Solutions
solutions
Consulting: Building a Framework for Customer Data Enablement
Actable can provide structured consulting engagements designed to right size the opportunity for customer data activation, develop a customized framework for activation, and chart a clear course for strategic, disciplined advancement.
Key areas of focus include assessments of:
- Business demands and use-case for customer data deployment
- Current-state readiness of data assets, technology, organization and team, software deployment planning and adoption
- Data science advancement and execution planning
- Customer Identity resolution planning
- Investment requirements and payback
Delivery: Delivering and Executing Customer Data Strategies
Our delivery practice takes ideas out of the theoretical realm and into reality. We bring an interdisciplinary ‘tiger team’ to your organization, ready to execute strategies our team develops or that accelerate previously-existing initiatives.
Services include but aren’t limited to:
- Marketing deployments utilizing advanced activation software (e.g. CDP, journey/personalization tools, etc.)
- Ongoing customer identity resolution management
- CDP implementation
- Upstream data readiness, sourcing, development, and engineering
- Custom audiences and customer segmentation
- Custom reporting and analytics solutions
- Advanced integrations and solutions architecture
Data Science as a Service: Enhancing Customer Data with Actable Data Sciences
Take your consumer data to the next level with predictive modeling and enrichments. Our Data Science team creates custom machine-learning models around your business goals and deploy them into your data environments and marketing systems.
Custom predictive models include but aren’t limited to:
- Propensity
- Churn
- Channel Optimization
- Next-Best Action
- Product Recommendations
- Predicted Value
Data Enrichments: Deepening Your Understanding of The Customer
Our machine learning models work in concert with additional data augmentation services, which take existing customer data sets and flesh them out, using either existing but disconnected data points, or purchased 3rd party data.
Typical examples include:
- Developing refined known-to-unknown data schemes
- Building customized customer views
- 3rd party data merges and onboarding, using secure, privacy-safe data transmission techniques
