Posted by Riley | Posted in Case Studies, Money Mondays, Plenty of Fish | Posted on July 11th, 2011
|Session Depth ≤ 20||0.511%||442||13||2.94%||$66.89||$49.00|
|Login Count ≤ 50||0.867%||341||13||3.81%||$33.77||$49.00|
I barely did any optimization on the images, I only got rid of the ones that were having the worst CTR, like the worst 10% and that equated to like 2 or 3 images on each campaign. I also submitted 37 creatives for each campaign and all but one creative was approved in every campaign.
My conversion ratio on the original campaign has tanked. I’m contributing that to the other two campaigns. I also wasn’t getting much traffic on it at 40c and raised it to 45c on Friday and 50c on Saturday.
The campaign targeting Login Count ≤ 50 wasn’t getting any traffic so I jumped the bid to 50c on Friday and 60c on Saturday and I’m still not hitting my campaign budget of $20 per day. I have a feeling that there’s not a lot of traffic here because users who are new to POF might not know of the iPhone app just yet, but I’m only guessing.
The campaign targeting Session Depth ≤ 20 was getting plenty of traffic, but I jumped it to 45c on Friday since I bumped everything else and then knocked it back down to 40c on Saturday. I was able to spend most of that $20 budget every day. I’m pretty sure by playing with my bid on this campaign and optimizing the creatives, I could get this profitable.
Plans for this coming weekend are to create a campaign that combines Session Depth ≤ 20 and Login Count ≤ 50. I also want to scale the campaign on Login Count to 50 – 100 and 100 – 150 to see how they perform.
Just so you guys know I’m more about testing out things and seeing how different targeting combo’s work on WAP traffic and not necessarily going for a profit. I’m just trying to find out what works and what doesn’t.
- Case Study: WAP & IAB Traffic on POF (Weekend 3 – Stats)
- Case Study: WAP & IAB Traffic on POF (Weekend 1 – Stats)
- Case Study: WAP & IAB Traffic on POF (Weekend 1)
- Case Study: Using POF Conversion Tracking to weed out non-converters.
- Case Study: Using POF Conversion Tracking to weed out non-converters – Results