POF Conversion Tracking for Profitability

POF Conversion Tracking for Profitability – Phase 1

Plenty of Fish has recently implemented conversion tracking into their ad platform. This will show you the exact characteristics of your converting users. You can use these reports to take a non-profitable campaign and turn it into something that will help you regain the money you lost testing and ultimately turn a profit.

This case study will take a real general dating offer and advertise it to the masses. I will take the data from their conversion tracking report and break it into ultra-targeted campaigns. I decided to go with the Singlesnet 25+ offer on C2M. I’ll be using some pretty generic ad copy that has been proven to work and will give them away below. The images I’m going to be using were gathered by me personally and I have a feeling that they will do quite well on POF so I won’t be outing those, sorry fellas. The frequency cap will be set to 3 and my bids will start out at $0.46 using Mr. Green’s 1 Penny Tip.

Targeting Criteria

  1. Single, widowed, divorced or separated Males that live in the United States and are between the ages of 25 and 32.
  2. Single, widowed, divorced or separated Females that live in the United States and are between the ages of 25 and 32.

Male Ad Copy

  1. Single Available Women!
    Are you looking for more single women in {state:your state}? Sign up now and find them tonight!
  2. Single Women!
    Are you looking for a single woman in {state:your state}? Sign up now and find her tonight!
  3. Want a Girlfriend?
    Sign up now and find a girl in {state:your state} tonight!

Female Ad Copy

  1. Single Available Men!
    Are you looking for more single men in {state:your state}? Sign up now and find them tonight!
  2. Single Men!
    Are you looking for a single man in {state:your state}? Sign up now and find him tonight!
  3. Want a Boyfriend?
    Sign up now and find a man in {state:your state} tonight!

POF Conversion Tracking for Profitabilty – Phase 2

I spent $550 and tried to split the amount between the male and female campaigns for Singlesnet. I’ve included a copy of ad copy split testing results and the conversion breakdowns for both, males and females. For the campaign targeting males I spent a total of $300.89 for 26 conversions at $4.00, resulting in a loss of $196.89. When it came to females I spent $254.43 for 21 conversions at $4.00, which also resulted in a loss to the tune of $170.43. These kinds of losses can be expected when you do really broad targeting to a really broad dating offer. My goal here was to try and find certain target criteria that converted better than others and I did just that, which I’ll talk about shortly.

Here you will see the ad copy split testing results and conversion breakdown for criteria with more than 5 conversions for the male gender.

Ad Copy Clicks Conversion Rate
Single Available Women 173 2.89%
Single Women 140 2.86%
Want a Girlfriend? 271 6.27%
Factor Conversions Conversion Rate
Education – Bachelors Degree 7 7.61%
Body Type – Average 11 5.56%
Income – 35,001 to 50,000 7 5.22%
Age 18-30 20 4.66%
Drinking – Socially 19 4.58%
Relationship – Long Term 6 4.35%
Body Type – Athletic 10 4.31%
Country – USA 21 4.19%
Education – High School 6 4.11%
Car – Yes 17 3.95%
Relationship – Dating 10 3.94%
Smoke – No 15 3.79%
Marital Status – Single 17 3.68%
Intent – Putting in serious effort to find someone 8 3.43%

As you can see from these results, I will be using the, “Want a Girlfriend?” ad copy, paired with a number of images that did well for me on this campaign. I will also be targeting men who have a bachelor’s degree, average body type, income from $35,001 – $50,000, drink socially and are looking for a long term relationship. I will build out separate campaigns for each of these 5 criteria. The rest of the targeting will be exactly like it was in Phase 1, except that I will only be targeting 25-29 year olds and leaving out the 30-32 year olds. They didn’t convert nearly as well as the 25-29 year olds.

And below you will find the ad copy split testing results and conversion breakdown for criteria with more than 5 conversions for the female gender.

Ad Copy Clicks Conversion Rate
Single Available Men 174 2.30%
Single Men 64 4.69%
Want a Boyfriend? 266 5.26%
Factor Conversions Conversion Rate
Relationship – Dating 6 4.41%
Marital Status – Single 14 4.32%
Smoke – No 12 4.17%
Car – Yes 12 4.03%
Country – USA 14 3.83%
Female – Age 18-30 13 3.82%
Body Type – Average 6 3.53%
Drinking – Socially 9 3.05%

Again, we see that the ad copy that performed the best was, “Want a Boyfriend?”. There were no obvious criteria that performed better than the others, so I’m going to leave the female campaign alone and focus solely on the male campaigns since it had more useful data.

I will be building the aforementioned campaigns tonight. Once they blow through the $500 in the coming week, I will make a follow up post with the results.

Please note that I didn’t pause any ad copy on purpose. I only checked the stats once a day and any images with .09% CTR or lower was paused. So that is probably what contributed to the large discrepancy in the number of clicks each ad copy received.

POF Conversion Tracking for Profitabilty – Results

Last weekend saw the final phase of my case study using POF’s conversion tracking to help turn a campaign profitable. Unfortunately, Phase 1 provided some skewed results because I tried to split $500 in testing between too many variables. Simply put, there wasn’t enough testing done and I realized it after analyzing the results. But, I took what data I had and went with it. I decided to test the results of only the male gender because they provided the most statistically significant results. The campaigns didn’t lose as much money as the first round and none of the campaigns were profitable, but I’ll explain why it was my fault and what you can try to turn a similar campaign profitable.

Targeting Criteria: Body Type – Average

Spent $107.12 Impressions 270,055
Revenue $68.00 Clicks 274
Net -$39.12 CTR 0.101%
Conversion Ratio 6.14%

Analysis: On my initial results 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

Spent $112.69 Impressions 301,433
Revenue $36.00 Clicks 244
Net -$76.69 CTR 0.081%
Conversion Ratio 3.72%

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

Spent $87.87 Impressions 220,1184
Revenue $24.00 Clicks 142
Net -$63.87 CTR 0.064%
Conversion Ratio 4.17%

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

Spent $99.32 Impressions 249,717
Revenue $52.00 Clicks 183
Net -$47.32 CTR 0.073%
Conversion Ratio 6.02%

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

Spent $93.58 Impressions 235,279
Revenue $32.00 Clicks 223
Net -$61.58 CTR 0.095%
Conversion Ratio 3.56%

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 PFO would 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 Ad 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 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. Update: I did another case study excluding poor performing criteria.

I also should have tailored my ad copy in every campaign to personalize the ads in hopes of getting a better ctr and conversion rate.

Disclaimer: this POF Case Study has been copied and pasted from my blog at RileyPool.com where I originally did this POF case study. This case study was done during July 2010.

Comments

  1. Most aff networks do not have room to add 2 tracking pixels to an offer. I know Wolfstorm Media does, but many others don’t. I am not a coder, but what is a workaround? Can I create a 3 PHP file and submit that as tracking pixel and have that PHP file call the tracking pixels (Prosper and POF)? Not sure if that technically works, do you know?

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