Melissa Data Quality Reviews

We use this tool for B2B and B2C customer de-duplication/matching, generating a golden version of our customers and for householding. 

We use Melissa Data Matchup for SSIS to de-duplicate our customer data on a daily basis so that we were able to reduce marketing costs and increase the quality of communication with customers.

It replaced a weekly primitive custom de-duplication (record level) matching process.

Its survivor-ship logic handles very complex column-level rules efficiently providing us with a first-time for a single version of truth for our customer data. It's inherent intelligence into name and address parsing provides a very accurate exact match with no false positives and no unexpected false negatives. We are continually impressed by its sophistication and ease of use. The tool does not requires a middle tier or specialized staff like every other tool on the market.

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. There's no separate server needed and no separate application to maintain.

This vendor offers a large variety of components from on-prem to cloud SaaS as well as hybrid of cloud and on-prem. This review is specific to the "MatchUp for SSIS" component.

For us, this tool had very high value due to the fact that we didn't have to become experts in some overly complicated DQ tool. And because it is fully integrated with our EDW ETL rather than having to originate and integrate an external application.

We are using it for daily 1) direct matching, 2) column-level survivor-ship and 3) mail house-holding. We started with B2C customers and later added B2B customers. The tool supports unique matching specific to organization names and individual names (as well as a variety of other specialized types of data values) and works well in both cases. For example it can pull out nicknames and match on those.

One of the business and operational benefits for us is feeding the end result to Adobe Campaign for marketing automation. But the primary output is simply creating and managing an analytical golden record for our customer data. This has provided a very effective, holistic, maintenance-free, and extremely cost effective solution for us.

The initial POC was up and running in just a few days with no training needed. The plug-in into our ETL tool was seamless and fully integrated into our existing processes. Most of our effort was due to the need to identify customer survivor-ship requirements and validation. Any needed adjustment changes could be done very quickly allowing us to focus on business requirements instead of implementing technology.

- 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.

We have been using this product for over 7 years.  

No as long as you don't try to match on null last names or lots of duplicate (exact match) records or try to run it in the default 64 bit mode of SSIS (issue here is only with new versions).

We can run 9 million customer record exact matches in 10 minutes using 5 partitions/parallel dataflows. Survivorship takes another 50 minutes. I'm sure you could run faster with dedicated hardware and running more parallel dataflows. The tool starts to exponentially slow down once you pass about 2 million customers in a single dataflow so its best to keep it at or under that number although mileage will vary depending on the complexity of your matching.  Its unfortunate that the vendor hasn't built in parallelism which would both eliminate the need to do this yourself.  They should be able to auto-scale it based on # of CPU's your running.

Even with that limitation this tool is magnitudes faster than the last matching tool I used and it wasn't a simple plug-in to an ETL tool. I recently heard of a competing tool that takes longer to match just a few thousand customers than this tool takes to run millions of them.

Note:

We probably run higher volumes than many organizations. For B2B and daily matching you could probably process a delta in a matter of a few minutes with this tool.  

Note:  I suspect an essential ingredient when considering scalability is whether you're calling a web service for matching or just on-prem. Their SSIS component is only on-prem but they offer a web service as well which we have not tested.

Combining survivorship and matching in the same data flow slows performance. We got much better performance by running in two separate dataflows - the first for just matching and then another for just survivorship (re-using the previous grouping numbers in the first match) to make it perform to our requirements.

Customer Service:

Fairly typical vendor support. They are immediately attentive to problems and provide email notifications of software versions. The main technical contact we work with has been there for the last decade which is very refreshing!

Technical Support:

They regularly release new versions of the product with bug fixes and enhancements although just the matchup tool itself has changed very little in the past 5 years. 

However unless you can interact directly with the development team problems may not get resolved in a timely manner. I have usually been left coming up with my own solution in the time I was waiting for their support to provide answers from their support team.

I have used Datamentors and SAS Dataflux in the past with good success although I would easily take this product over those products for just matching/survivorship purposes. We had tested Oracle's cloud-based Fusion product which wasn't actually a functioning product at the time. The MelissaData tool is light-years ahead of Datamentors, far easier to use and the price can't be compared. The SAS tool was very expensive.  All other matching tools require separate middle tier application verses this product which is just a plug-in to SSIS.

Initial setup on the first install was VERY easy. Propagating the matching rules to the next server was easy IF you know which file to copy which isn't well documented. The tool is extremely easy to use when you know just a few little things which aren't documented. Their development staff were very helpful in providing simple tips on how to set it up.

This was in-house implementation. The vendor was very responsive in answering questions.

I have no numbers for ROI but it's avoided having to spend 6 figures for similar functionality in another tool.  Plus since it's fully integrated with SSIS there is no need for separate server - more money saved. 

This vendor has no equal in pricing for equivalent functionality. First no one else offers this level of integration with SSIS. Second other vendors with equal functionality all cost many times the cost of this tool. Third it doesn't require a separate server or large learning curve of new software. Fourth, this is one of the "go to" vendors for matching purposes as some master data and data quality tools are actually calling MelissaData Matchup object in the backend then charging you a lot for their pretty GUI to do this for you.

I evaluated Microsoft's DQS which could not scale over 100,000 customer records. DQS actually supported calling MelissaData Matchup in the old Microsoft Marketplace (no longer available) to use it's more sophisticated matching but it was a moot point if DQS can't handle the volume.  

This tool is a dream compared to my previous experience with batch matching/de-duplication tools. And the pricing is incredible given its functionality and simplicity. High value and very lost cost. If you're an SSIS shop (they support other ETL tools also however) and you need to de-duplicate, household and/or do column-level survivorship then this tool can't be beat.

I highly advise running parallel threads by splitting your dataflow into multiple paths.  This allow parallel matching and increaes throuput significantly.

We used the trial and we used the custom solution Append for a month or so. On Excel we still use the custom solution today. We use it to find updated contact information for our customers.

We mainly communicate with our customers via email, so we primarily use it to find a phone number so we can contact them more efficiently. This allows us to talk to them and resolve their issues much more quickly.

The Append feature. The majority of the time we have a customer’s name and address and we need to find their phone number or email.

We would appreciate it if there was a larger database so that we could find information more often. For example, we can search for 10 people and only find the information for three of them, if we are lucky. Increasing this success rate would be beneficial and, at the same time, would be a great way to get more clients interested in the solution.

The custom software solution we still use in-house makes Excel a lot slower than usual.

No scalability issues at all.

I have never had to contact tech support. My sales rep helped me out with everything I needed.

We still use another solution due to a higher success rate with the amount of information provided. The reason we also use Melissa Data is because it provides information for our customers outside of the US as well, and it makes searching for multiple customers easier through the Append feature.

The initial setup was somewhat complex at first, but it was straightforward enough to understand, once you get the hang of it.

Buy a lot more credits than you think you’re going to need.

The only other product we are currently using is Whitepages Premium. It provides the information necessary, except for an email address sometimes. We also looked at Spokeo and other append services. Melissa caught my attention because we had previously worked with their address verifier and I knew it was a good solution for our needs.

I would rate this system an eight out of 10. The accuracy of correct information is very high when it's available. However, there was a 70% chance where the system would find the person we were looking for but there was no contact information.

Still, I would advise getting the service without hesitation. It can come in handy and, even if you don’t use it on a daily basis, it’s a great tool to have when you need additional contact information for any purpose.

Data quality: Using it to validate addresses and email addresses for valid deliverability.

Allows us to delete and correct incorrect data to make the searching of our applicant tracking system more consistent and relevant.

Ability to keep our data set clean and usable for our community searches.

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

No issues.

No issues.

So far, so good. Although, we have not needed to use this very often.

No previous solution was used. We implemented Melissa Data when we moved forward with our data quality tool.

We used a third-party to integrate into our DQM.

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.

No.

Have a good understanding of your data. Therefore, you can look at the recommended changes to make sure they make sense.

We provide a service for courthouses to summon candidates for jury duty. This requires the list of candidates’ addresses to be checked via the USPS NCOA list. We use SmartMover for this purpose.

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.

It provides address standardization and NCOA, and deliverable addresses. This saves our clients time, and money in postage fees, by providing updated and undeliverable addresses.

The billing structure does not seem very accurate. We’ve had issues with miscounted batch records processed. We also ran into some data quality issues, but they have been rectified and we haven’t noticed any issues since.

We encounter failed batch processes once in a while, but their team is quick to rectify issues.

Larger batches sometimes have failed batches.

Tech support is 10 out of 10.

We had issues with data quality and a very slow return time with our previous vendor.

It was very straightforward. The documentation is clear and the sales rep has been good with communication.

Pricing is based on tiers, with each tier capped at a specified number of records processed. Once you go over the cap at one tier, you are automatically bumped to the next tier. However, they seem to count failed batch processes so it’s good to keep track of the number of records sent. They’ll fix the count when notified, but their system fails to detect actual successful processes versus failed processes.

We looked at Service Objects and a few others. Some of these vendors had poor documentation, pricing was not competitive, or the product did not provide the customization we needed.

Thoroughly test the product. They have many different products that provide the same or similar results, but the execution is different. For example, the same goal of processing a list through NCOA can be accomplished via FTP, JSON, or SSIS. It depends on the implementation and which product is best suited for what you’re trying to achieve.

Capture email addresses and phone numbers for marketing.

Gives us the ability to offer an additional resource that other companies do not.

Phone numbers, so we can help people market efficiently.

Provide more phone numbers, even cell numbers (scrubbed numbers).

No issues.

Not applicable.

Technical support is excellent.

No.

It has a straightforward, easy setup.

It is affordable.

Great tool; certainly helpful if you need an affordable option.

We use Listware for Microsoft Excel for NCOA.

NCOA processing is now quick and easy. No waiting for the list to come back, no calling, and no worrying if there are enough credits available.

Being able to send out client mailings with the most accurate addresses possible. 

It would be helpful if a list of the codes and explanations could be included.

No stability issues.

No scalability issues.

Excellent.

No previous solution.

Very simple; step by step, online.

Pricing is very reasonable, no licensing required.

Satori. You have to call to purchase credits, unless you want to spend a couple thousand dollars a year to purchase unlimited NCOA. When I called I got voicemail. Wanted something quicker.

Try it. It couldn’t be much easier.

Address parsing for property tax roll records and adding Zip+4 to its latitude and longitude coordinates.

When we first started using Melissa Data products, we needed it for cleaning up parcel addresses and adding Zip+4 to its latitude and longitude coordinates. At the time, we were actually using the products for verifying the addresses and cleaning up cities and zip codes so our clients could use the information to send out mailings. Over the last few years, we have changed our direction a little bit. We no longer use the product for verifying or changing any of the address information we get from the state or property appraiser offices. We only use it now for parsing the addresses into street name, suffix, direction, unit, etc. to make our data easier for our clients to search on these separate fields. If the street name that comes from the property appraiser’s office is misspelled, we no longer use Melissa Data to clean it up. We just parse. There are reasons for why we do this that would take longer to explain, but wanted to give you an idea of what we are doing. We do append the lat/long info for any additions or changes that we get when we get the new tax roll updates each year.

Since we have changed directions and we are no longer using Melissa Data to clean up our address information, there are free tools that we can use to do the same thing. We can also write our own parsing routines ourselves, if necessary. The reason we have not looked at other tools yet is because this takes time for our team to change the processes that we already have in place. However, the long-term benefit is we would save this money that we are spending every year on Melissa Data products. We would just have an initial cost of rewriting everything the first year. Also, we can get most of the lat/long information we need from the county parcel maps that we already get for free. We also have another solution to handle the properties that are not necessarily in the maps data (because of timing or other issues). We are looking into this. 

Just giving honest feedback. We have no gripes with the products. We just have to look at ways to keep our own costs down.

We like having the ability to write our own utilities/software to process our records and store the final output the way we want. We use the objects inside of programs that we wrote in VB/VB.NET. This tool works better for us than using a batch processing system that we do not have enough control over as each record is being processed. 

I cannot think of anything to improve. The products do way more than we take advantage of at this time.

No issues.

No issues.

We have never used technical support.

We have not used another solution.

Extremely easy to install and setup. Initially, we had to figure out how to use all of the properties for each object and what the return codes meant, but this really was not that hard.

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. 

We do not give advice as to pricing and licensing.

I believe we evaluated other products offered by Melissa Data at the time (for example, “Mailers”). I do not know that there were other vendors offering what we needed at the time. Other vendors had options for sending batch data files, but no options for us to be able to write our own code.

I believe the Melissa Data products are very good. I tend to direct clients and colleagues to check out Melissa Data if they are doing mailings because those products are very good and simple to use. We usually suggest to our own customers that they check it out if they want to do mailings from the records we provide. There seem to be a lot of capabilities built into the Melissa Data products that we currently buy, but we are not taking advantage of because we just do not need those capabilities for what we are doing.

A significant part of our business revolves around the supply of domain names and, as such, we operate an accredited domain name registrar business. One of the requirements of the accreditation is that we validate customer data in relation to their domain name registration. The primary purpose of this is to deter misuse of domain names for fraudulent, phishing, or copyright issues. Being a policy requirement, our initial intention was to simply remain compliant with our accreditation requirements in the most cost effective manner. Melissa Data was well and truly on top of the list when it came to scoping our options for this objective.

We have, however benefited in additional ways from the service, in that our customer database is now significantly more accurate and reliable. This is particularly important when it comes to both cost savings and cost generating measures. There have been tangible benefits in combating fraudulent transactions. The information from Melissa Data is fed straight into our fraud system. This creates efficiency but also removes the need for manual address checks. Similarly, through more accurate data, our marketing department has been able to increase delivery and conversion rates through email direct marketing initiatives.

Automated data verification.

None of note, it suits our needs. It could always be cheaper.

No stability issues.

No scalability issues.

Limited use of tech support has been necessary, but all interactions have been pleasant. Nine out of 10.

No previous solution.

Straightforward. A simple API fit for purpose.

Melissa Data is cost effective and efficient. It was the best we could find when we first scoped the project.

SAS, Experian.

Talk to the Melissa Data team, they are helpful, friendly and efficient.

We use Melissa Data Listware for customer address verification.

I have only just started to use it at my current company so no improvements yet. In my previous role, we used Listware to reduce returned mail and reduce mailing costs.

Simplicity, ease of use, combined with overall accuracy of data.

The world is moving/has moved to the cloud. I get that. But it would be nice to easily integrate the solution with our own internal systems/processes in a way that keeps IT happy. Right now I live at a company with (exceedingly) tight IT policies, so integration of a cloud solution just doesn’t work. The on-premise version of Listware is too expensive relative to the cloud version.

No stability issues yet.

No scalability issues.

Average to below average. 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."

I have investigated but not used other solutions.

Easy enough. 

Cloud is very cheap. On-premise is expensive.

I can’t recall all the other solutions in detail; Trillium was one.

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.

We use Melissa Data Web Service during our freight bill entry process. We check Melissa Data to determine if a ship-to address is a residential address. If so, we add a residential delivery charge to the invoice.

Previously, we had to rely on the driver of the delivery to mark a shipment as residential. If they forgot or were not sure, the delivery would not be marked and we would potentially lose revenue from the residential delivery.

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

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.

No stability issues.

No scalability issues.

Tech support is fine.

We did not previously use a different product.

Straightforward. Melissa provided instructions on how to use the APIs, login information; it was very easy to set up.

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

Follow normal IT processes to design what you need; build, test, and implement.