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BCC Data Quality vs Melissa Data Quality comparison

 

Comparison Buyer's Guide

Executive Summary

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
30th
Ranking in Data Scrubbing Software
12th
Average Rating
10.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
Melissa Data Quality
Ranking in Data Quality
11th
Ranking in Data Scrubbing Software
4th
Average Rating
8.4
Reviews Sentiment
7.6
Number of Reviews
40
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2026, in the Data Quality category, the mindshare of BCC Data Quality is 1.5%, up from 0.4% compared to the previous year. The mindshare of Melissa Data Quality is 4.0%, up from 3.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Quality Mindshare Distribution
ProductMindshare (%)
Melissa Data Quality4.0%
BCC Data Quality1.5%
Other94.5%
Data Quality
 

Featured Reviews

it_user831795 - PeerSpot reviewer
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…
GM
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.

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​."
"Postal sorting to the best and lowest postal rates."
"This software is a must have for my company offerings."
"Be confident that the scalability and load are not going to be an issue with the services. ​"
"Contact Verify is very simple to use and performs very fast."
"Address verification ensures our customers get their packages, and we aren’t charged for incomplete address information."
"Melissa Data is cost effective and efficient."
"Melissa offer a high quality product with great service."
"The high value in this tool is its relatively low cost, ease of use, tight integration with SSIS, superior performance (compared to competitors), and attribute-level advanced survivor-ship logic."
"Helps our organization provide accurate address information to our customers for direct mailing (household) and other campaigns they want to do."
"Standardizing allows me to more effectively check for duplicate/existing records. Verifying increases the value of the data."
 

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.​"
"Update feature"
"It could always be cheaper."
"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. This is still excellent, just make sure you add in the appropriate fluff to your delivery timelines."
"Pricing model."
"Needs more/better search tools are needed. Also, state and local tax data would be nice."
"Needs better email append coverage (but every vendor struggles with this)."
"The use case I'm familiar with is for a merchant who was contrasting this technology with data from Dun and Bradstreet: so my recommendation is that Melissa Data purchase Dun and Bradstreet to combine their data breadth."
"Address validation and parsing in a few countries have room for improvement."
 

Pricing and Cost Advice

Information not available
"Pricing is very reasonable."
"Cloud version is very cheap. On-premise version is expensive."
"This vendor has no equal in pricing for equivalent functionality."
"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."
"​You should have a good idea of the size of your data and the amount of cleansing you will be doing, so you will purchase the appropriate size bundle.​"
"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."
"Buy a lot more credits than you think you’re going to need."
"Pricing is very reasonable, no licensing required."
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Top Industries

By visitors reading reviews
No data available
Construction Company
20%
Outsourcing Company
10%
Healthcare Company
6%
Comms Service Provider
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise3
Large Enterprise14
 

Also Known As

Bell and Howell Data Quality
No data available
 

Overview

 

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, Ataccama and others in Data Quality. Updated: July 2026.
909,563 professionals have used our research since 2012.