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This post is going to teach you how to give your campaigns an automated “refresh”.
POF has an option to target users by log-in count, that is, targeting someone by the # of times they’ve logged in to POF.com, over their lifetime. So, if you only targeted people who have logged in 150-200 times (log in count), then that’s the only time they’re going to see your ad.
Here’s a valid and tested strategy I like to call “Log in count breaks”. This idea is based on the fact that your campaigns will tend to die out the longer you keep them running. If you paused them for a few days and restarted again, chances are you’ll get better performance again. Here’s a graph illustrating my point:
(# of clicks w/ a break between June 11 and June 15)
So why not do this automatically with log-in count?
EXAMPLE: Campaign A is targeting 0-50 log in count & 100-150 log-in count and NOT targeting 50-100. This means when a user signs up for POF.com, they’ll see your ads up until they’ve logged in 50 times (0-50 log in count). Then, as soon as they hit log in 51, you give them a “log in count break” and your ads no longer show. Then, your ads reappear to the user after they’ve hit log in count 100-150.
This has worked for advertisers in the past so I hope it works for you too.
Finally passed 6 million logins in one day.
“Hard to believe after 8 years Plentyoffish still has non stop growth with no signs of slowing down any time soon”
Ever run a campaign and think, “Hmm, I wonder what my conversions would have been like if I excluded _________ demographic since the beginning?”.
Instead of creating a new campaign to split test your current campaign without ________ demographic, you can now exclude the demographic WITH THE CLICK OF A BUTTON.
For example, Take this sample conversion report, I’m going to click on the non-smoker demographic in the cross tab report to exclude non-smokers. I wonder how this will affect the conversion %’s. I chose non-smokers because it has a 9.798% chance to convert (which is low in the context of this campaign) and it has enough conversion #’s (121) to actually have an impact.
These are the results! As you can see, the majority of demographics have a higher % chance to convert so it looks like my campaign would have benefited by excluding the non-smoking demographic. Overall conversions # would be fewer but you’ll get more bang for buck when optimized.
So forget about creating 100′s of campaigns to split test a variable at time.
Point. Click. WIN.
The 110×80 ads on ads.pof.com now have the ability to target people who are clickers! We define a clicker as a person who has clicked on an ad previously. It’s no secret that a certain % of people will NEVER click on an ad, no matter what you show them. Well, now you can exclude those people and focus your efforts only on people who are proven clickers. Pretty powerful stuff if you ask me!
Have a (profitable) weekend everyone,