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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
26th
Ranking in Data Scrubbing Software
13th
Average Rating
10.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
Melissa Data Quality
Ranking in Data Quality
5th
Ranking in Data Scrubbing Software
5th
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 February 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 4.4%, up from 2.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Quality Market Share Distribution
ProductMarket Share (%)
Melissa Data Quality4.4%
BCC Data Quality1.6%
Other94.0%
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

"Postal sorting to the best and lowest postal rates."
"It fulfills the USPS requirements for mailings​."
"Be confident that the scalability and load are not going to be an issue with the services. ​"
"We ran a standard name, address, and zip code, internal dedupe between the different files we had purchased, and we were able to quickly notify our vendor that they had tens of thousands of duplications that they were not even aware of."
"Our customer database is now significantly more accurate and reliable."
"Address verification ensures our customers get their packages, and we aren’t charged for incomplete address information."
"​Initial setup was fairly straightforward. The documentation was very good in terms of how to integrate and consume the service(s) that we use. It did not take an abundance of time to set up things on our side to use the service."
"We use their GeoPoints to get the most precise, rooftop level geocoding."
"SSIS integration."
"Provides simplicity, ease of use, combined with overall accuracy of 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.​"
"The SSIS component setup seems a little klunky."
"MatchUp seems to be single threaded, and limits the amount of data that can be processed automatically."
"There are some hitches in setup, especially with the new encoding, but otherwise it’s relatively simple."
"There are some companies out there using Google or other sources to check / confirm if addresses are residential. If Melissa is not doing this, that could be an improvement."
"Pricing model."
"Needs to provide more phone numbers, even cell numbers (scrubbed numbers)."
"To continually update the database with NAICS codes on businesses."
"It will mix up family members at times, so we will change addresses at times that shouldn’t be changed."
 

Pricing and Cost Advice

Information not available
"Pricing is very reasonable, no licensing required."
"Understand how may transactions you will be processing so that you can get the right tier pricing."
"NCOA address verification was a requirement from USPS to send out the mailers. This was the only option that charged per address which was extremely helpful since we are a small non-profit school."
"It's affordable."
"​We are concerned that our own pricing is going up every year for Melissa Data products, but we highly recommend the services for people who are routinely sending out mailings."
"Depends on situation. We prefer to have data onsite, but some might prefer web access."
"Pricing is very reasonable."
"They were willing to work with our preferred vendors, though it involved extra steps to get the license."
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Top Industries

By visitors reading reviews
No data available
Insurance Company
15%
Educational Organization
6%
Manufacturing Company
6%
Computer Software Company
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, SAP and others in Data Quality. Updated: January 2026.
881,733 professionals have used our research since 2012.