What is data cleaning and why does it matter?

One of our weekly tasks during our time at Zooma has been to update the contact cards in HubSpot. But we are not just doing that for the records to look good; there's a reason why you should care for your database. Your database contains a lot of value and data that has lost its value and only costs you time and money. So cleaning your database will save time and money and avoid sending the wrong information to the wrong customers.

The database loses value during a time - about 20-30% of the database disappears every year. So imagine, if you haven't cleaned your data in five years - there's a lot of dead data lying there, costing you money.

If contacts have not responded to your information or shown any interest for some time, it is better to delete them and put the resources on the contacts that engage.

Data cleaning - What and Why?

Data cleaning means removing irrelevant, outdated, duplicated, or inactive data (deleting contacts). It gives you an updated CRM system with accurate information. It gives you an updated CRM system with valid information. Depending on how many contacts you have in your system, it can be a tremendous job, and it feels overwhelming to go through all the contacts. But with a good system, there are ways to segment and sort out contacts that are no longer of value. The ultimate goal of data cleaning is to make a dataset as accurate as possible.

Why does it matter?

Having a trustworthy CRM benefits you in several ways:

Your data defines your decisions

The data you have may be based on campaigns. If you base your campaigns on incorrect data - there is a good chance that you are spending time and resources on a campaign that is not even relevant to your company or your contacts.

Incorrect information can make an unprofessional impression

You can put people in campaigns for the wrong part of the Customer/Buyers journey or the offer itself. For duplicates of contacts, you can also happen to put the same person in two different campaigns/workflows. It gives an unprofessional impression of the company, and the contact may choose not to interact with you, even if the offer itself is of interest.

Incorrect analysis

An example is that you create a list of 200 contacts that you put into a workflow or a campaign - but 25% of the contacts are irrelevant to the process and are bounces or duplicates. Therefore, your analysis will be incorrect in this scenario since the starter information will be false.

Your CRM and marketing tools are only as robust as the data you've got in them

It doesn't matter how advanced your CRM system is if you don't have quality data. There's a high risk that your data will be disorganised and incomplete without up-to-date data, affecting purchases and the customer journey.