Most Customer Data Platform (CDP) vendors emphasize use cases to illustrate why businesses need a CDP. With the countless potential applications a CDP enables, focusing on impactful cases is a practical way to kick-start a CDP purchase. However, after implementing a CDP, the real advantage lies in adopting a continuous test-and-learn approach, which will allow your company to explore and validate new strategies with agility.
For instance, you might want to test if an AI-driven audience model improves retargeting campaign results or if A/B testing different landing pages boosts app downloads. Such experiments provide the evidence to support further investments in data-driven strategies.
Why a Test-and-Learn Process for CDP Use Cases?
A test-and-learn approach helps your marketers allocate resources efficiently and focus only on strategies that demonstrate real results. It also provides data-driven proof to justify further CDP investments. This way, your team will quickly develop vital use cases, achieve significant results in days or weeks instead of months. Let's dive into what we really mean by a test-and-learn approach, and how you can implement it:
- Define Your Use Case Objectives - Set a specific, measurable goal for the use case. For example, instead of vaguely aiming to "increase acquisitions," specify: "increase acquisitions from anonymous website visitors by 3%." Make sure that you do this for each use case.
- Ideation - Gather key stakeholders to brainstorm use cases and strategies for reaching your goal. If aiming to convert more anonymous visitors, consider personalizing pages, refining CTAs, or using identity resolution to better target unknown users.
- Review - Evaluate proposed ideas, narrowing down to use cases that seem both feasible and impactful. Assign scores based on effort and potential impact to streamline decisions.
- Prioritize - Rank use cases by expected impact and required effort. You may opt to start with quick, low-impact tests to build momentum or tackle high-impact tests first, depending on resources and urgency.
- Research - Ensure all necessary data sources are connected to the CDP to support testing. CDPs make this easier by integrating new data sources quickly, enabling immediate access to relevant data.
- Design - Create the content, messaging, and assets required for testing. This could involve crafting landing pages, feeding AI models with creative variants, or designing banners.
- Develop and Launch - Build and deploy the use cases. Many companies stop here, missing the critical step of analyzing outcomes.
- Analyze Results - Measure the success or failure of each test, using metrics available through the CDP.
- Optimize or Move to a New Use Case - Based on results, either refine the successful strategy or pivot to the next hypothesis. If a homepage banner personalization did not impact conversions, try retargeting campaigns or other approaches.
- Report the Results - Summarize findings and link them back to initial goals. For example, if personalization on the homepage had minimal impact, retargeting on paid media led to a 5% increase in conversions, validating a shift in focus.
Note: This article is a summary of an original source on relay42.com. Go to the article here.
