Data Trends for 2024

More than ever, data and analytics play a crucial role within companies and society as a whole. With various trends and developments reshaping our interaction with data, 2024 promises to be a significant year. Large Language Models and other applications within artificial intelligence offer new possibilities. And of course, it’s also important to keep an eye on the increasingly stringent privacy regulations. Time is ticking, and the importance of first-party data is growing.

We have compiled a list of important data trends for 2024. This is how you can make the most of the new developments in the data world this year!

First-party Data

One of the most important data trends for 2024 is the increasing importance of first-party data. Chrome will soon stop using third-party cookies. Google wants to get rid of cookies to make the internet a ‘more privacy-friendly place’.

With the new ‘Tracking Protection‘ feature, third-party cookies will be completely blocked. This means that you will unfortunately have to say goodbye to your data from third parties.

But what does this actually mean for you and how do you deal with it? No more data in your visitor’s browser means more focus on data collection on your own server side.

In other words: first-party data. This is first-hand data. This data comes from your own systems; it’s all the information about customers and visitors to your site that you collect and combine yourself. This data thus varies from contact details to information about online behavior collected based on cookies. Having this data well-organized is extremely important.

Server-Side Tag Management

A good first-party solution is server-side tag management. In this approach, the website sends data about the actions being performed to its server, which then sends it to the analytics provider (such as Google Analytics).

So it’s a good solution to still have access to the valuable data about your website visitors. Server-side tag management has many advantages such as better data security and efficiency.

Google Consent Mode

As you know, since the start of the GDPR law, explicit consent must be given for almost all cookies related to data collection. Due to this development, Google quickly came up with Google Consent Mode, allowing you to continue collecting sufficient data in a privacy-friendly manner.

Google Consent Mode ensures that Google’s cookies (for example Google Analytics, Google Ads and Google Tag Manager) are only activated where the user has given explicit consent.

Recently, Google consent mode has transitioned to V2. If you want to continue using Google Ads products and do remarketing in Europe, you must implement the new version of Google Consent Mode before March 2024. What does that entail exactly? We’ll explain it to you:

In the new update, two new parameters have been introduced. Previously, there were 5 options regarding Google consent: ad_storage, functionality_storage, personalization_storage, security_storage and analytics_storage. As we move towards an increasingly privacy-friendly internet, the enforcement of EU policy for user consent is being strengthened.

In version 2, users in consent mode must submit two new parameters in addition to ad_storage and analytics_storage:

Ad_user_data: Sets consent for sending user data to Google for online advertising purposes.

Ad_personalization: Sets consent for personalized ads.

So it’s important to switch to Google consent mode V2 before March. Users who are not using Google Consent Mode v2 by March 2024 will not be able to use Google Ads and will not be able to acquire new users from Europe.

Customer Data Platform

You’ve probably come across it before: Customer Data Platforms (CDPs). CDPs can come in handy in a time when customer data is spread across different systems. By centralizing all data in a CDP and building 360-degree customer profiles, companies can use the data effectively and maximize Customer Lifetime Value (CLV).

A CDP offers you full control over customer data and enables personalization, which leads to an improved customer experience and higher engagement.

On the other hand, Data Management Platforms (DMPs) are more focused on collecting and managing data for marketing purposes. Choosing the right CDP requires thorough research and can have a significant impact on your marketing efforts and business processes.

Data Safety

After all this information about data, it’s important to realize that with great data comes great responsibility. That’s why encryption, multi-factor authentication, and regular security audits are necessary.

Trust is key; your customer data must always be secure. Data security is not a fun or exciting topic, but it is something you need to be even more aware of next year.

Think about which new developments you want to support and work with clear guidelines within your company. For example, how do you ensure that you don’t just put all your (customer) data into open source AI applications?

Large Language Models

The final data trend that could play a major role in the coming year is the rise of Large Language Models.

A large language model (LLM) is a type of artificial intelligence (AI) trained to understand, generate, and manipulate human language. It consists of algorithms that analyze millions of pieces of text to understand how language works and then use this knowledge to generate human-like texts.

Using advanced algorithms, LLMs learn how human language works. They can be trained on various language and linguistic tasks, such as text analysis, translation, question-answering systems, summarization, chatbots, and much more.

This year, LLMs will play an increasingly important role in the data world. If they gain access to large amounts of data, they can provide a lot of valuable context in combination with graphs.

Many organizations still struggle with their data because up to 80% of it is unstructured or lacks semantic meaning.

Fortunately, LLMs can filter and classify unstructured data, allowing valuable insights to be extracted from otherwise “messy” data, such as customer support and sales conversations.

A nice feature of LLMs is that they can learn from textual data, for example from the internet. This means that they are continuously developing and can become increasingly better at understanding and generating human language as they are trained on new data. This means you can also ‘train’ LLMs.

The longer they are used, the better they can function within a company or organization.

Conclusion

There are plenty of trends you need to keep an eye on this year! From first-party data solutions to Large Language models: we are curious to see what the new year will bring us.

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