Why Is CRM Data Cleaning So Important? (Plus, the Techniques That Help You Keep Data Clean)

Carl Taylor | July 4, 2022

Your CRM data is invaluable for a successful business. However, that data will only be of use if you keep it clean and formatted correctly.

It goes without saying that accurate and relevant data is crucial for business success.

With pinpoint information, brands can precisely time their outreach and use the optimal channels to engage their prospects and customers. However, the data needs to be flawless to make this process as efficient as possible.

Unfortunately, this is often not the case.

According to several studies, about one-third of the data stored in company databases becomes outdated every year. Naturally, this prevents businesses from gaining valuable insight.

Bad data can represent a significant obstacle, drawing unnecessary expenses in resources, time, and effort. As a result, a company’s entire ROI can diminish significantly.

Contact information can change during a single year, making companies miss out on many opportunities, regardless of whether they’re in the B2B or B2C space. Besides outdated and incorrect information, data can also be bad if it’s duplicated, low-quality, missing, or poorly formatted.

Due to bad data, brands can have optimisation issues, conduct unsuccessful marketing campaigns, and suffer from poor brand perception. As a knock-on effect, bad data can negatively impact the entire organisation.

When the demographics of your customer base aren’t recorded correctly, your customer relationships can suffer irreparable damage. The same goes for flawed personalisation efforts.

Even worse, companies don’t get an unlimited number of attempts to restore customer satisfaction and regain trust. In other words, an unfortunate series of data errors can cost businesses more than they can handle.

The potential damage of bad data goes beyond marketing teams, too. Customer service, sales departments, and, by extension, management can feel the detrimental consequences.

When all this is taken into account, it’s clear that data cleaning should be an essential task in every organisation.

This article will explain what data cleaning means and suggest several useful techniques to keep your information clear of mistakes and up to date.

Explaining Data Cleaning

The first thing to note is that data cleaning is done on raw data before it’s analysed.

The process consists of discovering irrelevant, wrong, or otherwise faulty data in the system. Then, the data in question is corrected or removed.

While the term ‘cleaning’ might seem to imply deleting information, it doesn’t necessarily mean all bad data should be removed. Instead, data cleaning is a method of maximising accuracy while maintaining as much information as possible.

The potential corrections can include syntax and spelling corrections, data set standardisation, and error correction. For example, the data can become useful after duplicates, missing code or empty sections are removed.

As a part of data science, data cleaning isn’t the most straightforward process for non-experts. However, you can employ several techniques to keep the data in your CRM up to date.

The Key Data Cleaning Techniques

Employing data cleaning techniques will make your CRM more efficient. This improvement can enhance the profitability of your organisation and make your marketing and sales efforts more successful.

1. Purge Duplicate Data

Duplicate data can have an unfavourable effect on your customer satisfaction. It can lead to double-targeting, which means the same customer receives the same offer several times.

Of course, this can lead to people viewing your messages as spam, which is bad news for every brand.

Duplicated data appears more often than one might think. For example, several team members might enter identical customer data, or the same people might sign up multiple times. And if you import new data, the system might not recognise that matching information is already present.

Duplicate data can be removed from the system or merged. In most cases, this will be impossible to do manually.

Luckily, there are several automated solutions to handle duplicates. Dedicated apps can scan your database for multiple instances of the same data, while others can merge the duplicates.

Purging duplicate data will help you prevent various complications. When the duplicates are accounted for, your CRM should be set up to block any potential instances in the future. Certain CRMs come with native duplicate protection, which will be particularly useful.

Data duplication can happen when contact information is improperly imported across platforms. To reduce the chances of that happening, you should ensure the data is adequately stored while keeping efficiency in mind.

Our Automation Heroes can help in that regard. We can migrate your contact information onto an email platform with the correct tags of your choice, reducing the possibility of errors or discrepancies.

2. Limit Administrative Users to Lower Data Crossover

Data duplication can be avoided to a large extent by limiting admin users.

Naturally, how many team members in your organisation have complete administrative access will vary depending on the company size. Generally speaking, that number should stay within single digits for small to medium-sized businesses.

Fewer administrative users will mean better coordination in terms of data entry. And if your choice is limited to experienced team members, you’ll reduce the chances of data duplication significantly.

3. Create Standards and Practices for Data Entry

If you’re having issues with missing rather than duplicate data, you should look at the way information is being recorded.

Inconsistent methods of data input can produce complications within your system. This issue is particularly complicated because it can be caused by seemingly minor details.

For example, the information might be formatted differently. This extends to how you write names, addresses, and job titles. Whether all entries use the same capitalisation rules and abbreviations could be the difference between a reliable dataset and an almost unusable compilation of information.

To determine if your business has this type of issue, you should first perform a detailed analysis of the existing data.

Look for discrepancies in naming. In particular, see whether only formal names are used in all cases or if some entries include nicknames.

Check for the physical address formatting and how address changes are noted in the system.

Note if job titles are abbreviated or written out in full.

If you find mismatches in those fields, you’ll need to create a standard that all data administrators will adhere to. Furthermore, you should pay attention to how people from the same household are linked in the system and how notes are formatted.

It would be best to document all these practices and make the guidelines readily available for all team members who have administrative access to your CRM.

When you standardise your data entry formats, a significant portion of issues should be removed, and further discrepancies are much less likely to appear.

4. Use Tools to Validate Data Accuracy

As previously mentioned, manual data maintenance is practically impossible. In addition, it would be less effective and wasteful for your resources even if it could be done.

The ideal solution lies in using automated tools. In fact, some tools can help you do just that in real-time.

Tools like Tye can standardise your data by removing duplicates and invalid emails, as well as uniforming your lists. Drake can resolve any data dependencies, while Winpure can scrub redundant data extremely fast.

Other tools, such as OpenRefine and Data Ladder, can reformat and clean up your data and handle massive amounts of information automatically.

With some careful inspection, you can find just the right tool to ensure the information in your system is accurate and up to in-house standards. There are certain universal features that the tool of your choice should have, including duplicate detection, bulk formatting, and cleansing automation.

5. Archive Old and Unused Data

Even if certain information in your system isn’t particularly useful at the moment, that doesn’t mean the data won’t come in handy in the future.

You might use that information for reference, but you don’t want it clogging your system in the meantime. At the same time, some information could prove useful after several years.

The best way to handle data of this type would be to archive it.

Archiving data might not resolve issues with duplication or bad formatting, but it can bring other benefits. In particular, your CRM may function faster and more reliably.

When you archive unused data, you can speed up the processing time, free up storage disk space, make relevant details easier to find, and reduce the backup and restore time.

All this will make your CRM much more efficient. With a tidy data bank, you’ll also have an easier time managing the information that’s currently in use.

6. Outsource Data Cleaning

In many cases, outsourcing all of the data maintenance is a good choice.

Getting all relevant information in order can be time-consuming. Alternatively, the job can use up much of your resources.

Luckily, you can find dedicated services for data cleaning that will take care of the work for you. Outsourcing can often prove to be more cost-effective than managing data in-house since doing it yourself will likely involve expenses for additional tools and staff.

However, the greatest benefit of outsourcing will be in saving your most valuable resource: time. By delegating the work to a third party, you can avoid draining your team’s work hours with data management. Instead, your team members can focus on their essential tasks.

7. Schedule Regular Data Maintenance

It’s worth noting that data cleaning is a recurring job. Even if you get all of the information in your system in order, you’ll need to repeat the process again in a matter of months.

That’s why it would be best to have a clear schedule with time reserved for data cleaning. This principle will apply regardless of whether you do the job yourself or outsource it.

Keeping your data clean on a regular basis will help you avoid problems in the future and make your database more reliable.

Keep It Clean

A clean database means more dependable business operations, especially in the marketing and sales departments.

Getting the information formatted properly, resolving duplicates, and purging unnecessary data will improve your systems across the board. With the data in check, your company will start to function like clockwork.

Automation Agency can help you bring your data up to date and resolve any lingering issues. If you want to learn more about the services that could optimise your business through CRM implementation, don’t hesitate to join our Concierge Service.

About the author 

Carl Taylor

Carl Taylor is the Founder & CEO of Automation Agency. For the past 10 years Carl has been building businesses and marketing them online through the use of Sales Funnels, Email Marketing Automation, Landing Pages, and Wordpress Websites. Carl is also a #1 author and highly sought after speaker and consultant whose work has impacted thousands of businesses across various industries worldwide.

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