BCC Data Quality vs Melissa Data Quality comparison

BCC Software and Melissa are both solutions in the Data Quality category. BCC Software is ranked #24, while Melissa is ranked #6 with an average rating of 9.0. BCC Software holds a 1.4% mindshare in DQ, compared to Melissa’s 2.8% 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

279 Views
176 Comparison Views

100% willing to recommend

Melissa Data Quality

Read 40 Melissa Data Quality reviews

889 Views
507 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, SAP, Qlik and others in Data Quality.

To learn more, read our detailed Data Quality Report (Updated: December 2025).

Buyer's Guide

Data Quality

December 2025

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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

24th

Ranking in Data Scrubbing Software

14th

Average Rating

10.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Melissa Data Quality

Ranking in Data Quality

6th

Ranking in Data Scrubbing Software

4th

Average Rating

8.4

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of December 2025, in the Data Quality category, the mindshare of BCC Data Quality is 1.4%, up from 0.4% compared to the previous year. The mindshare of Melissa Data Quality is 2.8%, up from 2.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality Market Share Distribution
Product	Market Share (%)
Melissa Data Quality	2.8%
BCC Data Quality	1.4%
Other	95.8%

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

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

"It fulfills the USPS requirements for mailings."

"SSIS integration."

"We are able to more accurately identify valid, and better formatted, data which improves the data we store in our database."

"By validating and parsing the addresses our customers submit to us, we have reduced the number of addressing errors encountered during our processing."

"I was able to dedupe millions of records in the past, and append the most recent email."

"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."

"By using Melissa Data, we are able to scrub and verify, then better validate the end customer's address to ensure a more consistent delivery of products."

"We only use the one feature for the NAICS code. This allows our product users to know what industry a business is in."

"Provides simplicity, ease of use, combined with overall accuracy of data."

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."

"Pricing model."

"There are some hitches in setup, especially with the new encoding, but otherwise it’s relatively simple."

"An area for improvement is where an end customer's address is not found in the Melissa Data database, even though it is a valid address."

"Many issues, sometimes I have to completely log out and start over."

"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.""

"We have noticed that some of the emails and addresses return with confusing or incorrect codes, but for the most part, it is accurate."

"Needs to provide more phone numbers, even cell numbers (scrubbed numbers)."

"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."

More Melissa Data Quality cons

Pricing and Cost Advice

Information not available

"The price for address validation is similar in all software. However, the price for geocoding decides the actual pricing. If you get their most accurate geocoding (called GeoPoints), then it will add about $10k+ per million requests."

"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."

"I think it's worth the value for me to run it."

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

"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."

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

"Pricing is very reasonable, no licensing required."

"It's affordable."

More Melissa Data Quality pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

Insurance Company

14%

Manufacturing Company

12%

Computer Software Company

Healthcare Company

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

SQL Power Data Quality vs BCC Data Quality

Compared 100% of the time

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Qlik Talend Cloud vs Melissa Data Quality

Compared 22% of the time

Experian Data Quality vs Melissa Data Quality

Compared 16% of the time

Coheris Spad Data Quality vs Melissa Data Quality

Compared 12% of the time

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

Compared 11% of the time

Anchor Software Data Quality vs Melissa Data Quality

Compared 10% of the time

More Melissa Data Quality Competitors

Product Reports

Buyer's Guide

Data Quality

December 2025

Download BCC Data Quality product report

Buyer's Guide

Melissa Data Quality

December 2025

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.

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