BCC Data Quality vs Melissa Data Quality comparison

BCC Software and Melissa are both solutions in the Data Quality category. BCC Software is ranked #26, while Melissa is ranked #7. BCC Software holds a 1.6% mindshare in DQ, compared to Melissa’s 4.6% mindshare. Additionally, 100% of BCC Software users are willing to recommend the solution, compared to 95% of Melissa users who would recommend it.

BCC Data Quality

Read 1 BCC Data Quality review

390 Views
269 Comparison Views

100% willing to recommend

Melissa Data Quality

Read 40 Melissa Data Quality reviews

1,518 Views
1,047 Comparison Views

95% willing to recommend

BCC Data Quality

Melissa Data Quality

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between BCC Data Quality and Melissa Data Quality based on real PeerSpot user reviews.

Find out what your peers are saying about Informatica, Qlik, SAP and others in Data Quality.

To learn more, read our detailed Data Quality Report (Updated: February 2026).

Buyer's Guide

Data Quality

February 2026

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

BCC Data Quality

Ranking in Data Quality

26th

Ranking in Data Scrubbing Software

12th

Average Rating

10.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Melissa Data Quality

Ranking in Data Quality

7th

Ranking in Data Scrubbing Software

5th

Average Rating

8.4

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of March 2026, in the Data Quality category, the mindshare of BCC Data Quality is 1.6%, up from 0.3% compared to the previous year. The mindshare of Melissa Data Quality is 4.6%, up from 2.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality Mindshare Distribution
Product	Mindshare (%)
Melissa Data Quality	4.6%
BCC Data Quality	1.6%
Other	93.8%

Data Quality

Featured Reviews

it_user831795

President

Postal sorting to the best and lowest postal rates

It is used for clients' mail list hygiene to standardize, update change of addresses, dedupe, and postal sort for mailings with postal discounted rates My company provides these services for clients in the mailing industry. This software is a must have for my company offerings. Address…

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GaryM

Data Architect at World Vision

SSIS MatchUp Component is Amazing

- Scalability is a limitation as it is single threaded. You can bypass this limitation by partitioning your data (say by alphabetic ranges) into multiple dataflows but even within a single dataflow the tool starts to really bog down if you are doing survivorship on a lot of columns. It's just very old technology written that's starting to show its age since it's been fundamentally the same for many years. To stay relavent they will need to replace it with either ADF or SSIS-IR compliant version. - Licensing could be greatly simplified. As soon as a license expires (which is specific to each server) the product stops functioning without prior notice and requires a new license by contacting the vendor. And updating the license is overly complicated. - The tool needs to provide resizable forms/windows like all other SSIS windows. Vendor claims its an SSIS limitation but that isn't true since pretty much all SSIS components are resizable except theirs! This is just an annoyance but needless impact on productivity when developing new data flows. - The tool needs to provide for incremental matching using the MatchUp for SSIS tool (they provide this for other solutions such as standalone tool and MatchUp web service). We had to code our own incremental logic to work around this. - Tool needs ability to sort mapped columns in the GUI when using advanced survivorship (only allowed when not using column-level survivorship). - It should provide an option for a procedural language (such as C# or VB) for survivor-ship expressions rather than relying on SSIS expression language. - It should provide a more sophisticated ability to concatenate groups of data fields into common blocks of data for advanced survivor-ship prioritization (we do most of this in SQL prior to feeding the data to the tool). - It should provide the ability to only do survivor-ship with no matching (matching is currently required when running data through the tool). - Tool should provide a component similar to BDD to enable the ability to split into multiple thread matches based on data partitions for matching and survivor-ship rather than requiring custom coding a parallel capable solution. We broke down customer data by first letter of last name into ranges of last names so we could run parallel data flows. - Documentation needs to be provided that is specific to MatchUp for SSIS. Most of their wiki pages were written for the web service API MatchUp Object rather than the SSIS component. - They need to update their wiki site documentation as much of it is not kept current. Its also very very basic offering very little in terms of guidelines. For example, the tool is single-threaded so getting great performance requires running multiple parallel data flows or BDD in a data flow which you can figure out on your own but many SSIS practitioners aren't familiar with those techniques. - The tool can hang or crash on rare occasions for unknown reason. Restarting the package resolves the problem. I suspect they have something to do with running on VM (vendor doesn't recommend running on VM) but have no evidence to support it. When it crashes it creates dump file with just vague message saying the executable stopped running.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"It fulfills the USPS requirements for mailings."

"This software is a must have for my company offerings."

"Postal sorting to the best and lowest postal rates."

"We use a Melissa API to access the data, so it easy to use, accurate, and fast."

"Through more accurate data, our marketing department has been able to increase delivery and conversion rates through email direct marketing initiatives."

"Melissa Data is often best for the price, quality, thoroughness, and speed."

"This serves our single need and we may utilize Melissa Data for other lookups, such as validate address lookup, in the future."

"We are able to send out client mailings with the most accurate addresses possible."

"It saves a huge amount of time. Before using this service, we used a vendor that manually ran our lists through this NCOA list, which might have taken one to three business days to return the file. This was a huge bottleneck in our process, and the data returned was not always accurate. After switching to Melissa Data’s SmartMover, the process has been reduced to between ten minutes and three hours, depending on the amount of records sent."

"Personator application was able to append emails, new address if moved, phone number, geocode, and also standardizes existing customer information."

"It has a straightforward, easy setup."

More Melissa Data Quality pros

Cons

"I use another program for deduping files. I am not comfortable with the way BCC deduping runs when deduping by full name and address."

"Speed of delivery/ease of use. They advertise a 24-hour, next business day turn time on data annotation, but I’ve found it is usually closer to 72 hours."

"Needs to validate more addresses accurately."

"We are very pleased with the pricing but they need to have some good licence tracking mechanism."

"Overall there is a room for improvement in Customer Address Appends and Email Appends."

"Needs to validate more addresses accurately."

"Needs more and better search tools. Also, state and local tax data would be nice."

"Tech support at Melissa Data was very quick to wash their hands of an issue and say it's IT policies on my side that are causing the issue. There was no offer to try and find a work-around. Just an overwhelming attitude of "it’s not our problem.""

"Need to POC point of entry validation."

More Melissa Data Quality cons

Pricing and Cost Advice

Information not available

"Pricing is very reasonable."

"Trial subscriptions (via cloud) are very cheap and easy to use. It’s a great way to test Listware to see if you want to go deeper with integration."

"It is affordable."

"Be sure to determine how the data is priced (record-based versus credit-based or some hybrid of data and services)."

"Understand how may transactions you will be processing so that you can get the right tier pricing."

"They were willing to work with our preferred vendors, though it involved extra steps to get the license."

"Generally, the cost is ROI positive, depending on your shipping volume."

"The only complaint that I have towards it is they sell licenses based on a range of usage, and I feel those ranges are too large."

More Melissa Data Quality pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

Insurance Company

13%

Computer Software Company

Manufacturing Company

Educational Organization

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	3
Large Enterprise	14

Comparisons

Ataccama ONE Platform vs BCC Data Quality

Compared 26% of the time

SQL Power Data Quality vs BCC Data Quality

Compared 22% of the time

Microsoft Data Quality Services vs BCC Data Quality

Compared 15% of the time

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Qlik Talend Cloud vs Melissa Data Quality

Compared 20% of the time

Experian Data Quality vs Melissa Data Quality

Compared 16% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Melissa Data Quality

Compared 7% of the time

Coheris Spad Data Quality vs Melissa Data Quality

Compared 5% of the time

Anchor Software Data Quality vs Melissa Data Quality

Compared 4% of the time

More Melissa Data Quality Competitors

Product Reports

Buyer's Guide

Data Quality

February 2026

Download BCC Data Quality product report

Buyer's Guide

Melissa Data Quality

March 2026

Download Melissa Data Quality product report

Also Known As

Bell and Howell Data Quality

No data available

Overview

BCC Data Quality includes the following solutions:

LENS ensures submission and retrieval with our secure FTP-based process, receives an email when your updated lists are ready for pick-up, its processing supports PGP encryption.and process file types regardless of postal software used including delimited (comma or tab), fixed-length, Paradox, and dBase.
Datavolve confirms address data against the most current USPS reference data, evaluates address data where it enters your system, so data errors are fixed before they cause problems throughout an organization, records are standardized and enhanced with essential ZIP + 4 codes, postal carrier routes, delivery point, and other valuable information and deployable by over multiple platforms, wide operational configurations, and all data entry points.
ZIPFOURce Web Services Single and batch encoding options are both available, and the service adjusts names entered for proper casing: all caps or no caps, Uses USPS DPV technology to reveal whether an address listed in the ZIP + 4 database is actually recognized by the USPS as a deliverable destination and updates rural-style addresses to city-style formats, or renames/renumbers city-style addresses that may have been changed by local governments.
GoData is a web-based tool for data processing, performing data hygiene and list enhancement.

BCC Software

Data Quality Components for SSIS

This suite of data transformations for Microsoft SQL Server Integration Services (SSIS) delivers the full spectrum of data quality including data profiling, data verification, data enrichment and data matching. With an intuitive interface and drag/drop capabilities, this powerful toolkit makes it easy to unify data into a single version of the truth for Master Data Management (MDM) success.

Melissa

Sample Customers

Perinton Publishing

Boeing Co., FedEx, Ford Motor Co, Hewlett Packard, Meade-Johnson, Microsoft, Panasonic, Proctor & Gamble, SAAB Cars USA, Sony, Walt Disney, Weight Watchers, and Intel.

Find out what your peers are saying about Informatica, Qlik, SAP and others in Data Quality. Updated: February 2026.

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