Facebook managers trash their own ad targeting in unsealed remarks • Hacker News Board

Re: Facebook managers trash their own ad targeting in unsealed remarks

#71

Post by andylynch » Thu, Dec 24, 2020, 10:26 PM UTC

dodobirdlord wrote: post #49

scott00 wrote: post #30

Earlier quoted context omitted.

> It's not clear if Facebook explicitly knew at the time that the ad targets didn't meet the criteria, or if Facebook's targeting data was simply incorrect for those who were targeted. The plaintiffs don't care, nor should they. When I go to a restaurant and order a hamburger, if the server brings me a tuna melt I send it back. It doesn't matter why the server brought me a tuna melt. Facebook is essentially saying th…

We should give some amount of acceptance to the argument that modern contractual agreements are too complex for individuals to read and understand fully. But this is entirely unacceptable as an argument from one business buying services from another business. It’s not the “fine print”, it’s the contract. If the plaintiff’s argument amounts to “I didn’t read the contract.” they will rightly be laughed out of court.

Not necessarily. Given the scale of firms like Facebook there's a case for client categorisation like financial firms do, with additional duties and protections in play when dealing when with less sophsticated users eg. small merchants. Even beyond this mis-selling does lead to losing lawsuits despite what is attempted in fine print.

Re: Facebook managers trash their own ad targeting in unsealed remarks

#72

Post by [deleted] » Thu, Dec 24, 2020, 10:33 PM UTC

mjburgess wrote: post #5

This shows the limitations of ML: facebook has incredible amounts of preference & behaviour data on its users; and can't even meet incredibly generic categories such as "high-earner, college educated, etc.". The reason we think we're in an "AI" boom is 90% these ad. companies hyping their own abilities (an identical strategy to that of the initial boom in the 50s). What we call "AI" today is just an associative house…

[deleted]

Re: Facebook managers trash their own ad targeting in unsealed remarks

#73

Post by JMTQp8lwXL » Thu, Dec 24, 2020, 10:37 PM UTC

fairity wrote: post #18

Facebook's ad inventory is sold by auction. Inaccurate targeting isn't a big deal as long as all advertisers are treated the same. Furthermore, granular targeting is no longer the way to scale on Facebook. Therefore, inaccurate targeting will have little to no effect on most campaigns' efficacies (at least the ones designed by those who are knowledgable of the ecosystem). Any FB marketer worth their salt knows this.…

Couldn't this be sample bias since you were spending 8 figures? At that level of spending, you might be getting a proportionally higher 'correct' target demographic.

For small-time advertisers, FB knows these folks would have less capital to fight back against poor ad practices.

Re: Facebook managers trash their own ad targeting in unsealed remarks

#74

Post by Nbox9 » Thu, Dec 24, 2020, 10:40 PM UTC

nopriorarrests wrote: post #42

ma2rten wrote: post #29

Earlier quoted context omitted.

I can't speak for other people, but the reason that I think we are in an AI boom has nothing to do with online advertising. It is that computers can now recognize images, translate language, have conversations, generate articles, make realistic looking pictures, play the game of go, solve protein folding, generate realistic text to speech, recognize voices. All these things were not possible 5 years ago. Every year t…

>recognize voices. All these things were not possible 5 years ago. FTR: https://en.wikipedia.org/wiki/Dragon_NaturallySpeaking Dragon Systems released NaturallySpeaking 1.0 as their first continuous dictation product in 1997. As of 2012 LG Smart TVs include voice recognition feature powered by the same speech engine as Dragon NaturallySpeaking.

Along the same vain, Siri was launched in 2011.

Re: Facebook managers trash their own ad targeting in unsealed remarks

#75

Post by [deleted] » Thu, Dec 24, 2020, 10:42 PM UTC

mistersys wrote: post #25

the__alchemist wrote: post #21

Anecdotally, FB shows me the same ads on repeat: Few are relevant, and the same ones repeat past a threshold I'd assume would indicate I'm not interested. https://www.youtube.com/watch?v=KbKdKcGJ4tM

As someone who runs facebook ads for ecomm, repeated targeting are a core part of making facebook ads profitable. You'll almost never make money by running a simple, one-step ad with a link to your website. What we do is to target a group of people with a simple ad, then people who engage with or leave impressions on that ad will be run into a second ad, and so on and so forth until you finally funnel them into a con…

[deleted]

Re: Facebook managers trash their own ad targeting in unsealed remarks

#76

Post by marcinzm » Thu, Dec 24, 2020, 10:47 PM UTC

mjburgess wrote: post #5

This shows the limitations of ML: facebook has incredible amounts of preference & behaviour data on its users; and can't even meet incredibly generic categories such as "high-earner, college educated, etc.". The reason we think we're in an "AI" boom is 90% these ad. companies hyping their own abilities (an identical strategy to that of the initial boom in the 50s). What we call "AI" today is just an associative house…

AI doesn't need to be perfect to beat other approaches hands down and make hundreds of billions for companies using it. Having worked in the field, I'll take the 40+% revenue increases I got with AI in A/B tests any day of the week.

Re: Facebook managers trash their own ad targeting in unsealed remarks

#77

Post by selimthegrim » Thu, Dec 24, 2020, 10:55 PM UTC

mjburgess wrote: post #5

This shows the limitations of ML: facebook has incredible amounts of preference & behaviour data on its users; and can't even meet incredibly generic categories such as "high-earner, college educated, etc.". The reason we think we're in an "AI" boom is 90% these ad. companies hyping their own abilities (an identical strategy to that of the initial boom in the 50s). What we call "AI" today is just an associative house…

Someone better name their next paper after Hans Holbein

Re: Facebook managers trash their own ad targeting in unsealed remarks

#78

Post by amelius » Thu, Dec 24, 2020, 11:10 PM UTC

ummonk wrote: post #64

tsimionescu wrote: post #62

Earlier quoted context omitted.

Out of your list, translating language and solving protein folding are the only 2 that are likely to have any kind of major impact on the world in the somewhat near future, in my opinion. Image recognition may be a distant third, as it could prove very useful as a tool in many domains that have lots of visual data to sift through. Voice recognition is neat, and it is extremely useful in certain niches, but it is gene…

Computer vision is used for many driver assistance technologies, which are a big deal for ease of life.

People obsess too much over minor conveniences.

I don't care about driving. It still takes the same amount of time.

What I care more about is cooking. I'd rather have that one solved, as it would actually save me time. (No, I'm not looking for restaurants, meal delivery services or microwave meals).

Re: Facebook managers trash their own ad targeting in unsealed remarks

#79

Post by fairity » Thu, Dec 24, 2020, 11:10 PM UTC

stonecraftwolf wrote: post #70

fairity wrote: post #18

Facebook's ad inventory is sold by auction. Inaccurate targeting isn't a big deal as long as all advertisers are treated the same. Furthermore, granular targeting is no longer the way to scale on Facebook. Therefore, inaccurate targeting will have little to no effect on most campaigns' efficacies (at least the ones designed by those who are knowledgable of the ecosystem). Any FB marketer worth their salt knows this.…

> 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.

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.

Re: Facebook managers trash their own ad targeting in unsealed remarks

#80

Post by styles » Thu, Dec 24, 2020, 11:14 PM UTC

tylermenezes wrote: post #53

PragmaticPulp wrote: post #8

I know everyone loves to hate Facebook and articles that confirm that bias are very popular right now, but this lawsuit doesn't seem to have smoking gun evidence like the headline suggests. Have you ever written an e-mail or Slack message to a peer complaining that something at your company might not be working well? Or that something is totally broken and you think it should be prioritized in the ticket queue? Imagi…

As someone who has purchased Facebook ads, it's /so very evident/ that this is happening, that it's not particularly hard to compile evidence. Here's a specific example: we ran around $1k in ads last year, targeting senior-level engineers at technology companies, but the ads were getting liked by mostly people who worked minimum-wage jobs. Twitter and LinkedIn targeting were fine with pretty much the same parameters.…

I run $1,000's if not $10,000's a day in FB ads. I can confirm we've all known this for quite a long time.

Our general rule is if the product doesn't have broad appeal, you don't run it on FB.

My running theory on all ad networks is pretty simple. There are a very small subset of users, 25%-30%, of people who are regular purchasers and these companies know that based on conversion data. They generally just throw your ad in front of these people and let it ride.