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.

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.

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.

Related posts:

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