Customer Insights – DataConnect fragmented customer records into unified profiles, segments and insights. We implement Customer Insights – Data so marketing, sales and service can work from a more consistent customer view.
Start with reliable sources and identity rules, then add the measures and audiences that support a real business decision.
Import customer information from supported sources and configure refreshes around business needs.
Use matching and merge rules to bring records from different systems into unified customer profiles.
Connect purchases, subscriptions and other activities to the profile for a clearer history.
Calculate customer measures and create audiences using profile attributes, activities and business criteria.
Add supported enrichment data where it provides useful context and the required provider access is available.
Make selected profiles and segments available to connected applications through supported exports and integrations.
Choose a useful role for AI, then define the information, access and review needed for that role.
Evaluate supported churn models against the required transaction or subscription history. Use the score as a signal for a reviewed retention process.
Use supported lifetime-value and recommendation models when the available data meets model requirements. Agree how the business will act on the results.
Explore customer data using natural-language questions in the documented Copilot preview. Check the underlying measures, audience definition and answer before using it.
Combine the agreed product configuration with the systems and development that make the complete experience work.
Link commerce and membership activity to a profile, then offer an eligible digital membership pass through a connected service.
Discuss a Unified Loyalty & Wallet ProfileCombine renewal history, service context and a supported churn prediction to identify customers who need attention.
Discuss a Retention Signal That Starts ActionShow relevant customer history and measures where sellers or service representatives already work.
Discuss Customer 360 in the Team WorkspaceChoose an example to see the work, decision, handover and completion point.
Follow the work through the decision, handover and confirmed result.
Import CRM, membership and commerce records with stable source identifiers.
Review match rules and resolve sample false matches or duplicates.
Calculate the agreed membership and loyalty measures.
Send eligible data to the pass service and consuming applications.
Measures to Agree
Reviewed matches meeting the agreed acceptance criteria.
Customers represented in the required source combinations.
Eligible records delivered to the destination.
Confirmed activity from the connected loyalty system.
Follow the work through the decision, handover and confirmed result.
Load the relevant subscription, transaction and activity records.
Check model prerequisites and assess useful prediction quality.
Apply business rules, exclusions and communication permissions.
Activate follow-up and bring confirmed renewal events back into reporting.
Measures to Agree
History meeting the model input requirements.
Reviewed customers suitable for the retention action.
Selected customers receiving an owned next action.
Confirmed renewals from the source system.
Follow the work through the decision, handover and confirmed result.
Monitor the agreed ingestion schedule and failed updates.
Apply identity rules and refresh customer measures.
Serve the authorised profile in the consuming workspace.
Record missing or conflicting information for the data owner.
Measures to Agree
Elapsed time since the last successful source refresh.
Customer requests returning the intended profile.
Reviewed conflicting attributes requiring correction.
Team use of the customer context in the workspace.
Use the application that owns each record and make the handover between systems explicit.
Agree the business outcome, prepare the foundation and validate the complete experience before expanding it.
Choose the first process, its owner, completion criteria and baseline measures.
Identity rules, source history, refresh frequency, consent ownership and prediction prerequisites determine the implementation scope.
Configure or develop the agreed experience, permissions and system handovers.
Check realistic data, permissions, exceptions and confirmed outcomes. Prepare the team for a controlled launch.
Review source-confirmed results, operational issues and adoption before extending the next use case.
The starting point depends on the process and the systems you already use.
Data unifies records and creates customer insights. Journeys coordinates communications and follow-up. They can work together, but source quality, identity resolution and activation should be scoped as separate responsibilities.
Start with a specific task and the evidence needed to evaluate it. We check current feature status, environment prerequisites, data quality, permissions and cost. Preview capabilities are assessed separately from the agreed production scope.
The examples describe configured or custom solutions. The feature cards explain the product or delivery foundation; each use case and process identifies the connections, development and related services it needs.
Identity rules, source history, refresh frequency, consent ownership and prediction prerequisites determine the implementation scope. We also agree ownership, acceptance criteria, operating responsibility and the first measurable outcome.
Explore the applications, data platforms, and development capabilities that can support your requirements.
Browse practical use cases for payments, subscriptions, portals, approvals, customer communications, and connected operations.
Tell us where customers or teams lose time, context or a clear next action. We’ll help identify a practical starting point for Customer Insights – Data.