Cleansing CRM Customer Data: How to Clean It

A large customer data, dream of every business or marketing team. But what happens when it is so big that it goes out of control or it starts to rot. When you are running a business, your customer data needs to be up to date and complete. No duplicate, invalid or incomplete data should be present in your CRM database. Although no one wants to sit on this kind of customer data, it generates over time when CRM teams do not pay attention to it.

Clean, organized, and accurate, these three are the important traits of an ideal customer database. Around 51% of businesses using automation tactics, it is likely that they are collecting a considerable amount of old or rotten information. It generates from your end or customers’ end. Either way, it is a business’s duty to keep their data clean.


# How do I keep my data clean in my CRM?                                                          


Whatever data you have in your CRM may not be at its best. You need to keep a check on this to make sure that the data is in the best shape possible. You can do it manually to find all the flaws and to restructure your data. If you use your manpower, it is like compromising their original tasks and operation to do this cleaning.


# Create a Standard Practices:                                                          


When it comes to data, you need a pattern to insert data into your CRM. Make sure you are training your employees or teams to feed the CRM with data in a fixed pattern. Creating these guidelines will help you create a clean database.


There are different patterns for different things. Like

Dates: April 13, 2021 APRIL 13, 2021 13/05/2021 13-05-1991
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Phone Number: 091-9111911100 +91-9111-9111-00 9111-9111-00 09111911100

# Limit Numbers of Editors:                                                          


As we saw just now, a single entity of data can be entered differently. This will create duplicate records of multiple data. To avoid this, what a business can do is limiting the number of editors. People who can enter, alter, or delete the data have to be limited in numbers. Give training to limited people about the guidelines and access to edit the data. Fewer people will create fewer errors in the database.


# Regulate the Cleansing Process:                                                          


When you are doing something good, you need to keep it in practice. This also applies to this data cleansing process. It doesn’t. If you have followed the above two steps at their core, there are always chances of error. Why? Because you are not able to control the people entering the data. For this reason alone, you have to make the cleansing process very much regular.


# The Effects of Bad CRM Data?                                                          


Errors are always progressive. If it is made, it will only multiply itself at every level. So if there is an error in your data, every interaction made with it will be flawed too. This will result in bad communication or can damage the customer relationship.

Let’s learn this with an example. Suppose a customer filled the contact form and by mistake chose Mr. instead of Mrs. This is the first error in our database. Now suppose you set up an email campaign. Due to that error, you are addressing that particular user as Mr. instead of Mrs.

Users won’t admit their error here. After seeing this error in the email they receive, they might flag your business as spam. According to IBM, bad data is affecting the US economy by $3.1 trillion every year.

But this was the customer-side error, right? What can a business do in this? To avoid this kind of error, Make sure users double-check the data they feed in the form. You can also revert users with their data you have every month or two.

In short, bad data can do these things:

  • Ineffective marketing campaign
  • Creating a negative image of the brand
  • Unoptimized personalized marketing campaigns
  • Flawed marketing efforts

# How to Keep it Clean?                                                          


There are several methods that can help you cleanse your CRM data.


# Detect and Delete:                                                          


As we spoke about it earlier, when multiple people have editor access to your CRM data, it is more likely that you will face this error. The best way to keep this clean at the editing stage is by only allowing a short number of people to edit the data.

Another way to do that is by setting your CRM to detect duplicate content. To do that manually, you can use the filters of your CRM. Sort the data by Alphabet, phone number, or other information to detect duplicates. Delete all the duplicates as soon as you find one.


# Archive and Reuse:                                                          


Sometimes you have data of some clients or customers that you want to keep for future use. If you keep it in your CRM, it will only complex the data processing. To avoid this, you can always archive your old data. This will free your CRM from the old and currently unnecessary data. Archiving your data can benefit you by:

  • Increasing data processing time
  • Freeing some storage space
  • Making data reading easy
  • Reducing data backup and restore time

# Outsourcing the Cleaning Process:                                                          


There are so many freelancers or outsourcing companies that provide proofreading services. You can always hire them for this if your CRM does not contain any kind of sensitive data. Customer data must be protected at all costs. You should opt for this service only when you trust the third-party fully. This can benefit you by:

  • Saving your time
  • Reducing the cost
  • Providing professional proofreaders

# Concluding:                                                          


So these are the methods you can use to clean up the mess your data is creating for your business. CRM is the one business solution that integrates with others to create more value out of your data. If this very data is not up to the mark, this workflow will be damaged. But after reading this article, I don’t think it will affect at least your business anymore. If you are new to all these you can always connect with us to clear your doubts and problems.

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