Database cleansing – what is it and how does it work?

What is database cleansing and how does it work?

A recent report from Gartner estimates a 70.3% data decay for B2B data per year, and around 3% per month.

And B2B decay is more pronounced because of the current economic environment, with increased workplace flexibility, job instability, and changing customer demands all amount to more rapid data decay.

In the process of data management, data cleansing is an important step.

Customer data accumulates over time and, eventually, information goes out of date, reducing data quality.

A data cleanse involves using data analysis tools and techniques to identify out of date data.

During the data cleaning process, marketing data is scored to find:

  • incorrect data,
  • duplicate records,
  • irrelevant data, and
  • incomplete data.

This data is then updated or removed from the dataset.

The goal of the data cleansing process is to update, correct, and consolidate your data records.

We understand the value of accurate data.

As well as supplying marketing databases, More Than Words Marketing provides data cleansing services.

We take a number of important steps to keep our client’s data clean, and you can do the same. Here’s how.

What are the steps you take to clean data?

You can follow these basic steps for data cleaning – no matter what type of data your company has.

Step 1: Get rid of duplicates

Duplicate data is any entry that shares data with another entry in your marketing database. In most cases, duplicate data simply appears as a replica of another record.

Partial duplicates, however, are the most common (and most harmful) type of duplicate data. These records may have the same name, phone number, email, or address as another, but contain other data that doesn’t match.

Step 2: Correct structural problems

When you measure or transfer data and discover incorrect capitalisation, typos etc, you have a structural error. This leads to inconsistencies in categories and classes that can make it difficult to keep certain groups together.

For example, there may be a conflict between “N/A” and “Not Applicable”, but they both refer to the same category.

Step 3: Identify outliers

Any data point that is visibly out of line with the rest is considered an outlier.

It is important to investigate before taking action with outliers.

A common B2B marketing outlier is the ‘always opener’. These prospects might always open your emails, but never click through or engage in any other way. This could be because they just open every email they get – or they could even be an employee.

Without looking into the high open rate, you might add them to your ‘valued customers’ group when they’ve never actually bought anything.

Step 4: Correct or remove records with missing data

Data with missing values can either be filled in or discarded. Your choice will depend on what the missing value is.

For example, if you don’t have their email address, you’ll be unable to get in touch with them. If you have their email but don’t have their name, you can either use their email to find it or contact them directly.

Missing data can be handled in a couple of ways. Both are acceptable, but neither is optimal.

  1. If you decide to remove records with missing values, keep in mind that removing them will result in the loss of all the other associated information.
  2. It is possible to input missing values based on other observations. However, this may result in loss of database integrity since you are making decisions on the basis of assumptions.

Working with a data cleaning agency to add missing information to your databases is always the best choice.

Step 5: Standardise data input

Data that is dirty is often caused by incorrect input. If your process allows bad leads to flow in, you can’t maintain a healthy database.

To reduce human error, you should have a Standard Operating Procedure (SOP) for acquiring data.

Automation at the point of data collection is good standard practice.

Maintain a regular data cleansing schedule

It isn’t enough to clean data once.

Although a Standard Operating Procedure will help, inaccurate data cannot completely be prevented. Data might slip through the cracks, whether it was intentional or an honest mistake.

Ensure your data is cleansed regularly to ensure the maximum effectiveness of your marketing campaigns.

You can use More Than Words’ professional services to clean, replace, and validate marketing databases for businesses, schools, and the public sector.

To find out more contact 0330 010 8300 or email

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