Editorial
The Gist
- Customer data evolution. Customer data management is rapidly changing, demanding adaptability in privacy, compliance and security measures.
- Collaboration impact. Cross-organizational data collaborations are emerging, requiring proactive investment in analytics tools and partnerships.
- Data lake transformation. Data lakes are revolutionizing data storage and analysis, pushing for sophisticated machine learning and clear strategic goals.
The world continues to evolve at a breakneck pace, and the myriad of ways in which companies collect, analyze and leverage customer data is evolving at a similar speed. As a result, customer experience professionals, data scientists, and digital marketing mavens must continuously keep their fingers on the pulse of this rapidly shifting landscape.
Currently, we stand at the precipice of 2024, and what better way to prepare for the potential challenges and growth areas we'll face in the coming year than a deep dive into the trends shaping the future of customer data and data management?
So let's discuss what's in store.
Customer Data: The Rise of Privacy Regulations and the Need for Compliance
The near future promises to witness an uptick in customer data thievery and abuse. Consequently, consumers are beginning to demand greater control over their personal information. This will almost certainly lead to a proliferation of regulations designed to enhance privacy across the globe, forcing teams to adopt a more compliance-driven, transparent approach to data management.
In fact, there were 5.5 billion malware attacks globally in 2022, an increase of 100 million from 2021. During the first quarter of 2023 alone, more than 6 million data records were exposed worldwide through data breaches. And what's even more concerning is that 71% of these breaches were financially motivated.
Phishing is one of the most prevalent cybercrimes, accounting for nearly 22% of all data breaches. Package theft is also becoming increasingly common, with 18% of Americans reporting they have had a package stolen that contained a gift for someone else.
Given this landscape, it's becoming more crucial than ever for businesses to prioritize data security. This includes implementing robust security measures such as tokenization, end-to-end encryption and data anonymization. It's also essential to stay updated on the evolving regulatory environment and invest in employee education and training to ensure full compliance.
To better prepare for this trend as we approach the new year, begin testing and implementing security measures now, or at least as soon as possible.
Related Article: The State of Consumer Data Privacy Legislation in 2023
Cross-Organizational Data Collaborations: The Next Frontier
Another trend that stands to revolutionize customer data management in 2024 is the emergence of cross-organizational data collaborations. Think of it as a grand social experiment in which organizations and institutions open their vaults of customer data to one another, pooling their vast resources to better understand their common client base and drive more targeted, effective growth.
As more companies recognize the benefits of cross-organizational data collaborations, we can expect to see an increase in these kinds of partnerships. But keep in mind success in this area requires investment in the right tools and a proactive approach to potential challenges.
Proactivity is the name of the game — don't wait for these collaborations to become ubiquitous; start exploring partnerships early and invest in analytics tools that can combine data from various sources.
Related Article: What Defines Customer Data Today?
The Customer Data Lake Phenomenon
Data lakes — vast, scalable repositories of raw data — promise to transform the way we store and analyze customer information. By enabling teams to tap into these boundless data reservoirs, it is now possible to glean insights that were previously inaccessible, informing more data-driven, targeted growth strategies.
An example of this can be seen in the case of a Middle Eastern theme park, as detailed in an ethnographic case study published on EPIC.
The theme park teamed up with a group of anthropologists and data scientists, aiming to make use of their big data to improve customer experience. They created a data lake that allowed them to gather and analyze customer data from various sources — including ticket sales, ride usage and customer feedback. This data lake enabled the team to gain a comprehensive understanding of their customers' behaviors and preferences.
By analyzing the collected data, they were able to identify patterns and trends. For instance, they found out which rides were most popular at certain times of the day, which food outlets were preferred by families versus individual visitors, and how weather affected visitor numbers. These insights were then used to optimize operations, improve customer service and enhance the overall visitor experience.
However, implementing a data lake was not without its challenges. The team had to ensure that the data was securely stored and properly managed. They also learned the hard way that the best way to effectively leverage data was to determine which questions they wanted answered before deciding on which data sources to pull from.
This goes to show that as more enterprises adopt data lakes as their default data storage hubs, teams will be compelled to integrate more sophisticated machine learning algorithms and analytics tools to process this plentiful data efficiently. During the excitement for these new possibilities, though, remember to have a clear vision in mind beforehand as to what insights in particular you want to glean.
Prepare for this development by outlining the questions you want to answer, embracing contemporary data lake architecture, and developing robust ML algorithms to ensure your organization is primed for the forthcoming data explosion.
Reimagining Personalization With Prescriptive Analytics
You’ve heard it before — personalization is a cornerstone of successful marketing and customer experience strategies; and as you’ve probably discovered, coaxing useful insights from extensive streams of raw data is no small task. Enter prescriptive analytics — a cutting-edge discipline that utilizes advanced algorithms and hot-off-the-press AI use cases to unearth patterns, trends and actionable insights from a dataset.
According to a report by Markets and Markets, the prescriptive analytics market is expected to grow from $1.16 billion in 2019 to $14.3 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 24% during the forecast period.
These statistics suggest that prescriptive analytics is not just a passing trend but a vital tool for businesses aiming to leverage their data for strategic decision-making and personalized customer experiences.
As this technique becomes mainstream in 2024, teams must prepare for the dawn of a new era in personalization by investing in AI-powered algorithms and developing their own in-house prescriptive analytics expertise.
2024 Trends in Customer Data: Staying Ahead in the CX Field
The future of customer data is surprisingly close at hand, and those who adapt will find themselves at the forefront of the CX field. As we stride headlong into 2024, keeping an eye on the emerging trends and technologies that are shaping the landscape will become more and more crucial. From cross-organizational data collaborations to organizing customer data lakes, from AI-powered prescriptive analytics to advanced personalization tactics, the tools at our disposal are becoming increasingly sophisticated.
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But as these methodologies evolve, so too must our strategies. Success in this new era will not just be about collecting data; it will be about how effectively we can manage, analyze, and draw actionable insights from it. As we prepare to navigate these changes, investing in the right tools, developing in-house expertise, and fostering a culture of innovation will be more important than ever.
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