4 Key Steps to Enhancing Marketing Personalization

Have you ever walked into a roomful of people only to have the person you greet look at you with a vague expression as they try to puzzle together how they know you and what your name is? Doesn't feel great, does it?

Marketing personalization works the same way. Customers respond better when they are acknowledged as individuals with unique preferences and needs. Using a one-size-fits-all marketing approach and hoping for the best is not enough for today’s consumers.

According to Adobe’s 2025 AI and Digital Trends Report, 71% of consumers surveyed said they want brands to anticipate their needs with personalized offers or helpful information, but only 34% of brands deliver.

Similarly, 78% of consumers expect a seamless experience across digital and physical channels, yet only 45% of brands meet this expectation.

Most companies know marketing personalization is a key driver of customer loyalty and engagement, but they are unable to deliver a tailored experience due to technical roadblocks.

Usually, the pieces to building a seamless, personalized experience are there, but connecting it all is a challenge, especially when your data isn’t clean. Here are some key steps you can take to improve your marketing strategy:

Personalization is only as good as the data driving it. Begin with a scalable approach to collecting behavioral data from web, email and app interactions using tools like Adobe Analytics, Google Analytics or Adobe Customer Journey Analytics. Once this is in place, a strategy for stitching online and offline data must be architected. Oftentimes, organizations overlook assets such as call center records, chat logs and in-store transactions. Integrating this into a broader dataset can significantly boost accuracy and relevancy in marketing personalization.

Use a data warehouse or lake to cleanse and validate incoming data before importing it into other platforms, such as a customer relationship management (CRM) tool or a customer data platform (CDP).

CDPs are the gold standard in unifying data sources to create powerful segmentation. These platforms merge diverse data sources into a single, unified profile that can be used across channels. If you don’t have a CDP, look for a platform that integrates well with the rest of your MarTech stack.

For example, if you are leveraging Salesforce Marketing Cloud for marketing automation and the Salesforce CRM as your customer database, then it may make sense to go with the Salesforce CDP. If you are using Adobe Analytics, Adobe Customer Journey Analytics, Adobe Journey Optimizer or Adobe Target, it may make sense to go with the Adobe Real-Time CDP.

Having native integrations between these platforms results in faster time to market, less custom development and enhanced capabilities for activation across platforms.

While it may be tempting to jump into more advanced personalization techniques, it is important to first master behavioral segmentation, which involves categorizing users based on their interactions, such as website visits, email engagements or purchase history.

This is typically the first step for organizations looking to personalize their marketing efforts because it introduces a clear way to speak to customers based on their behavior.

By using your data, you can begin dividing customers into segments based on patterns, such as repeat visitors versus one-time visitors, and tailor content accordingly. A/B testing is often underutilized and can help you explore which segment-specific messaging resonates best with your audience.

Once behavioral data is in place, attribute-based segmentation takes personalization to the next level. Attribute data provides a clearer picture of your customer and helps fill in the gaps about their demographics, geographic location, values, interests and more.

Again, data is the key. By integrating all of your relevant data sources, you can begin tapping into some of the less obvious details. Platforms like Adobe Customer Journey Analytics and Salesforce Marketing Cloud can help with this intermediate step.

One of the biggest challenges with marketing personalization is keeping up with your audience as both people and trends change. Clearly, this can throw a wrench into any targeted marketing efforts, especially if you cannot quickly adjust. Artificial intelligence (AI) can analyze massive datasets to help you usher in hyper-segmentation, real-time personalization, predictive recommendations and more.

AI-driven personalization can significantly speed up your ability to pivot and adjust on the fly. However, it is important to test and refine personalization strategies manually before deploying AI tools. Poorly executed AI can frustrate users and erode trust, so focus on creating an experience that feels intuitive and helpful versus intrusive and erroneous.

By focusing on a solid data foundation, gradually moving toward advanced strategies and ensuring your team is aligned around a single personalization roadmap, your organization can greatly improve its marketing personalization efforts.

Working with a trusted expert that can help you develop a roadmap, improve your data quality and identify the right technology for your company can help you avoid common pitfalls.