Whenever I’m looking for a new niche to get into I like to look at what some other affiliate marketers are doing to get my head going. I can’t name the amount of times I’ve found a new niche simply by going to a few websites that contain adsense or throwing a few words into google and then looking for affiliate links by clicking a few ads. Once I find an affiliate, one of my favorite things to do is get all the other domains that are being hosted on the same IP as their domain using whois.sc. This only works well if the person is on a dedicated server as shared hosting usually results in a few thousand domains per IP which aren’t related to the affiliate at all. However, if the particular affiliate is on a dedicated box more often than not I can get every domain that affiliate currently has and see every campaign they are running. I’ll then do further analysis on those domains using various sites (SpyFu, Compete, etc.) to find out where they are advertising their other domains. Within about 5 minutes I can have a complete view of all their domains, know which sites they are advertising on, and I can simply jump right into their niche if I feel it’s a good one since they’ve provided me with a landing page example, advertising sources, as well as the offer to run. With all that said, I can’t stress enough how important it is to keep all your major campaigns on separate IPs (separate C blocks if possible) or on shared hosting.
Archive for March, 2008
Competitive Intelligence
March 29th, 2008Creating Relevant Campaign Group Names to Increase Your Quality Score
March 21st, 2008One of things I keep hearing over and over again is having ad group name and keyword correlation in order to increase your quality score. Although it isn’t a large factor in the long run (imo) it can definitely play an important role in setting your initial quality score. With that said, the easiest way I’ve found to find relevant ad group names is to simply find out the word frequency within your keyword list. For example on a job related keyword list, this was partially the results:
[jobs] => 1990
[job] => 863
[in] => 805
[resume] => 633
[salary] => 544
[employment] => 282
[for] => 257
[agencies] => 239
[resumes] => 190
[com] => 187
[monster] => 185
[canada] => 178
[online] => 169
[a] => 169
[uk] => 158
[london] => 154
[technician] => 145
[free] => 137
[of] => 132
[courses] => 125
[search] => 121
[salaries] => 117
[description] => 117
From this I get an instant idea of what ad group names I need to make and I’ll even take this list deeper and pull out the word frequency for only the keywords containing “jobs” to find subkeywords to build even more tight knit ad group names.
Here is a little snippet of php code that will produce the same results with your keyword list (stolen from: http://snipplr.com/view/2225/php-tag-cloud-based-on-word-frequency/ and modified slightly) :
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | <?php // Store frequency of words in an array $freqData = array(); $keywords = file_get_contents('yourkeywordlist.txt'); // Get individual words and build a frequency table foreach( str_word_count( $keywords, 1 ) as $word ) { // For each word found in the frequency table, increment its value by one $word = strtolower($word); array_key_exists( $word, $freqData ) ? $freqData[ $word ]++ : $freqData[ $word ] = 0; } arsort($freqData); print_r($freqData); ?> |
