Email lists are the start of any email campaign and newsletter management. However, a list can get messy from multiple merges or with user spammy behavior.
The benefits for cleaning your email list are:
- Improve deliverability - Every email provider uses your sender score to determine where to route your emails. To avoid being labeled as SPAM and successfully reach your user, the first step is to avoid sending emails to non-existing addresses. A bad sender score is hard to revert, so better spend some time up-front and clean your list from unreachable email addresses.
- Save money - Usually, you pay for each email you send. First, pruning your email list to remove duplicates and invalid addresses will save you money. Then, you need to remove all disposable email addresses that will never be read to keep only real emails.
- Detect and fix typos - After the cleaning process, wrong email addresses will be flagged. Manually, you can find simple typos in names or domains and fix them.
Email list cleaning is an important part of any digital business and must be done regularly. Datablist is a perfect data tool to perform this cleaning process. Using this step by step guide, you will learn how to:
- Remove duplicate emails
- Check email addresses syntax
- Check if emails are from disposable providers
- Ensure email domains exist
How does it compare to paid email cleaning services?
If you search for email verification services on Google, you'll find hundreds (thousands?) of them. Almost all of them charge a fee per email address. Datablist includes an email verification service and it is free. It is great and enough for simple email verifications. However, if you need deeper analysis or if you have to perform verifications on hundreds of thousands of emails, please use a paid email cleaning service.
Step 1: Remove duplicate emails
Create a collection
The first step in the email cleaning process is to create a collection on Datablist in which you will pour your email addresses.
In Datablist, click the + to create a new collection. Select "Create collection from scratch" to have an empty collection and give it a name.
Ensure email uniqueness to remove duplicates
It's common to have an email list built over time. The result is several email listings merged into one. Resulting in duplicates! If your list stores contact information like First Name, Last Name, etc. you might have contact information spread over several duplicates rows.
To prevent duplicates, create a new Email property and select the "do not allow duplicate values" option. With this property option, Datablist will automatically deduplicate and merge your contacts on data import.
Import your email addresses
Now you have a collection, it's time to import your email lists: whether you have only one email list or several that you want to merge!
Datablist offers two options to import your data:
- With CSV files
- Using copy/pasting from a spreadsheet
Option 1: Import from CSV files
The CSV format is a simple standard to transfer tabular data between software applications. Every newsletter tool and digital marketing solution offer exports of your contacts in CSV files.
To import your CSV file, click the "Import CSV" button and select your file. Datablist will read the columns and show you a mapping page.
Map the CSV email column with the Email collection property. For the other CSV columns, map them with existing collection properties or click the + button to automatically create a new collection property that will match the CSV column.
Follow the process and select a merging option:
The merging option is important when your listing contains contact information in addition to the email address.
Soft Merge, if a contact exists with the same email, it will not update properties with previous data (contacts already in the collection or the first contact found in the CSV). This is the default setting.
Hard Merge, if data exists with the same email, it will update it.
Option 2: Import with Copy/Pasting
Datablist is compatible with copy/pasting from any spreadsheet. Just select the cells from your spreadsheet, go to your Datablist collection and use the
Edit -> Paste from your browser or directly the
Ctrl + v keyboard shortcut.
On pasting, Datablist will show you the columns and rows it has detected. To import a column, map it to an existing property or create a new property.
Warning: Only mapped columns will be imported!
Merge other contact lists if needed
If you are building an email collection from several sources, just import all your lists into the same collection. Any duplicates will be merged and you'll end up with a single list.
Step 2: Free email list cleaning
Now you have a collection on Datablist with all the email addresses, it's time to clean it!
What does the service check?
Datablist has a built-in free email verification service. This free service does 3 verifications:
- Email syntax analysis
- Disposable providers check
- Domain MX records check
Email syntax analysis
The first check is to ensure the email conforms to the IEFT standard and does a complete syntactical analysis.
This analysis will flagged addresses without the at sign (@), with invalid domains, etc.
Check disposable providers
The second check is to detect temporary emails. The service looks for domains belonging to Disposable Email Address (DEA) providers such as Mailinator, Temp-Mail, YopMail, etc.
The current database lists about 3000 disposable provider domains and is updated regularly using this disposable domains list.
Check domain MX records
A valid email address must have a corresponding domain name with configured MX records. Those MX records specify the mail server accepting the email messages for the domain. Missing MX records indicate an invalid email address.
For every email address domain, the service checks the DNS records and looks for the MX ones. If the domain doesn't exist, the email will be flagged as invalid. If the domain exists and doesn't have a valid MX record, it will also be flagged as invalid.
Perform cleaning on your collection
Performing an email list cleaning on Datablist is simple. Just select the email addresses in your collection and run the "Email Address Validation" action.
Once you have selected "Email Address Validation", a drawer opens on the right with 3 sections:
Input Properties, and
Select "Check for MX-records in email domain" in the settings to analyze the MX records.
Select the property from your collection that contains the email address. In this example, the collection has an "Email" property that will be matched.
The "Email Address Validation" service returns 2 values:
- Valid Email - A boolean (
false) to indicate whether the email address is valid.
- Error status - A text explaining why the email address is invalid when "Valid" Email" is
It's important to map the output properties to the collection to store the results.
Click the + on the right of each output property to add the result properties to the collection.
Once the service is done, analyze all invalid emails to detect easy fix typos.
Step 3: Remove unsubscribed emails
This last step is optional. You might have a dedicated list containing all unsubscribed emails that you want to remove from your main list. If your list with unsubscribed emails has a specific column like:
email | Unsubscribed email@example.com | yes firstname.lastname@example.org | yes email@example.com | yes
Simply import it to your Datablist collection using a CSV file or copy/pasting. Don't forget to create and map the
Unsubscribed column during the import.
Because you set the
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