Data Cleansing

Do you have an ugly data problem?


Clean up fast with our 4-step data cleansing solution for your toughest data problems.



It takes time, money, and expertise to create effective marketing campaigns that drive sales and boost profits. In order to spend the least and get the best results, it’s crucial to deliver the perfect marketing message to the right customer at the right time. Achieve spot-on deliverability for every marketing message you send through the proven power of data cleansing.

  •  Is your customer data a big, fat mess?
  • Are your profiles riddled with missing information?
  • Are you too busy running your business to spend hours cleaning up dirty data?

If you answered YES to any of these questions, you’re not alone.

Most databases are filled with incomplete, duplicate, incorrect customer data. This dirty data makes marketing campaigns more expensive and less effective.

Why Data Cleansing?

Luckily, there is a simple, 4-step solution to clean up your data fast (no matter how busy you are or how big your data mess may be).

Data cleansing is a process that ensures the integrity of your data.

  • When your data is clean, you can trust that you’re marketing to customers at their correct physical and email addresses.
  • When you’re sure your data is accurate, you can justify the cost of maintaining customer records in your database.
  • When your data is organized and optimized, you know every marketing communication you send will be money well spent.


What is Data Cleansing?

Data cleansing is a way to find missing, incorrect, and duplicate information in your customer records. At Massa & Company, we process millions of records through our data cleansing software each year.

Using in-house data cleansing tools and external services like NCOA (National Change of Address) and ECOA (Email Change of Address), we’re able to find and eliminate duplicates and inaccuracies in your customer data.

When you have pristine data, you can create highly targeted marketing campaigns that make better use of every dollar spent.


Data Cleansing in 4 Simple Steps

Step One: Find the right address

The first step in the data cleansing process is determining the right mailing and email addresses for every customer in your database.

First, we verify each customer’s mailing address using the NCOA. We then cross-reference against multiple periodicals to ensure complete accuracy, as follows:

  • We utilize an Apartment Append to ensure deliverability to apartments and suites, as well as Seasonal Address identification, which enables us identify seasonal and vacation homes. This data point allows you to market to each customer at the right home during the right time of year, and cuts down on wasted mailings to empty beach houses!
  • We next use Deceased Identification to remove deceased customers from future communications, and Deliverability Point Validation (DPV®) to guarantee each address is 100% deliverable.
  • We then process your email addresses using ECOA. This includes finding new email addresses for bounced emails and correcting typos in email extensions. You can even find out if you’re emailing the same person at multiple addresses.

When you know where to communicate with your customers, you can spend more time focusing on what those customers want and how to market to them more effectively.


Step Two: Merge your databases

  • Do you have the same information contained in several different databases?
  • Are you unsure of which duplicate customer records are most current?
  • Are you stuck with different field formats that make merging seem impossible?

Step Two of our data cleansing process solves all of these problems and more. During this step, we will…

  • Merge multiple Excel spreadsheets into one
  • Merge multiple files into a single database of your choice
  • Combine, modify, or separate data fields and columns (such as separating first and last names into two different fields)

When data is uniform and housed in a single location, it’s easier to work with. You’ll save time searching for the right customer records and be freed to focus on campaign optimization instead.


Step Three: Get rid of duplicate data

Duplicate data means increased marketing costs.

  • For direct mail, you incur the hard costs of extra postage and extra printed materials.
  • For digital campaigns, you incur increased costs by paying to store bad data. Since many email programs charge according to how many email addresses you have, hanging onto duplicate emails can make a huge dent in your marketing budget.

During Step Three, we’ll identify and eradicate duplicate customer addresses to help you slash the cost of your marketing campaigns and database maintenance.


Step Four: Repair and replace missing data

Now that we have the correct addresses and uniform data housed in a single location, it’s time to repair, replace, and perfect every field in your database.

During Step Four, we will…

    • Create unique IDs for every customer record, thus preventing future duplicates
    • Research and fill in missing address data where possible
    • Research and fill in missing area codes
    • Add salutation
    • Add or standardize prefixes and suffixes
    • And more!

By the time Step Four is complete, every customer record in your database will be up-to-date with the most current information. That means no more duplicate records, no more missing apartment numbers, and no more guesswork when it’s time to launch your next marketing campaign!

Data cleansing is the fastest, most effective way to put your data to work.

As Massa& Company, we’ll do the heavy lifting so you can focus on crafting marketing campaigns that get results. With pitch-perfect data that’s been primed through the power of data cleansing, you’ll be able to spend less per customer and achieve even better results.

Are you ready to cleanse your data and slash your marketing spend? Get started right now. Fill out the form below to get your free data cleansing estimate in just 2-3 business days.

Bad Request

error was encountered while trying to use an ErrorDocument to handle the request.

Additionally, a 400 Bad Request 400 Bad Request