Customer Data Integration
Big Data Segmentation of Major Decisions
Challenges
Customer Data Integration
CDI uses Standard data integration techniques, to represent a specific customer across multiple touchpoints with your company. According to Acxiom, CDI involves:
- Cleaning, updating, and supplementing missing customer contact data
- Consolidate relevant data sets, clean duplicates, and merge records from different sources to enable customer (or donor) recognition at every touchpoint.
- Enrichment of internal and transactional data with external knowledge and segmentation
- Compliance with „contact suppression“ and data protection regulations to protect the customer and the company
Customer segmentation
Together, CDI and segmentation can support the company's growth drivers, such as Customer Relationship Management (CRM), brand awareness, customer loyalty, and IT initiatives like Business Intelligence, Predictive Analytics., Master Data Management (MDM), Data Loss Prevention (DLP) and compliance with data protection regulations.
However, along the way, there are several challenges that can make it difficult to gain a customer overview or segment, or to extract the necessary insights for better business decisions. With very large datasets, customer segmentation analysis can be a slow and very difficult process, taking place on complex and costly platforms. It can expose sensitive data that requires specific, integrated protection. Your current approach may also lack the audit trails from these processes, which are necessary for internal and external review.
Solutions
Unlike massive, online (database) and flat-file sources of customer and transaction data, Sort Control Language (SortCL program in the IRI Voracity platform or the IRI CoSort-Subset-Productthe ability to integrate and report results simultaneously across different subsets, views, or filtered groups.
Powerful functions for selection, deduplication, sorting, merging, aggregation, and reformatting combine CDI, staging, and segmented reporting within the same job script and I/O pass. Create as many outputs as necessary, based on defined conditions and in customized formats.
Use various selection criteria for customer segmentation, including:
- Name, Age, Address, or Date Ranges
- Account or other identification numbers
- Transaction or Product IDs (SKUs)
- Website visits or IP addresses
- new, modified, deleted, or duplicate data
Uses built-in field-level encryption (or other features for Privacy protectionto prevent the disclosure of sensitive data based on required knowledge.
Every time SortCL is run, it can create a complete XML audit log. This allows you to examine user, job, and runtime parameters to perform detective controls and verify compliance with data privacy regulations.
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