Address scrubbing is basically the process of correcting and verifying addresses automatically in a list or database, also known as address verification. It’s very important to give your mailing list a good scrub to keep addresses up-to-date and ensure you can analyze and keep track of your customers and prospects effectively.
As you can imagine, address data of customers, leads, and so on is one of the most problematic fields in a data set. Rife with errors such as incomplete ZIP codes, abbreviated terms (STrt, ST. St), missing block or street names, address scrubbing is a necessary task in the data cleaning process.
Left unattended, poor address data will affect your analytics, making it difficult for you to get the insights you need from your mailing list. Hence, it is important to invest in address scrubbing to not only clean your address data, but also provide standardization and validation of addresses.
Here’s what you need to know about the impact of bad address data on data analytics, how an address scrubbing service and or software solution can help, and what steps you should to take in-house to make your address data effective for analytics.
Let’s dive in.
What is Bad Address Data?
Address data is gathered via multiple ways – the most common being via web forms, social media, and customer support. There are also multiple people at the end of the system inputting this data.
Web forms are usually filled by the intended audience, and it is quite common for this audience to enter an incorrect address. Most people only enter a complete address form only if they require a delivery or a mailing service. Even then, the address entered is often unstructured and may be missing a ZIP code or a bloc/street name. Eventually, this bad data costs companies time, effort, and money in fixing it. And this is just the tip of the iceberg.
Companies have to even suffer the brunt of poor analytics when they cannot get accurate address data. In this way, bad data isn’t just costly in terms of money and time, but also deeply affects strategic business planning and operations.
In a nutshell, any address data that has the following problems may be considered as bad data:
- Incomplete information with missing key elements such as ZIP codes, street, or block names etc.
- Inaccurate information such as writing the wrong street, apartment name or block number.
- Invalid addresses that do not match with the official postal database
- Non-standardized, unstructured data format that causes a problem during data migration
While you cannot prevent bad address data from happening, you can use an address scrubbing service to help you clean data.
What to Look for in an Address Scrubbing Service?
There are a dime a dozen address scrubbing services out there, but only the top-in-class solution will help you with the most critical function of address scrubbing – that of address validation.
The most common address scrubbing solutions profiles errors and lets you fix them. Some also let you dedupe duplicated address information.
Professional address validation solutions however do more than just scrubbing. When choosing a solution, make sure you take the following into account:
- Data Integration: Your address data is probably stored in multiple systems and under multiple formats. For example, your marketing team may be pulling in address data from web forms which have higher errors than say address data recorded by billing or customer service departments. An address scrubbing service must allow for the ability to integrate data from multiple formats. If you cannot integrate data and have to manually extract it to an acceptable file format, you’re already wasting time on an unnecessary activity.
- Data Profiling: Supposing you have millions of rows of data, how would you know what kind of errors your address data has? You will have to manually create filters or algorithms to sort through the different types of errors and still not be able to fix it all. A best-in-class address scrubbing solution allows you to profile your data for errors. You can find out the health of each row of your address data. You can also discover in detail issues like punctuation, negative spacing, poor formatting among many other problems. The point being – if you don’t know what’s affecting your data, how would you proceed to fixing it?
- Data Cleaning: Once you discover errors, time to fix it! You can fix address data based on a number of business rules that will usually be pre-built-in. You don’t have to manually define any rule.
- CASS Certified Address Validation: Make sure the solution you’re using offers a CASS Certified address validation service – meaning your address data will be verified and validated against an updated US (or any other official government) database to ensure that the address is valid. This is highly essential for when you want to use physical addresses to send mails or even to analyze your audience set for a certain region.
- Data De-duping: If you have data from disparate data sources, chances are this data may be duplicated. Common address scrubbing services do not offer data matching or deduping, so you might have to get another de-duping service separately.
Your choice of an address scrubbing tool will entirely depend on your budget, data size and the level of dirty data you have to deal with.
What Other Options Do You Have to Fix Bad Address Data?
Bad address data is a constant occurrence. As long as you generate data, you’ll be dealing with bad or dirty data. Therefore, it is necessary to implement a long-term solution to prevent this bad data from negatively affecting your busines.
Some companies prefer to hire data analysts to fix their bad data issues, while others hire expensive development teams to develop in-house cleaning algorithms. While both approaches seem like the most suitable option and some do work, they are often the most prone to failure and not very effective.
For example, a data analyst’s job is not to fix bad data – it’s to derive insights for analytics. But more than 80% of a data analyst’s job is spent in fixing bad data. Over time, the task becomes repetitive and data analysts feel demotivated as they realize their skill set is not being used for the right purpose.
Development teams on the other hand are not data experts. They can code solutions (monitored by a data analyst) but they don’t understand the actual information in the data as business users do.
Moreover, an in-house team can cost quite a lot of money each year, and even then, the accuracy is prone to suffer, and the bad data problem remains unchanged. Data quality is an urgent need and so while you spend months hunting for the right team, bringing them on board, then letting them find the perfect solution, you’re likely to lag behind your competitors who acted faster in managing the problem.
So, ultimately, address scrubbing is a much more efficient and cost-effective solution for cleaning address data. This automated software solution isn’t just about cleaning or verification activity like most online sources state. It involves a whole lot more. From data integration to data matching, from data cleaning to data validation, there is a whole process involved in fixing bad address data.
It’s imperative, therefore, for you to take bad address data as a serious problem that requires instant attention. In this era, delaying data issues will set you back considerably.