If you are using an additional anti-spam product along with the SPAMSteward service, there are typically two reasons why the third party filter may be identifying spam messages that SPAMSteward did not identify as spam.

1. The message may have bypassed the SPAMSteward service altogether (the message did not even pass through our filters). Please click here for more information on bypasses.

2. Many anti-spam products rate all (or most) messages as possibly being spam. Please make sure that your anti-spam product determined that the message was absolutely spam and not just 10-90% likely to be spam.

Many of these products that use Bayesian and other heuristics will determine that most of your email is spam, including legitimate email. In these cases it's normal for most of your email to be identified as spam, especially mail from new senders (potential new clients). We do not recommend simply marking all email from new potential clients as spam, and recommend that SPAMSteward not be used with other anti-spam products, as you will just encounter more false positives. If our service is not blocking 98% of your spam, we're happy to work with you to resolve any problem. Please click here for a list of the most common causes when not receiving expected service levels.

Although it is true that Bayesian and other filters that use heuristics are occasionally able to guess that some types of email are possibly spam when SPAMSteward did not, you will find that in the long run our filtering will be more accurate. Bayesian and other heuristic filters have different weaknesses than content based filtering, but you should find that the weaknesses inherent in content based filtering are more acceptable.

In addition, Bayesian and other heuristics typically only tag such messages as "possibly spam". This means that you will still have to review the messages, since it’s just a guess as to whether the message is actually spam. You don't want to miss any important emails because your software guessed that an email from a new client was 51% likely to be spam.

The type of filtering we do is the next generation in anti-spam filtering - we actually determine for certain that a message is either spam or is displaying characteristics reminiscent of a spammer. A respected independent reviewer, Ron Anderson (of Network Computing), reviewed the top 30 anti-spam products in the industry and rated ours #1 for accuracy.

Please also see our article on challenge/response systems.