Data Quality and Integration

 

Data Quality Pays!

Continually monitored, updated and protected.

Data quality is the foundation of safeguarding and maximizing customer information assets that empower you to make informed decisions, increase sales, profits, customer satisfaction and retention. We employ systematic processes that are continuously and comprehensively monitored to ensure the highest level of data quality.

Working inside the data we’ll deliver the greatest return on your marketing investment. With NCOA we know who moves and where. CASS ™ will certify addresses, and we’ll transform, recode and eliminate duplicates, leverage relationship links, suppress when appropriate, and take full advantage of a wide range of both consumer and business demographic overlays.

Data Blending – When you have multiple sources of data you will need to combine them into a single data set with common identifiable data elements and data origin information. This is the first step toward improving data quality.

Data Audit – Understand what you have to work with and what is missing. An audit with comprehensive statistics and summaries on each data element is essential to determining what steps are needed to properly standardize and recode values. When you have a baseline on the quality of your source data you can measure the value of the improvement of your data assets.

Data Definition – Central to data quality improvement is a shared, common data dictionary. The effort improves the result of all future projects involving integrated customer data.

Address Standardization and Validation – Inspect postal addresses to ensure consistency, deliverability and improve duplicate identification and detecting multiple relationships within a household. CASS certification guarantees favorable delivery costs and performance.

NCOA – National Change Of Address processing is an important step for prospect and lapsed customer addresses.

Email Audit – Improve your email list and preserve your reputation with Email Validation, Hygiene, & Correction.

Duplication Identification – a key step in reducing waste, verifying cross business relationships, and assessing the best sources for prospective customers.

Relationship Identification – Create persistent relationship keys at account, individual, household and business levels to continuously measure the value of the relationship, budget and communicate appropriately with the customer. This is an essential step for professionally managing a longitudinal customer repository.

Data Enhancement – Augment customer data with 3rd party demographic and behavior data for profiling and modeling.

Data Appending – Add digital contact information through matching to email and digital repositories.

Data Aggregation – Create relationship level aggregations and summaries that utilize transactions from various systems; order management, customer service, product registration, contact history, etc.