Adobe Customer Journey Analytics | Prepared for Deluxe
Deluxe can build on its Adobe Analytics foundation to connect digital behavior with customer, order, service and lifecycle context. The goal is not more reporting. It is a clearer view of the journeys that create, retain and expand customer value.
Executive point of view
Deluxe has a strong reason to modernize analytics without discarding the value already created in Adobe Analytics. Adobe Analytics answers important questions about digital properties and digital interactions. Customer Journey Analytics extends that investment to questions that span customers, channels, orders, service interactions and time.
The next analytics question is increasingly not “what happened on the website?” but “what happened across the customer journey, why did it happen, and what should we learn from it?”
Deluxe reality
Deluxe reality
Deluxe reality
Deluxe reality
What CJA solves
Each one is a place where a digital-only view runs out of context.
Fragmented journey visibility
Bring web and other experience data together with customer, call-center, transaction and service data so analysis can follow the connected journey.
Digital-only context
Extend analysis beyond pages and sessions to calls, call reasons, orders, repeat behavior and service outcomes when those datasets are connected.
Identity fragmentation
Use appropriate identifiers to analyze the same person across digital and offline interactions, subject to Deluxe data and governance choices.
Slow question-to-answer cycles
Reduce repeated piecing together of separate web and call-center views and enable flexible journey exploration in a shared analytical environment.
The incremental value
Deluxe would have two years to transition from Adobe Analytics to CJA. Adobe Analytics is the digital analytics foundation Deluxe has built on. CJA expands the analytical canvas when the business question crosses channels, systems, identities or lifecycle stages.
| Dimension | Adobe Analytics foundation | Incremental value with CJA |
|---|---|---|
| Primary scope | Digital interaction and digital property analysis | Journey analysis across connected online and offline datasets |
| Customer view | Digital visitor and session analysis | Person-level analysis across connected interactions when identity and data are available |
| Attribution | Digital attribution approaches | Apply attribution across connected web, call-center and order outcomes |
| Analysis experience | Workspace-based exploration | Familiar Analysis Workspace patterns extended to broader journey data |
| Business questions | What happened in a digital experience? | What happened before and after the digital interaction, and which journey produced the outcome? |
Customer-validated opportunity
Core business question
Which customer journeys should remain digital, and which benefit from an assisted interaction?
Web, CRM and call-center data are the primary sources of interest, and today those interactions live in separate places. The business need is broader than call deflection: understand the economics of the channel transition and make better decisions about where to remove friction versus where assisted service contributes value.
Analyze what customers were doing on the website before a call and where the digital-to-call transition occurs.
Use call reason and journey context to distinguish routine needs that may be suited to self-service from interactions tied to order creation.
Trace web pages, searches and call reasons through to call-center orders to understand which paths contribute to successful outcomes.
Provide connected views of web and call-center behavior instead of repeatedly reconciling separate channel datasets.
Print business
Use case 1 of 5
CJA analysis
Connect web activity, person and customer context, call interactions, call reasons and orders. Analyze which journeys should self-serve versus transition to assisted service.
Use case 2 of 5
CJA analysis
Connect prior orders, website behavior, campaign and service interactions, and reorder outcomes.
Use case 3 of 5
CJA analysis
Analyze browse, search, configuration, cart and checkout behavior alongside completed online and assisted orders.
Use case 4 of 5
CJA analysis
Compare connected pre-lapse and retained journeys to identify experience patterns associated with declining engagement or purchase.
Use case 5 of 5
CJA analysis
Identify behaviors and experiences that distinguish one-time buyers from customers who place a second order.
Adobe CX Enterprise Coworker
Adobe CX Enterprise Coworker can make connected customer journey data more accessible and actionable for Deluxe teams. Once web, call-center, CRM and order data are available for analysis, a Deluxe user could ask in natural language:
Why did online conversions decline?
Where are customers falling out of the purchase journey?
Which digital interactions are associated with customers moving to the call center?
Coworker supports data exploration, root-cause analysis, anomaly investigation and stakeholder-ready summaries. Teams can move from identifying a change in performance to investigating the underlying drivers without first building a new report for every question.
Example prompt
“Why did online order conversion decline last week? Identify where customers dropped out of the digital journey and whether those customers subsequently contacted the call center.”
An illustration of how Coworker’s root-cause and journey-analysis capabilities could apply to Deluxe.
For Deluxe, that could help teams more quickly distinguish digital friction that may warrant improved self-service from assisted journeys that contribute to successful order outcomes.