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How do you build meaningful, lasting relationships? With personalization as we're used to thinking about it, a blog like this would help drive AI-fueled recommendations or a killer customer data platform. But that really misses the point. Relationships are about people, and a good relationship requires investing significant time and energy. That's why we generally have an inner circle in our own lives that is kept small by design.

So how do organizations accomplish the impossible - build meaningful relationships that last across thousands, if not millions, of individuals? And, how do they do that in an environment in which audiences are more willing to walk away than ever before, and the impact of one bad experience can far outweigh the benefit of multiple good ones?

Organizations across industries haven't been sleeping on the importance of personalization for unlocking engagement with audiences. If we're being honest, however, the technology available has fallen well short of expectations.

Why is personalization at scale so hard?

So how do you move from ad hoc to accurate, reactive to relevant – for every individual at infinite scale? Let's first establish what's required to drive these goals:

This requires access to all your data including transactional, observational, and behavioral - any type from any source.

To fully understand what's happening with your audience, it's not enough to react to data that's weeks or even days old. Insight into engagement up to the second means real-time processing of streaming and cognitive services like computer vision and intelligent voice recognition.

Even with access to accurate, real-time data, you must be able to synthesize that data within seconds and make predictions to better understand both what t will happen and what should happen. This is how you build lasting loyalty while reducing risk and creating true scale.

But if these requirements are so critical, why are so many organizations struggling to meet them? Delivering personalization that is accurate, real-time, and relevant demands that organizations can understand and analyze the past to predict the future and affect the present. The reality is that traditional systems don't support these goals. Instead, companies are relying on a complex set of disparate tools - data warehouses, lakes, orchestration, BI, streaming, AI - that come with lock-in from proprietary formats and protocols, and create duplication when working across more than one cloud. Scale in this scenario is virtually impossible considering the performance limitations and ever-increasing costs. In speaking with our customers - across regions and industries - it's become clear that organizations of all sizes and maturity struggle with these challenges.

To make this concept more tangible, let's walk through the data journey of one of our customers Disney+, who is all about delivering a world-class experience for their audience. To do so, they have to synthesize data across customer records and streaming platforms to deliver results in milliseconds. Under the old technology paradigm described above, this meant accessing customer records from a data warehouse, streaming data from 5 separate platforms, and leveraging yet more tools to make sense of it all. As you can imagine, it wasn't possible to achieve the desired result under those conditions. So Disney+ worked with Databricks to build real-time, data-driven capabilities on a unified streaming platform. The platform ingests billions of events per hour and analyzes them to help Disney+ scale its viewing experience to tens of millions of customers with the required quality and reliability.

We live in a world in which the audience you're trying to engage is more likely to walk away after just one bad experience than ever before. Organizations like Disney+ that are built on creating world-class experiences have realized that speed, performance, cost, and scale are non-negotiable in today's world.

We'll also be diving into this topic in an upcoming webinar where customers like USPS, Amgen, ITV, Gousto, Corning, and Albertsons will describe their own journey and how they're leveraging the only data, analytics, and AI platform built from the ground up for how organizations use data.
Register here!

Meet 1:1∞: Powered By a Lakehouse

The Databricks Lakehouse was purpose-built with the understanding that simplifying and democratizing data, analytics, and AI is the key to engagement, people, operations, and products reaching their full potential. How does it do this?

  • Simple - Lakehouse is the only platform to unify all of the technologies we've talked about – data lake, data warehouse data orchestration, BI, streaming, AI/ML - into one composable, infinitely scalable solution that always performs better at a lower TCO.
  • Open - Lakehouse is based on open source and open formats, so you are always in control and never locked-in by proprietary formats
  • Multi-cloud - You have the power of choice to gain more value from all your existing investments, while never being limited in your future direction or technology choices.

What does this mean for personalization? The Lakehouse uniquely allows you to use all of your data, from any source, with unprecedented accuracy, availability, and relevance. You can fully analyze the past - even if the past was just seconds ago - and predict the future (not only what will happen but what should happen) to always act in the present with maximum impact and effectiveness.

Transformation is not a destination, but a journey, and this new era will be marked by the "data-defined enterprise" - able to leverage data, analytics, and AI and create digital feedback loops across the entire enterprise to enable speed and scale for long-term success.

Want to learn more? Join our panel, Personalization Meets Scale, which features leaders from industry innovators such as Albertsons, Amgen, Corning and more. Register now!

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