June 10, 2024
Achieving effective personalization requires structuring your data correctly. Here are three considerations to guide this process.
Amanda Giacobassi
Today’s consumers and businesses expect personalization in their marketing – this is no longer a luxury but a necessity. Personalization is what enables you to send relevant, and therefore more effective, communications to your customers and prospects.
For example, as an airline, you might want to send relevant vacation packages or destination recommendations to increase marketing ROI.
However achieving this type of customer experience seems like a self-evident goal, so why do more enterprises not do it already? The reason is that, for most, their data is not properly organized and integrated across their platforms to achieve this type of personalization at scale.
Scaling and automating personalization across a vast enterprise database, multiple product lines, marketing channels, and content formats require tackling an unglamorous but key building block: structured data. This concept can be defined as data stored in a standardized format that is both easily human and machine-readable.
Organizing, cleaning, and structuring your data involves tasks such as securing business agreement on where and how field-level data will be stored, creating automated flows to classify raw data into the structured format, executing a cleanup or purge of historical data, and monitoring structured data fields for accuracy and compliance.
Three Considerations When Structuring Data
Achieving effective personalization requires structuring your data correctly. Here are three considerations to guide this process.
#1 – Align on How Data is Populated
To effectively structure data, it's crucial to gain alignment on how data is populated across your organization. For instance, your sales team might be responsible for updating customers' product interests—a field that requires ongoing maintenance.
Similarly, smart campaigns automatically assigning sources need regular oversight to ensure new lead sources are integrated, preventing data gaps. This alignment helps maintain a consistent and reliable data foundation, which is critical for accurate personalization.
#2 – Define Which Data You Want to Personalize
Not all data can or should be personalized. It's crucial to identify key data fields that will drive your personalization strategy. For example, if you are focusing on industry-specific personalization, there should be a dedicated field that categorizes each vertical accurately. Conduct a thorough assessment to determine the origin of this data—whether it stems from marketing activities, sales inputs, or product usage. Ideally, consolidating data from a singular source reduces complexity and enhances consistency, streamlining the personalization process.
#3 – Ensure Data is Accurate
The accuracy of your data is the cornerstone of successful personalization. Here’s how you can implement a meticulous process to validate and monitor data integrity:
Consistent validation and monitoring of these data fields are crucial. Although this demands additional effort, maintaining clean and reliable data is vital for crafting relevant and impactful personalized experiences. A structured data approach ensures that your personalization initiatives are built on solid ground, leading to enhanced engagement and stronger business outcomes.
Building a Strong Foundation for Success
When data is structured effectively, it provides the foundation for personalization. This involves achieving alignment on key data fields, consistent monitoring, and regular re-evaluation of personalization fields. Periodically adjusting to changes, such as new product data or market shifts, ensures that your personalization efforts remain relevant and impactful. By maintaining these practices, your organization can deliver highly engaging and effective personalized experiences.
Does your organization need help structuring data? Learn how the Marketo experts at MERGE can help. Contact us today!
