4 Data Activation Trends to Look Out for in 2024

Data-driven marketing has been around for years, but the use of customer data platforms (CDPs) is relatively new to the space and changing every aspect of data activation. Trail-blazing digital marketers are taking advantage of enhanced, first-party customer knowledge to drive their marketing efforts.

Here are the most prominent emerging data activation trends for 2024:

AI-Driven and Omnichannel Journey Orchestration

Machine learning and artificial intelligence (AI) top our list for 2024, to the surprise of no one. Since ChatGPT burst onto the public scene in late 2022, it’s hard to find any profession without a strong opinion about AI, positive or negative. And although generative AI draws all the public attention, savvy marketers are looking at how these same self-learning systems can deliver Next Best Experiences (NBX) to improve marketing outcomes.

How this works in journey orchestration starts with the rich data store of real-time CDPs. By integrating offline and online data to support the creation of finely tuned audience segments, businesses can optimize campaigns across all channels, from web and email to video, social, and mobile apps.

NBX is delivered by micro-segmenting customers based on their precisely construed intent or interest, with decisioning on how to proceed taking place in near-real-time. Just as the military has leveraged OODA loops (Observe, Orient, Decide, Act), AI takes the same approach to grow customer loyalty, sell new offers, and generate other positive business outcomes.

Audience Modeling

Once the domain of DMPs, CDPs are adopting new modeling techniques to better analyze customers. Audience modeling can enhance targeting and increase marketing focus. Lookalike Modeling: This takes all your existing customer segments into consideration and expands on them. Through demographic and behavioral data, lookalike modeling helps you find potential customers who share the same characteristics as your existing customers and reach out to them.The next best option is to eliminate unqualified prospects. Businesses always have ideal customer characteristics and traits in mind. If an audience member doesn’t fit your target demographic, you can remove them from your marketing campaign. Data can be used to identify disqualifying features and make your marketing campaigns more efficient and effective. Predictive Modeling: Predictive modeling is usually associated with statistics, but it’s making its way into modern digital marketing. The technique involves finding customers or prospective customers based on their purchase behavior and demographics.Despite the name, “predictive” modeling does not involve predicting the future. Instead, it takes advantage of data analysis techniques to target customers based on their known behavior and demographics data. From direct mails to social media advertisements, predictive modeling uses various types of data to target customers. Algorithmic Modeling: Algorithmic modeling helps implement marketing automation for data scientists and digital marketers alike. It collects data from data management platforms, advertising data and retail data to identify potential customers. Algorithmic modeling is a mix of economic theory and machine learning, and it helps create the right marketing strategies. It can not only help with customer identification and marketing but also in developing pricing strategies based on customer data.

Intelligent Media Optimization

One of the most critical techniques online businesses are adopting is media optimization. While social media marketing, mailing lists, and direct messaging are standard practices, over-saturating your audience with promotions can hurt the returns on investment for your marketing teams. This is where media optimization techniques like audience suppression come in — enhanced by the greater customer awareness a CDP provides. For example, if you’re selling products or services that see long-term usage, you shouldn’t invest in ad campaigns for your existing customers. Instead, focus on value-added services for items they’ve already purchased. Audience Suppression: Many advanced businesses take advantage of application programming interfaces (APIs) to conduct real-time audience suppression. Modern tools can monitor data in real-time and notify businesses when they identify audience members who are unlikely to react to your marketing campaigns. Frequency Capping: Custom data management platforms can help you customize your marketing campaigns. Specific ads will reach your audience only when they meet certain criteria. Instead of taking a one-size-fits-all approach for your audience, businesses are leveraging data to segment their audiences and avoid unnecessary retargeting. Retargeting: Retargeting campaigns are designed to remind website visitors to check out products and services on a website after they leave pages without making a purchase. Taking advantage of customers’ web browsing data, relevant ads can be displayed to try turn them into buyers. 

Ecosystem & Architecture Integrations

This was on our 2023 list, but it’s still relevant because efforts to reduce tech debt and intensify integrations are growing at an accelerated pace. Staying ahead of the competition in a developing digital economy isn’t easy. It’s necessary to deploy new technology capabilities to give your data-driven digital marketing strategies an edge. Ecosystem Integration: In addition to providing rich business process functionality, data management platforms need to integrate applications, data sources, sales channels, and other important systems. Digital business platforms are adopting service-oriented architecture and other integration mechanisms that are designed to easily integrate with other systems. Businesses have recognized that there are barriers to communication between marketing teams, advertising and media teams, and data analysts and data scientists within an organization. They’re beginning to break down the barriers to communication and adopt a tighter, more cohesive ecosystem. Teams are working together and trying to relate to a customer’s journey. Through proper collaborations within an organization, businesses can create fully informed relationships with their customers. Architecture Integration: By centralizing the architecture of data management platforms, businesses can integrate analytics, data management, marketing, and sales in one place. All stakeholders and teams are exposed to a centralized system that allows them to collect data and work toward better marketing communications. Centralized architecture also leads to more transparency within the business.

The Bottom Line

By focusing on data-driven marketing, businesses can connect with their customers better than ever before. The use of data management platforms in marketing is trending in 2024, as more businesses understand the importance of integrating their marketing, sales, and data operations.

• Data Management and Activation
• Data
• Digital Marketing
• SEO
• Data Management Platform
• Customer Data Platform
• Media Optimization
• Data-driven Marketing
• Analytics