Since I know neither the schema nor the query you're running, I can only give you so much. You can look at costs to narrow in on a few spots.
Lines 30-32 indicate that you are pulling a lot of data from buyclicks and transactions. This makes up a huge portion of the cost of this query. Lines 33-40 are very similar. Looks like you are probably pulling more data than you need, and you'll see a lot of improvement if you can reduce these two spots. Fixing those two parts will make all the nested loops and hash joins that use this data a lot faster.
Looks like there are several sequential scans (Seq Scan) that you could likely improve with a quick index on the relevant columns. You seem to be filtering for similar things on ad_codes in a main query and a subquery, which probably could be refactored out. These are small optimizations compared to the first.
My email is in my profile if you want to talk about this more.
Lines 30-32 indicate that you are pulling a lot of data from buyclicks and transactions. This makes up a huge portion of the cost of this query. Lines 33-40 are very similar. Looks like you are probably pulling more data than you need, and you'll see a lot of improvement if you can reduce these two spots. Fixing those two parts will make all the nested loops and hash joins that use this data a lot faster.
Looks like there are several sequential scans (Seq Scan) that you could likely improve with a quick index on the relevant columns. You seem to be filtering for similar things on ad_codes in a main query and a subquery, which probably could be refactored out. These are small optimizations compared to the first.
My email is in my profile if you want to talk about this more.