"Congratulations! You have won, and here is your free guide to analyzing spam emails."
Imagine you receive an email with the above subject. Will you click on it or mark it as spam? Chances are your email service provider will have already sent it to spam or junk mail!
Spam emails were once a huge issue, but today email service providers use AI and machine learning to detect spam, and they do not even make it to most users' inboxes. But spam protection is a double-edged sword – a boon for users, but a bane for marketers.
Email marketers have an ongoing struggle to frame their emails in such a way that the email provider does not mark them as spam. Understanding what causes emails to be marked as spam is crucial in the present email marketing landscape.
In this blog, we will use Gigasheet, a no-code data science app, to analyze spam emails. Our spam email data analysis on a set of spam emails revealed patterns that can help you identify what factors decide whether your emails will see your audience's inbox or spam folder.
Our top 3 recommendations to prevent marketing emails from going to spam are:
First, did you know that you even have a sender reputation? Well, you do! And the email provider is going to use it to decide to let you into your target inboxes. The reputation is comprised of two parts:
Your email marketing program, or marketing automation tool is not a place to cut corners. If you found a great deal on a bulk email program, it may be too good to be true!
Email providers look at the IP addresses where emails are coming from, and if they are known to have spam complaints, then they will flag other senders from that address, even if their activities are above board. Simply put, you could be guilty by association!
There are plenty of options available these days, so choose an email program that is reputable. Many top email programs have built in tools to prevent spam triggers. That's a good sign that your shared companions may be following the rules.
Now that you have a reputable email marketing program, it's time for you to do your part to build your credibility. Your email sender reputation is a score that an Internet Service Provider (ISP) assigns to an organization that sends emails. The higher the score, the more likely the ISP will deliver your email to the target inbox!
Your email provider will also keep track of your activities. If they see you sending spammy emails, then you will be deprioritized even amongst your shared companions.
The easiest way to avoid this problem is to only email folks that have opted into your email list. There are also legal reasons, such as GDPR in Europe, why you should only email those folks who have opted in.
But there is even more that you can do! A lot of folks will sign up to your lists with a fake, or "burner" email address. Why waste time emailing these folks? You can use an Email Verification tool to automatically determine which emails are disposable. Gigasheet offers a free email verification enrichment that you can try today!
The enrichment will tell you whether an email address comes from an:
Lastly, you can go one step further and perform an email validation. This will actually reach out to the email in question and validate whether it is real or not! It is the only way to be 100% sure that you are targeting real email addresses.
Email Validation requires payment since it is an actual service. There are plenty of options online, and many offered inside your email marketing program. We are partial to Abstract API's industry-leading email verification API, which you can run on your data in Gigasheet.
In this section we are going to walk you through an analysis of spam emails using Gigasheet in a matter of minutes.
First of all, we need to upload our file to Gigasheet. Head over to gigasheet.com and log in to your account. You can log in using Google, Microsoft, and GitHub for seamless login.
Once logged in, we can get to work. Click on New and select CSV or XLSX file with spam email dataset. We will use the file named email.csv with 5,728 rows for our analysis. The file consists of two columns – text and spam.
You can upload files from your device or cloud storage. If your file is too large, zip it, upload it, and Gigasheet will process it easily.
Let us start with some basic grouping and filtering to get an idea of the dataset we are working with. We first want to know how much spam we received against the total number of legitimate emails. Then, we will use Gigasheet's group function to group emails by column spam.
We can see that, out of 5,728 email records, 4,360 are hams, and the remaining 1,368 are spam mails. We can visualize it using Gigasheet's inbuilt charts. We will select the grouped rows, left-click, and select chart range > pie.
Now, we want to focus only on spam and analyze what kinds of spam we have at hand. For that, we will use Gigasheet's filter tool and apply it to create a filter where the spam columns value equals 1.
Now, we only have spam in front of us. So let us see the average character count of these spam emails.
First, we will calculate the character count of each spam email to calculate the average character count. Then, we will click on the insert menu, select character count, and select the text column.
And for the average character count, we will select the Average function. On average, spam emails have around 1,137 characters. Similarly, we can calculate minimum, maximum and median, character count, and more.
A quick look at subject lines reveals a trend. Most of these spams offer a commission for signing up or claiming they can help us earn more. We can use Gigasheet's filter tool to substantiate our hypothesis to check all such spam emails.
We will create a filter to check and filter all the spam emails with the following words: free, sign up, commission, grow revenue, and increase sales. Hit apply, and we have 287 spam mails asking us to sign up for a service to earn a commission, increase online sales, and grow revenue.
Write subject lines that are meaningful and timely to your organization. Avoid action words that can be interpreted as "Spammy"
Unfortunately, these are likely some of the things you think resonate with your target audience. But you are a marketer! Come up with some Subject lines that are less spammy.
Also, if you chose a good email program, try A/B testing the subject line on every send. The good ones will send your email to a small segment of the list, test the subject line, and then send the remaining emails with the winning option!
You should regularly email your list. That way, you will stay top of mind to anyone that is subscribed. We are not saying every day, but we do recommend maintaining a cadence. Otherwise, an email once in a blue moon is likely to trigger many recipients marking your email as spam.
Along those lines, if someone isn't clicking or opening your emails, you should remove them from your list. Why? Well, it goes back to the email sender reputation. The ISPs are trying to protect their email clients from spam and only want to let emails that are wanted and relevant to them through. So, if the ISP notices that your emails are not being opened or clicked, they are going to eventually be blocked.
It's better to be pro-active and remove the person from your list, rather than be reactive and try to fix your sender reputation after you have been downgraded! Do not wind up on the wrong side of the spam filters.
If your email program allows you to see the last opened date, set up a job that automatically removes users from your distribution list after a certain amount of time of inactivity. If this isn't an option, set a calendar reminder and manually do this quarterly!
We have mentioned Gigasheet a few times in our spam email data analysis, so let us go over why you should choose Gigasheet for all kinds of marketing data analysis.
And that is why we choose Gigasheet over others to analyze data for marketing! The best part is Gigasheet is free to use, and that is not spam.