/div>\n\n\n\n

Lastly, trust and security are fundamental to achieving personalization at scale. In today\u2019s environment, businesses must be able to navigate strict regulatory requirements, safeguard sensitive customer data, and maintain user trust while delivering tailored experiences. Overcoming these challenges requires implementing robust security measures, such as end-to-end encryption, role-based access controls, and compliance monitoring, all of which can be enabled and streamlined through cloud platforms. Azure provides a unified environment where businesses can securely integrate data, enforce regulatory compliance across regions, and monitor potential risks in real time, ensuring sensitive information is protected at every stage. Harvey, for example, leveraged advanced encryption, access management, and compliance tools to meet the stringent security requirements of its clients. This solution enables law firms to confidently protect sensitive client data while delivering innovative, AI-powered legal services. As Harvey\u2019s Chief Executive Officer explained, “Law firms trust Azure because it allows them to deliver cutting-edge, AI-driven legal services without compromising on security or compliance<\/em>.\u201d This commitment to security enables Harvey to focus on innovation while maintaining trust with its clients. <\/p>\n\n\n\n

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Harvey makes lawyers more efficient with Azure AI infrastructure<\/a><\/div>\n<\/div>\n\n\n\n

Transform your business with scalable personalization <\/h2>\n\n\n\n

Personalization at scale is essential for businesses striving to stay competitive in today\u2019s rapidly evolving market. Customers increasingly expect experiences that feel tailored, anticipate their needs, and build trust. As cloud and AI technologies continue to advance, the opportunities for deeper, more impactful personalization will only expand. <\/p>\n\n\n\n

You can stay ahead of the competition by delivering personalized experiences that resonate with your customers. Here are some essential steps you can take to get started today:  <\/p>\n\n\n\n