I just concluded an A/B test that I ran simply out of curiosity. I first created a total of 10 campaigns targeting different things and having different creatives. I then created identical copies of these 10 campaigns.
In summary, I had 20 CBO campaigns divided into group A and group B. I created 2 brand new Facebook pages; one for group A and the second one for group B. The only difference between group A and group B was that the page names from which the ads ran were different. The adsets, targeting, creatives and everything else was 100% identical. On these 2 different pages I even uploaded identical display pictures and content.
The results came out to be very shocking for me. I use the word shocking because the price per result wasn’t slightly higher on one page than the other. It was more than 100% higher which means if CPA was $10 on 1 page, it was $25 on the other page.
The takeaway is that Facebook page name has a massive role in your over-all ad performance and cost per result.
Some people make it seem like that creating viral content is a science. I think there’s some data analytics to it but it’s not entirely science.
In my opinion creating viral content means putting a ton of content out for your audience, studying consumption based on user behavior, and trying to replicate that again in the next piece of content.
It may sound like bit of a science, but the root of all viral content comes down to just pure testing.
These days I spend a lot of time and money running ads for our e-commerce store. The key to running ads right is to test everything; creatives, targeting, copywriting and all permutations of all variants.
In the end, I keep the ones that work, and stop the ones that don’t.
Product video ads aren’t much different either. I believe that before the consumers have received and used the product first hand, the product is only as good as it’s creative.
Sometimes we take segments of what works within multiple creatives and stitch together to make what now works as a whole.
In the end, for me, it’s just testing, looking at results, and improving based on the data.