Our spam filter prefers delivery over rejection. This means we don't often reject email just because it doesn't meet some technical configuration details. Many large mail services like Microsoft and Google Mail will immediately reject email that does not follow certain rules. On the other hand, we simply increase the likelihood it will be placed into your spam folder. While this method provides greater reliability with respect to delivery, it make identifying spam more difficult. If you tell us what you consider spam and not spam by following the best practices below, we will customize the spam filter for you.
The best ways for you to get the most from our Spam filter are (link to instructions and video below) ...
- Use our web based email client by logging into https://myeditweb.com
- Configure your email client such (Outlook, Thunderbird, iPhone, Android) to use IMAP protocol.
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You will now have two folders in your email client, one called Inbox and another called Spam.
- Set your spam filter settings (https://myeditweb.com) so Route Spam is set to Quarantine.
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Set your spam filter settings (https://myeditweb.com) so Sensitivity is set to Normal.
- If Spam Email comes into your Inbox, drag it into the Spam folder.
- If Good Email comes into your Spam Folder, drag it into your Inbox.
Click here to learn how to set up your email account to follow these best practices. Each email that goes through our spam filter is assigned a score based on over 500 criteria, each with its own score. If the score exceeds a certain number, the message will be classified as spam and put into your spam folder. If the message has a score under a certain number, it will be placed into your inbox.
Two of the scoring criteria are directly impacted by you moving messages between you Inbox and Spam Folder.
- Neural Network. This is the same Artificial Intelligence technology used by Chat GPT, Gemini, Copilot and the background removal feature of your smartphone. When you move messages between your Inbox and Spam folder, this information is used to train the Neural Network about what is and isn't spam. This neural network is resource intensive so all users share the same system.
- Bayesian Classifier. This system does a statistical analysis of the content of a message and classifies it Spam or Not Spam as compared to the statistics of other messages that are Spam and Not Spam. When you move messages between your Inbox and Spam folder the message is analyzed to learn how to score other messaged. The statistics are used only to classify the single users messages. This is what customizes the spam filter for each user.
Another important thing happens when you move messages between folders. We collect statistics about how these messages scored. We use these statistics to adjust our spam filter to work better. In a perfect world we would not see and messages moved. In the real world we try to get these numbers as small as possible. For instance, as more customers move messages and train the Bayesian Classifier, we may increase the importance of the classifier on scoring messages.
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