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Pitney Bowes

Pitney Bowes Data Quality

Composite Score

6.5 /10

CX Score

7.3 /10

6 Reviews Write a Review

What is Pitney Bowes Data Quality?

Ensure the quality of your customer data with validation, standardisation, and de-duplication solutions.

Company Details

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Pitney Bowes Data Quality Ratings

Real user data aggregated to summarize the product performance and customer experience.

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

80 Likeliness to Recommend

100 Plan to Renew

60 Satisfaction of Cost Relative to Value

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Emotional Footprint Overview

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

+97 Net Emotional Footprint

The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.

How much do users love Pitney Bowes Data Quality?

0% Negative

12% Neutral

88% Positive

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Feature Ratings

Average 63

Data Enrichment

Record Management

Geocoding

Data Source Connectivity

Data Cleansing

Record Deduplication

Data Profiling

Data Matching

Reporting Components

Dashboard

Data Monitoring and Administration

Vendor Capability Ratings

Average 63

Quality of Features

Product Strategy and Rate of Improvement

Vendor Support

Breadth of Features

Business Value Created

Ease of Customization

Availability and Quality of Training

Ease of IT Administration

Ease of Data Integration

Ease of Implementation

Usability and Intuitiveness

Pitney Bowes Data Quality Reviews

Adebomi A.

Role: Finance
Industry: Banking
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted May 2025

Powerful data quality tool.

Likeliness to Recommend

7 /10

What differentiates Pitney Bowes Data Quality from other similar products?

What sets this product apart is how well it handles complex location data. The geocoding and address validation tools are top-tier, especially if you're dealing with customer records across multiple regions. It also supports deep customization for data quality workflows, which isn’t common in many other tools. Once it’s up and running, it feels like a reliable workhorse that can handle messy, large-scale data.

What is your favorite aspect of this product?

The geocoding and data matching features stand out for me. They are precise and consistent—even when the input data is a bit rough. It really helps when you’re trying to clean up customer addresses or deduplicate similar entries. Once you learn your way around, it becomes a very powerful tool.

What do you dislike most about this product?

The user interface isn’t the most intuitive, especially for someone new to it. It feels a bit outdated and can overwhelm you at first. Also, implementation isn’t straightforward—you’ll likely need help from IT or someone who knows the tool well.

What recommendations would you give to someone considering this product?

If you’re going for Spectrum, just know that the learning curve is real. Don’t rush the setup. Take time to understand your data flow, and ideally have someone who’s used it before guide the integration. But if you're serious about data quality, especially at scale, it’s a solid investment. Just be ready to spend time configuring it properly.

Pros

Helps Innovate
Continually Improving Product
Performance Enhancing
Enables Productivity

Role: Sales Marketing
Industry: Transportation
Involvement: Initial Implementation

Validated Review

Anonymous Reviewer

Submitted May 2025

Relevant data drives autonomous systems

Likeliness to Recommend

10 /10

Pros

Trustworthy
Effective Service
Caring
Saves Time

Role: Finance
Industry: Consulting
Involvement: End User of Application

Validated Review

Anonymous Reviewer

Submitted Dec 2022

Better Handling OF Data With Pitney Bowes

Likeliness to Recommend

9 /10

Pros

Helps Innovate
Performance Enhancing
Trustworthy
Unique Features

How We Deliver

Events

Pitney Bowes Data Quality

What is Pitney Bowes Data Quality?

Company Details

Need Assistance?

Pitney Bowes Data Quality Ratings

80 Likeliness to Recommend

100 Plan to Renew

60 Satisfaction of Cost Relative to Value

Emotional Footprint Overview

+97 Net Emotional Footprint

How much do users love Pitney Bowes Data Quality?

Pros

Feature Ratings Average rating of all product features, some of which may not be shown below

Data Enrichment Includes the enhancement of the value of internally held data by appending related attributes from external sources .

Record Management Includes ability for Data stewards to monitoring data quality, taking action to determine the root cause of flagged issues and recommending remediation actions.

Geocoding Includes geo-referencing, address validation and verification, data mapping, and data append.

Data Source Connectivity Includes abiity to connect to a wide selection of data source types and systems.

Data Cleansing Includes data auditing, workflow specification, post-processing, and controlling. such as address standardization and the correction of known invalid values.

Record Deduplication Identity resolution is the process of linking various records and is the main engine for record deduplication, which can enable some aspects of data cleansing.

Data Profiling Includes statistical analysis of data values to evaluate the frequency, distribution and completeness of data.

Data Matching Includes fuzzy matching, data comparison, and data merging.

Reporting Components Lightweight controls and components that are easily embeddable and reusable. Integration with common apps such as Word, Excel, etc.

Dashboard Includes alerts and notifications, KPIs, visual analytics, and interactive features.

Data Monitoring and Administration Includes ability to continuously monitored data quality rules, as well as generate alerts to notify data stewards when they need to address an issue.

Vendor Capability Ratings Average rating of all vendor capabilities, some of which may not be shown below

Quality of Features Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Product Strategy and Rate of Improvement Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Vendor Support The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

Breadth of Features Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Business Value Created Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Ease of Customization Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.

Availability and Quality of Training Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

Ease of IT Administration This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Ease of Data Integration Use this data to determine whether the product will cause headaches or make data integration easy.

Ease of Implementation Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Usability and Intuitiveness End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Pitney Bowes Data Quality Reviews

Adebomi A.

Powerful data quality tool.

Likeliness to Recommend

Pros

Relevant data drives autonomous systems

Likeliness to Recommend

Pros

Better Handling OF Data With Pitney Bowes

Likeliness to Recommend

Pros

Title

Feature Ratings

Data Enrichment

Record Management

Geocoding

Data Source Connectivity

Data Cleansing

Record Deduplication

Data Profiling

Data Matching

Reporting Components

Dashboard

Data Monitoring and Administration

Vendor Capability Ratings

Quality of Features

Product Strategy and Rate of Improvement

Vendor Support

Breadth of Features

Business Value Created

Ease of Customization

Availability and Quality of Training

Ease of IT Administration

Ease of Data Integration

Ease of Implementation

Usability and Intuitiveness