4 ms·

> Furthermore, granular targeting is no longer the way to scale on Facebook. Can you elaborate on this? I’m not sure I understand what the alternative is.

fairity 6y ago
3-5 years ago, the most effective way to design campaigns was by micro-targeting audiences. That is, you would have thousands of adsets, and each adset would target a small slice of your target audience. The theory behind micro-targeting was that your audience's conversion rate varies considerably by certain key targeting attributes. And, if your audience has varying conversion rates, your CPC bids ought to reflect this. For example, let's assume your LTV is $100. And, let's assume your average conversion rate is 1%, but actually, males convert at 0.5% and females convert at 1.5%. If you do NOT split your audience by gender, you will be forced to bid $1 per click for every user. However, if you split your audience by gender, you can bid $0.5 for men and $1.5 for females. By splicing your audience, you gain considerable efficiency. The theory behind micro-targeting was to find the permutations of targeting attributes that split your audience into segments with the most variance in conversion rates. However, what's happened over the past few years is that Facebook's AI has become vastly better at doing micro-targeting than even the best individual marketers. This is partly because they have more data than platform participants, but also because they have much smarter engineers. As a result, it's now become better to hand over targeting responsibilities to Facebook's AI. For the most part, you just tell them what you want the average CPA to be, and they do the targeting for you behind the scenes.
- disgruntledphd2 6y ago
  This has actually been true since at least 2013, as long as you were optimising for something that made you money. If you're optimising for a proxy objective, more granular targeting can make sense (if you have more information about your customers), but if you can just make money from website conversions or in-app purchases, you're better off letting the algorithm do its thing. (The magic is driven not by incredible engineers but by more people to show the ad to enabling the only people who see it to have high expected conversion rates. This is perhaps the real dirty secret of internet advertising, in that they are predominantly platforms for showing ads to people who were probably going to convert anyway).

fairity 6y ago

3-5 years ago, the most effective way to design campaigns was by micro-targeting audiences. That is, you would have thousands of adsets, and each adset would target a small slice of your target audience. The theory behind micro-targeting was that your audience's conversion rate varies considerably by certain key targeting attributes. And, if your audience has varying conversion rates, your CPC bids ought to reflect this. For example, let's assume your LTV is $100. And, let's assume your average conversion rate is 1%, but actually, males convert at 0.5% and females convert at 1.5%. If you do NOT split your audience by gender, you will be forced to bid $1 per click for every user. However, if you split your audience by gender, you can bid $0.5 for men and $1.5 for females. By splicing your audience, you gain considerable efficiency. The theory behind micro-targeting was to find the permutations of targeting attributes that split your audience into segments with the most variance in conversion rates. However, what's happened over the past few years is that Facebook's AI has become vastly better at doing micro-targeting than even the best individual marketers. This is partly because they have more data than platform participants, but also because they have much smarter engineers. As a result, it's now become better to hand over targeting responsibilities to Facebook's AI. For the most part, you just tell them what you want the average CPA to be, and they do the targeting for you behind the scenes.

disgruntledphd2 6y ago
This has actually been true since at least 2013, as long as you were optimising for something that made you money. If you're optimising for a proxy objective, more granular targeting can make sense (if you have more information about your customers), but if you can just make money from website conversions or in-app purchases, you're better off letting the algorithm do its thing. (The magic is driven not by incredible engineers but by more people to show the ad to enabling the only people who see it to have high expected conversion rates. This is perhaps the real dirty secret of internet advertising, in that they are predominantly platforms for showing ads to people who were probably going to convert anyway).