Improve your data quality.
Improve your bottom line.
Data is used in a myriad of business-critical processes. Each year, companies lose trillions of dollars due to poor data quality. That's why it's essential to understand how data issues are affecting your business.
$15MM
That's the annual average cost of data-quality issues to organizations according to Gartner.*
*Source: Smarter with Gartner
Data Quality Management and Metrics
Data discovery
Access a complete enterprise metadata picture. Search, discover and understand data relationships.
Data profiling
How good is yours? See if your data is fit for use by directly profiling your files, data stores and logical models.
Global address management
Verify, validate and standardize data in real-time for 220 countries.
Global name recognition
Match, standardize, analyze and/or consolidate complex records with confidence.
Data validation and standardization
Attain improved speed, accuracy and processing abilities across various formats and sources.
Advanced name and address matching
Gain a clearer picture of your customers with name and address matching features across databases.
Data Stewardship
Correct, approve and incorporate efficiency exceptions into your collaborative data quality process.
Smart Data Quality
Smart data quality is smarter. Achieve better matching accuracy at lower costs. Automate and accelerate your entity resolutions.
Flexibility. Accuracy. Intelligence.
Gain the accuracy you need, at scale
High-volume data verification and standardization for robust profiles, linkages and enrichment.
Deploy as desired
From a single server to big-data platform with our advanced architecture and open systems design .
Built-in learning capabilities
Continually improve speed, accuracy and processing ability for data integrity and entity resolution.
A flexible pricing model
Find the solution for your specific needs.
Pitney Bowes Spectrum™ Technology Platform improves the completeness, validity, consistency, timeliness, and accuracy of your customer data via data standardization, verification and enhancement. Ensuring that your customer data is accurate, complete and up to date enables your firm to better understand and connect with your customers.
"Poor quality customer information is rampant in CRM and inhibits customer relationships and outcomes."*
*Source: Forrester "Fix data problems that destroy customer effectiveness".
The L’Occitane Group focuses on data quality as a foundation for improving personalized customer engagement.
Watch the video >
The ROI of Data Quality
Make your data work harder with a fresh look at the value of data improvement. Gain insights from industry experts on how to move the needle on data quality and business income.
Data Assessment: Put your data to test
Understand data quality (completeness, uniqueness and frequency) and related risk to take action.
With the help of Pitney Bowes, Poste Maroc Group deployed an automated solution that streamlined address validation and reduced the rate of undeliverable mail by approximately 90 percent.
"This was an exemplary project, we have already achieved payback on the solution with our first customer.”
Said Bellaouchou,
Head of Addressing,
Poste Maroc Group
Luxury brands focus on quality of customer data, as globetrotting buyers expect to be known wherever they go.
“Pitney Bowes can manage the end-to-end process of CIM from data quality to data governance worldwide.”
Worldwide CRM Manager, Leading Luxury Goods Retailer.
Achieving new levels of precision and maximizing your data.
Align customer data across your enterprise systems. Learn how you can leverage more precise data to improve results from sales and marketing to customer service.
Gaining a picture-perfect customer view.
The company, armed with a precise and comprehensive view of its customers, has generated over $3 million in additional art sales in the short term; it is well on its way to achieving its goal of a $5 to $6 million increase in annual sales.
Applying address parsing in a hyper-connected world: a neural network approach.
Traditionally, delivery address verification involves manual effort, or is dependent on some hardcoded rule-based processing. Pitney Bowes has developed an approach using supervised machine learning.
Build a competitive advantage through data maturity and explore other stages.
Navigate through our proven end-to-end solutions.
