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.

Related posts:

1. Case Study: WAP & IAB Traffic on POF (Weekend 3 – Stats)
2. Case Study: WAP & IAB Traffic on POF (Weekend 1 – Stats)
3. Case Study: WAP & IAB Traffic on POF (Weekend 1)

Targeting Criteria: Body Type – Average

Analysis: On my previous case study an average body type showed a conversion rate of 5.56% which was higher than average for the entire campaign in the testing phase. On this final phase these numbers held true and the conversion ratio even increased a bit. This campaign had the second most amount of traffic. The CTR was the highest of any of the other campaigns. If you were going to start a campaign, I would definitely include this targeting criteria in your campaign.

Targeting Criteria: Drinking Habits – Socially

Analysis: When I did my original test campaign, this criteria converted right at the same percentage as the overall campaign.  In this second go round, it didn’t fare so well and performed well under what I expected to.  This target criteria by far had the most amount of traffic available.

Targeting Criteria: Education Level – Bachelors Degree

Analysis: This target criteria performed the best in the initial testing stage converting at 7.61%, but it only had 7 conversions.  I had high hopes for this campaign and a little bit of worry because I wasn’t sure if the conversion ratio was a fluke.  And as you can the conversion ratio didn’t perform as well as I had hoped.  After the testing, it converted just under the average ratio for the campaign.  I’m also pretty sure the target demographic for this criteria is pretty small, hence the CTR dying out on all my images really quickly and most images not even being clicked on after a few thousand impressions.

Targeting Criteria: Income – $35,001 – $50,000

Analysis: This is another target criteria that was pretty risky.  In my initial tests it only had 7 conversions, but it converted at 5.22%, well above the campaign average.  After sending a fair amount of traffic to it, it converted even better than in my initial tests.  The only thing holding this campaign back from being profitable was the CTR.  I struggled with CTR in this campaign for a reason unknown to me.  I used what I thought were some of my best images at this campaign without any luck.  So if you know you have some images with really good CTR, this is something you might want to build into your next campaign.

Targeting Criteria: Search Type – Long-term

Analysis: This criteria converted right at the campaign average and I wanted a fifth criteria to test so I threw it in there.  Unfortunately, the campaign didn’t convert nearly as well as it did in my initial tests, which could be contributed to it only having 6 conversions.  These users seemed to be pretty click happy as it had the second best CTR of all the campaigns, they just didn’t convert nearly well enough.

Final Thoughts

The day after the campaign I received an email from Convert2Media that informed me the payout for Singlesnet 25+ was raised to 4.50. So you can take all the revenue figures here and increase them by 12.5%. It still doesn’t make any campaign profitable, but it definitely helps out quite a bit.

It would really help if Plenty of Fish could include the estimated number of people in our target demographics to give us an idea of how long we can expect our images to last before the users succumb to banner blindness.

One of my biggest problems with these final campaigns was choosing the correct images.  When I was running these campaigns I had numerous other campaigns I was working on so it was tough to keep an eye on these campaigns, even while using Mr. Green‘s POF Tool to upload new images throughout the campaign’s livelihood.  If you can keep your CTR up on your campaigns you will be way closer to profitability than I was.  I also have to fault myself for not split testing images.  I rarely ever do this and is one thing I need to severely address.  I’ve done this a few other times and I do know that images to play a role in the conversion rates.

There are a number of things you can take away from this case study.  By looking at the numbers above you can clearly see two targeting criteria that convert better than others, so try building those into your campaigns.  Maybe you can even combine the criteria and see how they perform together, but that will limit the amount of traffic you can get it.  Or you can do it the other way and exclude poor performing criteria from your campaigns.

If you use any of the tips I mentioned here and don’t mind sharing in the comments below how it turned out for you, please do!

Related posts:

1. Case Study: Using POF Conversion Tracking to make a Profitable Campaign – Phase 2
2. Case Study: Using POF Conversion Tracking to make a Profitable Campaign – Phase 1
3. Case Study: Using POF Conversion Tracking to weed out non-converters – Results

I was wanting to promote a niche dating site and I thought I had found the perfect site to contact for a direct buy. After a few back and forths with the domain owner and we agreed on a flat fee of $250 for a 30-day long run of the site. I was going to share the banner inventory with another banner, so I would see half the site’s traffic. When I asked how much traffic his site received, he told me, “[Sitename].com gets around 3000 unique visitors per day.” and “The site gets around 300000-350000 impressions on average monthly.” After my 30 days was up, I ended up getting a total of 17,398 impressions, resulting in 86 clicks and 0 conversions. I have run this offer for well over a year now and the average conversion rate I see is 12-18%.

So here’s my $250 worth of media buying advice to anybody who is about to do their first buy.

1. Check the demographics of the site you’re interested in buying banner inventory on. Use Quantcast, Compete or your favorite demographic website. Even these results will not be perfect. Your best bet is to ask for a media kit, if one is available.  Make sure the demographics match what works best for your offer.
2. Whenever you ask for the amount of traffic a site has, ALWAYS ask for proof of this.  Check the website’s source code, see if they’re using any type of analytics tool, such as Google Analytics.  Ask for a report of the last 30 days worth of traffic, at least.
3. When scouring the details of this traffic report you just asked for, see if you can determine where his traffic comes from. Is it type-in traffic or is it from organic search results?  If it’s a bunch of type-in traffic, you can probably bet that your target audience will develop banner blindness quicker.
4. While you’re still analyzing that report, check which countries this traffic is coming from.  You better make sure the traffic comes from a country that your offer allows!
5. Finally, do some math to find out how many conversions you will need to be profitable.  If it was a flat-fee per month, it’s easy to figureo out what it will take to be profitable.  If it’s a CPM buy, calculate how many conversions you will need per thousand impressions to be profitable.  Using data from other traffic sources, about how many clicks does that translate too?  Using that information, what CTR should you be expecting?  How do these figures relate to other traffic sources you’ve tested?  Does it seem realistic that you might be profitable?  I hope so!

P.S. Yes I’m a fucking idiot for not doing proper research. Thanks for noticing. =)

Related posts:

1. Free MacBook Air from Profit Kings Media
2. Another $1,000 from Profit Kings Media!
3. Free $250 Facebook Advertising!

Related posts:

1. Wanna Make BANK on Plenty of Fish? Try this…
2. Plenty of Fish Case Study – CPM Bid Effects – Preview
3. Plenty of Fish Case Study: Session Depth (repost)

With some affiliates experiencing problems getting blacklisted from offers they promote on Plenty of Fish, I’ve decided to promote a dating offer where the quality isn’t expected to be top notch in the first place.  With this in mind, I’ve picked the Singlesnet offer on Profit Kings Media that accepts traffic from users that are 21 – 24 years of age.

I will only be using one ad copy.  The ad title will be: Single Available Women and the description will be:  There are 986 sexy, single women online in {state:default}. Sign up and meet them today!  The {state:default} will be replaced by the users state they registered in, so it will look more customized for them.

I will be targeting males in the United States that are 21 – 24 and are single, divorced, widowed or separated.

I’ve picked 6 random images from Justin Dupre’s image pack that he released on his blog.  The ones I’ve choosen are below.

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[View with PicLens]

I will be automating the creation of these ads using Mr. Green‘s Plenty of Fish Ad Uploader.  I suggest you buy a copy today!

I will report back next week on the numbers.

Related posts:

1. Plenty of Fish Case Study – CPM Bid Effects – Results
2. Plenty of Fish Case Study: Session Depth
3. Plenty of Fish Case Study: Session Depth (repost)

I also tested out a number of campaigns and failed miserably and lost hundreds of dollars.  So if you’re worried about losign a few hundred testing, this is not something you should try.

What I’m giving away here was my first profitable campaign on PPV.  I’m going to let everybody know just how I did it.

First thing I did was sign up on TrafficVance.  When you first sign up you will need at least $1,000 to get started.  So if you’re not able to blow some money, don’t try out PPV.

Next, you will want to go and download Laser URL.  If you don’t know how to use this program go here for Laser URL Tutorial Videos.  You will want to search a very closely related term to your offer using Laser URL.  I always let it search 10 pages deep on all three search engines.  This gives me a number of URL’s to prune and use for testing purposes.  Once you get these URLs, export them to a spreadsheet and then I suggest researching each URL to see if they even relate to your offer.  If they relate, it’ll be one of your targets.

I ran the Mobile IQ Quiz – QuizYou over at EWA.  I used Laser URL to search for the term iq quiz.  I of course pruned my targets and threw the list into TrafficVance.

My first time through I made sure I was the highest bidder on all the URL’s I targetted because I wanted some good test data.  I let it run for a couple days and came back to optimize it.  Make sure you’re tracking where your traffic comes from using the %%$KEYWORD%% variable that TrafficVance uses.  This way you can see which targets are converting and what the EPC for that target is so you can adjust your bids according.

After some time I was able to drop all the low traffic and non-converting targets down to about 10 targets.  The only bad thing about this was that I had to monitor these things day and night because I would get into daily bidding wars on URL’s, especially my best converting URL.  This got tiresome, I finally just got fed up with it and was okay with being in the 3rd spot.  I noticed more and more competition coming in on my targets and I was eventually being out bid on all my target URL’s.  The headache to keep up with these bids eventually became so much that I quit running the offer because of the increased competition and higher bids led to a dismal ROI that was no longer worthy of my time.

I came back a couple months later and noticed all the bids were much lower than they once were so I turned the campaign on and let it run for a couple days.  For whatever reason the offer was no longer converting on these URL’s so I paused the offer and haven’t ran it since.

My gross revenue for this offer was $7,144.00 and my total spend for this campaign was $4,867.27.  That equates to a $2,277 profit and a 46.7% ROI.

P.S. – If you’re going to run a PPV campaign, I suggest that your Prosper202 install be on a dedicated server.  I always suggest LiquidWeb for any server you may need.

Related posts:

1. PPVSpy – How is it useful for an affiliate running PPV traffic? Find out here…

After having 2 sets of images have their CTR die out on me I got lazy and tested out another another ad copy and saw my conversions tank by 54% so I figure the ad copy had to be misleading.   So I decided I wanted to try out 5 completely different sets of ad copy and see the difference between their conversion rates.  I tried to relate each ad title with the description.  I used the same images as my first go around so I know they can perform decently and since I haven’t ran them in awhile their CTR should at least be respectable now.

Here are the stats for the last 7 days according to Prosper.

• Ad Copy 1 (Original): 8280 Clicks, 438 Conversions, 5.29% Conversion Ratio
• Ad Copy 2: 12612 Clicks, 498 Conversions, 3.95% Conversation Ratio
• Ad Copy 3: 441 Clicks, 9 Conversions, 2.04% Conversion Ratio
• Ad Copy 4: 323 Clicks, 10 Conversions, 3.1% Conversion Ratio
• Ad Copy 5: 721 Clicks, 34 Conversions, 4.72% Conversion Ratio

I found it pretty crazy that my original ad copy converted best for me after the split testing I did.

So here’s concrete proof that split testing makes a huge difference!  If you’ve never split tested your ad copy, DO IT NOW! I’ve never done much split testing of ad copy until I ran this campaign and have finally came to an amazing revelation, even though I should’ve known it.

On Facebook your CTR depends on the image you use in your ad copy.  Your conversion ratio depends on the text in your ad copy!  It is imperative to split test both!

Related posts:

1. Split Testing on Facebook Case Study: Part 2
2. Split Testing on Facebook Case Study: Part 1
3. Case Study: Using POF Conversion Tracking to make a Profitable Campaign – Results

Okay so the CTR began to die out on the images I found in Split Testing on Facebook Case Study: Part 1.  I was still making some pretty good money off this campaign and decided I needed to switch up the ad copy.  Me being pretty lazy I went to the merchant’s landing page and used some of the lines that caught my attention in my ad copy and mind you since I was lazy I only used one variation and scaled this out to every demographic.  After about 5 days of continually submitting ads I finally got my ads past the review team at Facebook.  I just knew I was going to kill it again for a few days and wasn’t sure what I was going to do after that, probably try a different ad copy.

So I threw up this one ad copy using those images I used in the first go round.  I figure they haven’t been shown in a couple weeks, they should have some juice left in them.  Plus with some new ad copy I should be sitting pretty.

I ran it for a couple days and lost a nice chunk of change, mainly because my conversion ratio had tanked by 54%.  I’ve included screenshots below.  And that amount of data was more than enough to be statistically relevant.  My first concern was since I haven’t ran this offer in a few days maybe the advertiser was up to no good so I hit up my affiliate manager and asked him if the conversion rate for the network as a whole changed and he said nope.  So I was thinking since the only thing that had changed was the ad copy, maybe the ad copy was now a bit misleading because it did include that the user could win money.

Part 3 I will be split testing 5 different sets of ad copy to determine how it affects my conversion ratio.

Related posts:

1. Split Testing on Facebook Case Study: Part 3
2. Split Testing on Facebook Case Study: Part 1
3. Case Study: Facebook Ads – CPC versus CPM ($2163.08 spent)

I finally figured out something I could search for that would bring up similar images on Google image search and I found a couple I thought were going to kill it so I saved them.  I was talking to a friend about needing some more images and he told me to use Bing’s image search.  I checked it out and oh my god!  Bing’s image search is killer!  Try it out sometime if you haven’t already.

So I found 88 images I thought might work well and I used the same exact ad copy.  The only thing I did was change the picture.  I knew to be profitable in this particular demographic for this offer I would need a 0.10% CTR or higher with the amount I was bidding, so that’s what I was looking for.  If you’ll look at the screenshots below you’ll see I found a handful of keepers.

On the next part of this case study I’ll switch up the ad copy and see how well the ads perform.

Related posts:

1. Split Testing on Facebook Case Study: Part 3
2. Split Testing on Facebook Case Study: Part 2
3. Plenty of Fish Case Study – CPM Bid Effects – Preview

Are you trying to attack a micro-niche?  Say a niche of less than 100,000 on Facebook?  You better have your best ad copy and images ready to go from the get go.

With these small target demographics it’s a littler tougher to get started and get impressions.  Once you have some ads with an established CTR Facebook will favor those ads over new ads that are made.  Here’s proof.  I threw up some ads in a 75k demo that I was already banging out.  I wanted to test new ad copy because my CTR was dropping like a rock.  I had the same exact demographic using the same exact bid and these ads couldn’t even get 1 impression from Facebook because my other ads (and others I’m sure) were already sucking up all the impressions.  So I would have to bid higher and higher just to receive impressions at all.  Check out the image below for evidence of that.

If it’s a new vertical for you and you’re not sure what type of ad copy and/or image will work well I suggest trying out no more than 5 images and 5 sets of ad copy to split test.  Throw up those 25 ads, see which does well.  Then throw up another set of 25 ads to see which ad copy and images do well that time.  Then I would take your 4 best images and 4 best ad copies and this is when you turn up the traffic.

If you’re already in the vertical, such as dating and know which images are going to do well, just use a set of 10 or so images using an ad copy that is proven.  When the CTR on those images start dying pause those ads and bust out another 10 images that perform well using a different ad copy.  Just rinse and repeat this anytime your CTR starts to die out.  It works like a charm for me.

Have you experienced the same thing?  Let me know!

Related posts:

1. Exploring untapped micro-niches in dating equals money in the bank!
2. Split Testing on Facebook Case Study: Part 3
3. Split Testing on Facebook Case Study: Part 1