Dave Bilbrough spoke to partners at the 2018 Adobe Summit about how Adobe has been transforming experience through the use of enterprise big data within the Adobe cloud platform. As machine learning and artificial intelligence continue to evolve and shape customer experience, leveraging Adobe Cloud Platform to author, import or use pre-built intelligent services based on machine learning and AI technologies is the next technology frontier.
A compelling digital strategy aligns customer experiences, business execution, and the right technology as the market and your competition constantly evolve. Our Digital Essentials highlight the most compelling aspects of all three to help you react and respond to this ongoing evolution.
The opportunity for truly unique data comes from combining data. The complete picture can only be drawn by taking all the data collected through the Adobe Cloud platform and marrying it to the enterprise data. Pulling all the pieces together from enterprise data stores, related to audience activation and campaign orchestration opens new avenues for capturing revenue and engaging users.
To demonstrate the power that this yields, Mr. Bilbourgh provided three case studies to show some of the possibilities from real-world scenarios; two examples from specific implementations with Time-Warner Cable (TWC) and one from T-Mobile. I will address only one of the Time-Warner Cable examples. Read all of the details below:
The Case Example
The case we seek to address is referred to as the “Promo Roll-off” case. This is when a customer has promo offer that has expired, and TWC would like to convert the promo offer into a sale.
The high-level data interaction followed this pattern:
1. The promo data was captured from an internal database and uploaded into Adobe Data Workbench.
2. Data workbench processed the data and forwarded the customer to Adobe Campaign.
3. The web session is brokered by Adobe Experience Manager with component targeting the specific user.
4. Campaign receives the call and executes the business rules and passes offer back to Experience Manager.
5. The user has presented the offer and can choose to act.
Some of the additional considerations were part of the solution:
-Marketing & Product Management define where the targeted interactions point were to be placed.
-Development of custom Experience Manager components to communication with Campaign.
-Campaign team defines and maintains the business rules.
-Experience Manager authors place a custom component on the page and maintains the page.
Through the use of Data Workbench, the power of external data is leveraged to extend the knowledge of the customer and drive unique actionable content to them. The ability to extend this beyond just the inclusion of data, but to expand this to take advantage of Machine Learning or Artificial Intelligence in possible.
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