The one about layers

I spend most of my time on paid acquisition these days. App install campaigns more specifically. We’ve been successfully scaling and we’re at a point where I’m spending a couple thousand dollars / day. At this scale, I need to be more careful. You don’t want to make a mistake and waste $10.000 over a weekend. That would be a tough Monday. Especially because prices are lowest on Sunday for some app in our category. 

I think about the concept of layers in paid acquisition. Or, how far down the funnel do you look at (aka how many layers), when considering the price you’re willing to pay for an install. 

  1. First layer – install price. 

When you are starting out, you’re just trying to establish a solid price per install probably. I think the average is around $1 if the product is relevant to the audience. 

  1. Second layer – account created / engaged 

Once you start spending more, it makes sense to look at which audiences / countries actually get through your on-oboarding and either create an account and engage. 

  1. Third layer – revenue 

Right now we are optimising for revenue. Meaning we look at the end conversion per country and see what is the true cost we can pay and still make money. Doing this has changed the picture significantly for us. We did waste a good amount of our budget on countries where installs were cheap, but not profitable. And it wasn’t event the obvious cheap Chinese installs. This is to be expected, but the magnitude was unexpected for me. For example, now I know that a price in Scandinavia can be 300% higher than in Southern Europe and we’ll still make money. 300%! In a way this makes sense. Our app is only in English. Pretty much all young Scandinavians speak fluent English. Not so much in Portugal, Spain, France, Italy, etc…

Conclusion. Once you start spending significant amount of money, make sure you’re digging deep enough to understand the true cost and profitability of each installs. We’re only dividing this optimisation by countries. We will probably dig deeper. Maybe gender? Age? Will see. 

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