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Value-Based Outcomes are defined areas of focus that help you measure the value of a CDP to your overall business. When it comes to building use cases in BlueConic, all of them should roll up to at least one Value-Based Outcome to prove its significance to your business goals. If a use case does not apply to a Value-Based Outcome, it may not be worth the effort.

Value-Based Outcomes can be seen as a type of broad use case, with multiple smaller, more specific use cases underneath a hierarchy. One Value-Based Outcome could have a dozen specific use cases.

Value-Based Outcomes for your CDP use cases

1. Higher data quality

   This area focuses on improving data confidence and providing your business with the most comprehensive, up-to-date consumer records. When you have higher quality data and better data confidence, you will have a better approach to consumer data risk.
   • Examples of higher data quality use cases:
     • Creating a first-party "Golden Record" of PII information by connecting off-site and on-site data to stitch customer data together and continuously improve upon it to make it available for activation or insights.
     • Using the unified profile in BlueConic to identify gaps and inconsistencies in data that sits in other systems.
     • Transforming data to normalize information from other systems so it can be used in your use cases.
     • Moving from third-party data to first-party data using identity resolution to improve target audiences for advertising.

2. Increased agility & flexibility

   This area focuses on ensuring you can adjust how you engage with your data, quickly, in a world where things are changing all of the time. A key piece of this is giving you the ability to be agnostic about the data sources and types that are part of your systems.
   • Examples of increased agility & flexibility use cases:
     • Building, deploying, and activating custom-built plugins with BlueConic's range of public APIs and development toolkits.
     • Eliminating manual processes that require handoffs between teams.
     • Easily adding or removing data sources to BlueConic and connecting that data source to your martech ecosystem.
     • Transforming customer and transactional data on-the-fly with user-friendly, configuration-based imports, without the need for hard-to-use ETL tooling.
     • Working from a CDP that has up-to-date data and can automate your workflows for sending them to activation.

3. Mitigated consumer data risk

   This area focuses on minimizing the leaks and delays associated with consent management and providing consumers with control over their data.
   • Examples of mitigated consumer data risk use cases:
     • Using Objectives to have BlueConic allow or restrict the flow of individual data points to other platforms, including clearing data where consent is no longer active.
     • Offering consumers control over their own data via a marketer-configurable privacy preference center.
     • Automating GDPR compliance request handling.
     • Exporting or syncing consent to other platforms that sit downstream from BlueConic for consent management.

4. Improved analytics & insights

   This area focuses on providing you with insights that improve your understanding of the performance of your programs and who your customers are. This takes insights one step further by making sure they are actionable.
   • Examples of improved analytics and insights use cases:
     • Tracking email engagement on the profile timeline and pushing event information out via a connection for further analysis.
     • Training and applying ML models (RFM/CLV) on profiles with purchase data.
     • Showing trends in revenue by demographics.
     • Calculating consumer LTV by subscription, offer, store location, product category, etc.
     • Customizing reporting on profile and timeline data generated by AI Workbench.

5. Smarter customer engagement

   This area focuses on communicating with customers in smarter, more actionable ways that are creative and dynamic.
   • Examples of smarter customer engagement use cases:
     • Using BlueConic Lifecycles to capture a customer where they are in their own journey and orchestrate messaging.
     • Increasing resonance and relevancy of select triggered or scheduled emails through data-driven segmentation to increase engagement.
     • Adding ML-based product recommendations.
     • Targeting on advertising networks with relevant messaging using data-driven segmentation or excluding those who you knew are a customer already.

Over time, a successful CDP implementation will drive improvements in all of these areas. But if you're just starting with BlueConic, try focusing on your top priority areas first and working your way out to the others.