If you set DPSAM up with global/merged group support, your users can experience instant filtering out of the box. From a completely empty corpus, however, we found DSPAM to start filtering its very first spam with 10-20 SPAMs [reported into the system]. DSPAM generally climbs to around 95-98% accuracy within the first few days to a week or so, depending on how much mail you receive. It catches a majority of spam with only around 100-200 spam reported into the system, learning from the other few thousand it should catch by itself in the meantime.

If you require faster precision results, you might want to start your users off with a seeded dictionary (see the dspam_merge tool), or use a global or merged dictionary for your users to start with. Many advanced features of DSPAM, such as Noise Reduction and inoculation do not kick in until at least 2,500 innocent messages have been learned. You can use the included dspam_stats tool to get a good idea of how effective your current dictionary is.