You may be all about perfecting your email game, but there's, like, this fine line between you flexing on the marketing world and email spam filters doing their thing and hitting your email sender reputation.
Statista estimates that global cybercrime will cost firms $10.5 trillion annually. This precisely explains why email spam filters are getting stronger.
If you get how email spam filters work and how to prevent emails from going to spam, you can totally guarantee that your emails fall into recipients' inboxes. Use this free email revenue calculator to determine how much money you could gain from email outreach.
Alright, let's cut the small talk and dive straight into the email spam filter game.
By the end of this article, you'll be clued in on how spam filters do their thing, the different types out there, and how to slide past these email gatekeepers.
The Article Walkthrough:
An Email Spam Filter: How Do Spam Detection Systems Work
Behind every email spam filter stands a well-developed algorithm that helps it detect potentially suspicious emails. Different spam filters rely on varying criteria to spot separate red flags.
Most spam filters consider multiple email features and components that act as attention triggers. They assign each message a score that predetermines whether the email lands in the primary inbox or spam folder or is blocked altogether.
Spam filters will react instantly to those IP addresses that have already been marked as spamming, not to mention attached links, large fonts, and images that are usually treated as non-official business cards of cybercriminals.
Remember that most spam filters constantly learn from real users' behavior. As people mark different incoming messages as junk, spam filters analyze those, too, to detect standard features that can be used for spam detection in the future.
However, no spam filter is perfect since most users prefer to have a few spam messages land in their primary inbox rather than a potentially important email getting lost in the spam folder forever.
With all the theory and handy visuals, you may be curious about how an actual spam filter works. So, we'll have a brief overview of the Barracuda filtering process:
- The filter scans the sender's IP to determine if it belongs to the list of suspicious addresses.
- The message is checked for any signs of malware or viruses attached.
- Barracuda conducts a Bayesian analysis to determine how the sent email correlates with the known spam database.
- The filter carries out a spam intention analysis to determine if the message is sent to persuade the reader to do something—something a cybercriminal or a spammer would like them to fulfill.
- It checks if there are any admin rules violated.
- The spam filter looks for spam fingerprinting in case any other Barracuda installation has already marked the message.
Generally, spam filters like Barracuda are preset to focus on the 'bigger fish' scanning for viruses and checking blacklists first. After that, the filter checks out the remaining aspects (Check the article on Barracuda blacklist, SpamCop blacklist, SURBL blacklist, Spamhaus blacklist, and Spamhaus PBL blacklist to learn about major blacklists)
3rd Party/cloud-based spam filters
Cloud-based spam filters run on 3-party servers and have been designed to provide a business with extra protection over the emailing system. Such filters are developed to correspond with the company's email infrastructure. The well-tuned combination of these methods ensures enhanced fine-tuning.
As you put a cloud-based filter to use, you can decide whether you want to stick to an aggressive or milder anti-spam policy. The stricter the policy, the fewer emails will get into the primary inbox, and that isn't the best-case scenario since no filter is perfect.
Cloud-based filters are known for their improved reporting and analytical features. You can configure the filter according to your specific needs, which is a major advantage to keep in mind.
The core of cloud-based filters consists of balancing content and credibility metrics to figure out which message is most likely to be spam. Keep in mind that such filters work on a real-time basis, but they take a lot of data to analyze before finalizing the decision.
In case you wonder what reliable filters belong to the category, both Cloudmark and Symantec have proved to be more than effective.
Gateway spam filters
The Barracuda spam filter we discussed earlier belongs to the category of hardware-based spam gateway spam filters. These filters are usually placed behind a firewall to ensure that around 99% of spam messages are detected and effectively dealt with.
Such a high-end spam detection rate is explained by the "Greylisting" technology applied. Unlike filters that mainly compare a sending server's IP address against an RBL blacklist to detect unsolicited emails, gateway filters return the message back to the original mail server with a request to send it again.
The spamming mail server will usually ignore the "send again" request since they are busy scamming other people, and if the email does not come back, the filter marks it as spam. In the event that the message does come up, secondary checks are applied.
By secondary check-ups, most gateway filters identify IP addresses against blacklists, check their SPFs (Sender Policy Framework), and conduct recipient verification.
Being undeniably effective, gateway filters are slower than others, and this downside may be predetermined for those dealing with increased mail loads. Besides, some gateway filters lack SUBRL filtering, meaning spam URLs may pass undetected.
Desktop spam filters
First things first, it needs to be pointed out that desktop filters are also third-party spam filters. However, unlike other spam filters, they are directly installed on the user's computer, making these filters incredibly reliable and effective.
After you purchase and download one of these filters, such as Microsoft SmartScreen or G-lock SpamCombat, you can configure them according to your needs and preferences.
Besides, you can always upgrade or update your filtering strategies as the need arises. Desktop filters track the incoming messages after they pass Email Service Provider's (ESP) ones and sort them according to your customized preferences.
Email service providers' built-in filters
We've mentioned ESP filters briefly in the previous chapter. It must be stated that as email service provider's filters become more trustworthy and practical, desktop ones become less requested.
The most popular email service provider's filters would be:
- Gmail spam filter
- Outlook spam filter
- Office 365 spam filter
- Verizon spam filter
- Yahoo spam filter
The chances are that you've been using them without even knowing it since they are already built-in.
Some people still assume that these filters are primarily reserved for individual use, but most ESPs offer enterprise packages these days.
ESP's spam filters work according to the encoded advanced algorithms trained to detect the most recent spam patterns. They exploit Machine Learning to define the sender's trust score and inbox-worthiness.
Generally, these spam filters rely on 7 factors to decide which mail goes to the spam folder and which is sent to the primary inbox:
- Proper authentication (including IMAP vs POP3 setup)
- Source IP
- Email sender reputation
- Spam traps
- Blacklists
- Sender score
- Content quality
8 Types of Spam Filters Essential to Know
Content filters
Primary goal: To prevent unsolicited or potentially harmful emails from reaching the recipient's inbox by identifying and blocking spam based on the email content.
How does it work: Content filters scan the body text of incoming emails, looking for spam trigger words and assessing whether the email's content can be considered spam. For example, if it keeps finding the word "sale" over and over, it will give it a high spam score and block it from reaching the recipient's inbox. Each section and element of the email is included while screening - subject line, header, footer, photos, color, font, attachments, links, etc.
Email deliverability challenges: The apparent downside of content filters is that they can block harmless mail if it contains spam trigger words or exhibits other characteristics typically associated with spam. This can result in false positives and hinder legitimate email communication.
Quick strategies to pass through this spam filter:
- Avoid using shortened URLs
- Avoid overusing images and links
- Proofread your content for typos or grammatical errors
- Avoid 'spammy' or triggering words like free, donate, etc.
- Personalize your email content to make it more relevant (Check out our article on email marketing personalization for 14 additional suggestions on how to customise your marketing efforts)
- Use online free spam word checker
📚 Relevant reading: How to avoid the spam trap: Key strategies
Reputation-based filters
Primary goal: reputation-based spam filters are configured to evaluate sender reputation as the primary factor indicating whether the email is legit or sent from an unreliable source with a malicious purpose.
How does it work: reputation filters collect available sender reputation data, including but not limited to sending loads, frequency, and user engagement. They analyze the gathered information and compare the derived score to the acceptable threshold. The messages with low sender scores are marked as spam and kept out of the users' primary inboxes.
Email deliverability challenges: reputation-based spam filters are undoubtedly useful and practical. But, sometimes, these filters give out false positives if they are tuned to act overly aggressively so that important messages get into the spam folder. These filters are very complex since they use different factors to determine the sender reputation. Even if you are exceptionally careful while configuring those, their decisions are still difficult to predict.
Quick strategies to pass through this spam filter:
- Keep your sender score up
- Use a reliable ESP
- Authenticate your emails
- Monitor your reputation closely
- Perform email deliverability test before scheduled send-outs
Blacklist filters
Primary goal: to prevent emails from known scammers from getting into the user inbox. Blacklist filters must be regularly updated since spammers can update their sending addresses in no time.
How does it work: Blacklists rely on an IP address and email address database containing the most known spam senders. When an email is sent, the filter compares its credentials with the existing list of suspicious senders. If either the email address or the IP coincides with one added to the spam source lists, the message will be blocked or quarantined.
Email deliverability challenges: blacklist filters are incredibly handy and quite reliable, but there are a few downsides to keep in mind. At times, legitimate senders get added to the blacklist based on the filter's unique criteria. Thus, false positives are possible. Aside from that, spammers are incredibly quick to switch between their sending domains, and if the blacklist isn't updated on time, there's a chance of a fraudulent message passing through. Besides, you need to invest lots of time and effort to remove domain from blacklist (especially from such major blacklists as Outlook email blacklist or Spamhaus blacklist).
Quick strategies to pass through this spam filter:
- Create a strong and reliable email list
- Use a consistent 'From' address
- Work on a clear subject line
- Track your email delivery vs deliverability stats
Safelist filters
Primary goal: to ensure that messages from legitimate sources aren't accidentally blocked by spam filters. Safelist spam filters allow pre-approved senders to get past by spam filters unobstructed.
How does it work: A safelist filter, or a whitelist, filled with approved sender addresses or domains, is created by a recipient. The chosen email client adds these chosen addresses to its primary safelist. When an incoming email from an approved sender comes, the ESP or email client immediately recognizes it as a legitimate message and sends it straight to the primary inbox.
Email deliverability challenges: Safelist filters are prone to outdating. If you don't keep the list up-to-date, emails from legitimate sources will be directed to spam folders instead of the primary inbox. Besides, unreliable addresses are possible to infiltrate the safelist, and you'll be receiving potentially malicious messages instead. Safelist filters aren't effective when it comes to allowing in new and unfamiliar senders that may be useful to you.
Quick strategies to pass through this spam filter:
- Ask your users to whitelist you
- Use a recognizable sender name
- Stick to a consistent 'From' address
- Notify the userbase about any address or domain changes
- Follow the best email outreach trends
Header filters
Primary goal: To identify and prevent suspicious and potentially harmful emails from getting into the user's primary inbox. The main attention is aimed at the header components that can tell the filter a lot about the sending system and the sender themselves.
How does it work: header filter evaluates such an informative message field as the header, which contains useful information on the sender's IP and email's route. Based on the retrieved information, the filter understands which source the message comes from.
If the stated IP address belongs to the category of suspicious or potentially spamming sources, the filter will mark it accordingly. Moreover, spammers won't be able to pass by undetected even if they use a different email address.
Some headers present data that indicates that the given message is just a copy of the same email sent to different groups of people. These stats may trigger header filters as well.
Email deliverability challenges:
Email header filters are undoubtedly handy but are challenging to configure correctly. If you create an overly aggressive header filter, most legitimate emails will be filtered out based on sending loads, subject lines, or overall marketing content.
Quick strategies to pass through this spam filter:
- Start with a reputable ESP
- Keep up with your sender data consistency
- Keep away from spam trigger words
- Monitor email metrics
Language Filters
Primary goal: To detect and prevent the successful delivery of spammy messages based on the language factor. including but not limited to emails in foreign languages, inappropriate or offensive emails, overly salesy messages, etc.
How does it work: a language filter detects messages written in languages that aren't explicitly used in the location or preferred by the recipient. In the majority of cases, such filters keep the inbox load flow at bay since they sieve through all the mail, leaving out unusual language patterns and symbol combos, which also may turn out to be quite harmful.
Email deliverability challenges:
One of the most overlooked flaws of language filters, especially regarding email deliverability, is that they put business correspondence at risk. Suppose you cooperate with international partners or expect to establish such cooperation. In that case, the filter will cut in half your chance since it may accidentally send important emails to the spam folder.
Quick strategies to pass through this spam filter:
- Write emails in the language your target audience is fluent
- Use proper geolocation settings
- Stay clear of ALL CAPs and symbols in your messages
Rule-based filters
Primary goal: to filter out unwanted and potentially harmful emails from your primary inbox once and for all.
How does it work: rule-based filters are all about personalization and customization. These filters allow you to perfect the filtering process based on your individual needs and preferences. As the user sets well-defined rules, let's say to block emails based on sender IP, header quality, domain, location, word triggers, etc.
Email deliverability challenges:
One of the most apparent email deliverability challenges connected with the rule-based filter is, consequently, the best feature they are known for – customizability. As users personalize their spam filters, it's difficult to predict the criteria used. The challenge works both ways – while the sender is unable to get into the primary inbox, the recipient has no access to potential opportunities on offer.
Quick strategies to pass through this spam filter:
- Keep up with email compliance
- Personalize your content
- Check email deliverability before every campaign
- Interact with your target audience so that they whitelist you
Bayesian filters
Primary goal: to detect and effectively deal with spam messages based on the content criteria through unique and ever-changing filter algorithms.
How does it work: Bayesian filters use a statistical approach to spam filtering based on the Bayesian probability theory, named after British mathematician Thomas Bayes. The filters assign all incoming messages a probability score, letting only legitimate messages through.
While both Bayesian and content filters use the same email component to determine whether it is spam, the latter are run by predefined rules. At the same time, the former is known for its immense adaptability to ever-evolving trends and necessary flexibility due to the algorithms the filters are run by.
Sometimes even mail from the most legitimate sources ends up in the spam folder. Bayesian filters try to sort the incoming messages with as few casualties as possible.
Highly-effective statistical analysis allows the filter to adapt to your needs and preferences. As you mark certain emails as spam, the filter memorizes the pattern and prevents such messages from cluttering your inbox in the future. A low false positives rate is the most outstanding feature of the filter.
Email deliverability challenges: if you send bulk emails at random, the complaint rate will grow. Since Bayesian filters are highly analytical, the common patterns will have their effect, and these filters may block your future messages from getting into your target audience's inbox.
Quick strategies to pass through this spam filter:
- Avoid purchasing email lists at all cost
- Personalize each campaign and every message
- Work on your sender reputation
- Warm your domain up well
- Use an official email source
Bottom Line: Collaborative Filtering Trends
Global email marketing revenue is predicted to reach up to $11 billion by the end of the year and as much as $17.9 by 2027. In response, different filter types are likely to unite their efforts to keep digital communication via email safe and sound. If you want to join the beneficiaries of these marketing uprisings, you should be fully aware of the risks that collaborative filtering techniques pose.
With the best email outreach tools available in the market and dedicated monitoring of email compliance cganges, such as ever-changing Google email sending requirements, you can solve the problem before it causes any damage to your current campaign or email marketing in general. All it takes is to request a professional email deliverability consulting and have the experienced sharks of the marketing pool bite through the most challenging spam filter obstacles!
