marketingtech

I'd argue it's not "just business" when a government intervenes (rightly or wrongly) in a free market outcome.

The "forced sale" aspect is strange to me.

I can understand if the CMA could apply stipulations to the deal to address their concerns like "You must offer an API to other platforms that matches your internal usage."

But Giphy is a money-losing company that can't exist independently any longer. Forcing a sale to another company/investor when they have zero leverage is a negative outcome for the Giphy team and product.

I would imagine most of these investments will go to three places:

* Sales - start generating revenue from all these eyeballs, leveraging your interest graph for targeting. this requires way more headcount than you'd expect, especially to chase enough revenue to justify a $10b valuation

* Safety - beyond all the well-discussed dangers of large-scale user forums, this also impacts monetization. you don't want to subject the average new user to extreme/alt/adult content (though you can still offer space for those communities) or else you may scare them off. major advertisers want "brand safety" and want to avoid being associated with upsetting or even mildly profane content

* Regulatory - dozens of countries and states are rolling out unique regulations around privacy, data usage, and user rights. this is a nightmare to navigate from both a product and legal sense

> The years prior to 2010 or whenever they jumped into advertising would argue "You're wrong, Facebook."

For better and for worse, we've seen pretty significant shifts in advertising over the last decade that has led to the collapse of brand names' domination over certain categories.

There are over 1 million tiny ecommerce businesses on Shopify that could never afford or rationalize a mass-market TV, print, or radio commercial but they can still be generate meaningful profits with only $100 worth of digital ads that are delivered to the right people.

It's undeniable that small businesses are benefiting from these types of ads, though you're welcome to question the macro-economic implications of that.

This would probably have the opposite effect of what you're looking for. You'd penalize non-targeted ads, which require a larger spend to be effective.

Personalized ads are ultimately cheaper than non-targeted ads because you don't need to buy as many impressions to hit the audience that you're looking for.

Per the latest earnings release on https://investor.fb.com on July 28:

* Facebook daily active users (DAUs) – DAUs were 1.91 billion on average for June 2021, an increase of 7% year-over-year.

* Facebook monthly active users (MAUs) – MAUs were 2.90 billion as of June 30, 2021, an increase of 7% year-over-year.

* Family daily active people (DAP) – DAP was 2.76 billion on average for June 2021, an increase of 12% year-over-year.

* Family monthly active people (MAP) – MAP was 3.51 billion as of June 30, 2021, an increase of 12% year-over-year.

It's hard to show large growth rates when you already count most of the +16, non-Chinese internet population as your users, but it doesn't look like an apex.

You're also granting the extension access to your friends' data, given that it can see everything that you can. Your friends consented to show that data to you, but not to the extension developer. Your friends' consent is not transitive.

There's growing evidence that large media companies can generate revenue from advertising deals from large brands with high-level interest targeting.

That doesn't say anything about the performance of targeted ads - just that high-level targeting is a suitable replacement for narrow targeting at a certain scale.

That's a separate concern from niche publishers (without direct sales teams) and niche brands (who only have a few thousand dollars to spend on marketing) who both want to maximize the value they're getting from the ecosystem.

And that's where the real money in advertising is. Fortune 500 companies boycotted FB last year and it didn't make a dent in their revenue, because they have millions of small businesses that all spend $50 on ads per month. That level of spending is only effective with narrow targeting.

You're also granting the extension access to your friends' data, given that it can see everything that you can. Your friends consented to show that data to you, but not to the extension developer. Your friends' consent is not transitive.

University researchers get Facebook users to install a plugin that exfiltrates their data and their friends' data from the platform.

Besides leveraging a browser plugin for scraping rather than FB's official APIs, how is this different from Cambridge Analytica? And didn't most people want Facebook to fight back harder against that behavior?

It's easy to mock the pettiness of all parties described here, and it's common for people on this forum to take absolutist stances with regards to privacy/advertising, but it's also important to recognize that these arguments will actually define the future of the internet for the average user.

There are trillion dollar companies on both sides of the argument, and their eventual compromise will establish the defaults for billions of users.

There are also two fundamental components of the Big Tech debate at odds with each other here - privacy and competition. Increasing privacy decreases competition by strengthening the Big Tech companies that engage with users at the platform/browser/OS/hardware level. See: Google's removal of third-party cookies from Chrome in the name of privacy was just blocked by EU competition regulators, because it would cripple competing advertising companies[1].

[1] https://arstechnica.com/tech-policy/2021/06/eu-antitrust-reg...

HN discussions where people thought this story was real: 2019 - https://news.ycombinator.com/item?id=20227175 2021 - https://news.ycombinator.com/item?id=25510351

By creating an under-13 product and making active attempts to remove them from the 13+ product, they can push to raise the bar on COPPA and other regulations.

Imagine if governments cracked down on Snapchat and TikTok for not doing enough to keep under-13 users off their apps.

"Instagram and Messenger are setting such great examples for child safety and data protection, while these other apps are endangering our youth and capturing personal data from underage users. Won't somebody think of the children?"

Last quarter, they made $9.27 per user[1, slide 4], however that's not evenly distributed. They made $48 per user in US and Canada. But even that isn't evenly distributed.

The users who are likely to pay for the subscription are also the most valuable to advertiser because they have disposable income. Some Facebook users see ads for luxury cars, real estate, and vacations, while other users see ads for dollar stores and dropshipped junk. FB earns much more in their auction from that first set of users, but those will be the first users willing to pay to opt out of ads.

Dynamic pricing would probably offend both audiences - "what do you mean the algorithm thinks I'm worthless?" "what do you mean that I'm worth thousands of dollars to you?"

[1] https://s21.q4cdn.com/399680738/files/doc_financials/2021/FB...

That's an interesting question, but it doesn't accurately describe the collection/transfer of data as far as FB or Google are concerned.

Millions of websites/apps/stores willingly deliver this information to Facebook/Google for free, and it's your relationship with each of those websites/apps/stores that governs the collection and sharing of that data.

GDPR, for instance, makes a distinction between "data controllers" and "data processors." The businesses are the controllers, and FB/Google are processors. Both have responsibilities regarding the handling of your data, but most of the requirements fall on the controller. The processors are able to assume that the controller had the right to share the data with them.

Facebook uses a second price auction. Google does not.

https://www.adexchanger.com/online-advertising/google-switch...

Google operates one of the largest exchanges for advertising - ad sellers place their inventory up for auction using Google tools and each integrated ad network can place a single blind bid to try to buy the inventory.

The catch is that Google operates their own ad network and can leverage their visibility into the exchange to be only bidder who is not blind.

For any given inventory, Google can wait for every ad network to submit their bid and then make a decision as to whether or not they should place the highest bid to win the auction.

The information asymmetry allows Google to bid more efficiently - if they're prepared to bid $5 but they know everyone else is bidding $1, they'll lower their bid to $1.01.

Apple is the company that declared this the canonical Public Suffix List. Facebook is just directing their customers towards it. "If you need to be considered a public suffix for Apple's new policy, you'll need to send your pull request to this repo."

This is fascinating to see Apple and Facebook engineers politely yet publicly arguing over potential technical implementations of Apple's privacy policies.

This is a result of Apple limiting the entropy of marketing data that can be received from a domain (defined as an eTLD+1) to 6 bits.

This causes problems for platforms like Shopify or marketplaces like Alibaba or eBay that may have multiple sellers trying to run ads on a domain and competing for the same small pool of entropy.

This solution? Leverage the "public suffix" list to define your domain as an eTLD and give every seller a separate subdomain so that everyone gets their own data entropy namespace.

Now every hosting provider or online marketplace is scrambling to re-architect their site into subdomains with public suffixes to maintain the status quo.

They use the term "dark patterns" in the press release, but the actual regulation is very specific, straightforward, and limited to the "Do Not Sell My Personal Information" link that's required by the California Consumer Privacy Act.

  The notice of right to opt-out shall be designed and presented in a way that is easy to read and understandable to consumers. The notice shall:
  a. Use plain, straightforward language and avoid technical or legal jargon.
  b. Use a format that draws the consumer’s attention to the notice and makes the notice readable, including on smaller screens, if applicable.
  c. Be available in the languages in which the business in its ordinary course provides contracts, disclaimers, sale announcements, and other information to consumers in California.
  d. Be reasonably accessible to consumers with disabilities. For notices provided online, the business shall follow generally recognized industry standards, such as the Web Content Accessibility Guidelines, version 2.1 of June 5, 2018, from the World Wide Web Consortium, incorporated herein by reference. In other contexts, the business shall provide information on how a consumer with a disability may access the notice in an alternative format.

source: https://oag.ca.gov/system/files/attachments/press-docs/CCPA%...

It sounds like you're referring to the sell-side of advertising (i.e. a publisher running ads on their site).

I'm referring to the buy-side of advertising (i.e. an ecomm business running a marketing campaign). Each task could be "Tell Google that person 123 visited landing page X." or "Tell Facebook that person 456 purchased a tshirt." This lets you create targeting segments on the platforms and measure the results of your campaigns.

In that situation, the third-party that is actively collecting and transmitting the data becomes a controller and is subject to regulation.

Under the predominant data transfer model, the third-parties cede responsibility by making the data transfer an active behavior by businesses. Ad tech companies can say "We didn't actively collect the data from customers - we passively received it from businesses." That makes a huge difference in term of regulatory compliance.

That said, this has been the most common data transfer model for years. "Data hoovering" is a misconception that allows millions of businesses who actively send customer data to Google/FB to shift privacy criticism onto the platforms.

It's incredibly cheap in the context of 6 or 7 figure marketing budgets. It gets budgeted as a new compliance cost to continue doing business as normal even after Apple, Mozilla, and Google block advertising pixels from their browsers.

If you have 100k transactions or even landing page views per month, $599 is going to be the cheapest part of your advertising stack.

There's a distinction between being a data controller and a data processor.

The businesses that use these platforms are the data *controllers* and are responsible for implementing consent, "do not sell my information", "show me my data", or "delete my data" flows as required by law. The platforms generally offer APIs to implement these required data flows in a centralized way, which is another major value prop for them.

The platforms serve as the data *processor* and can assume the data is compliantly obtained by the controller until informed otherwise.

Zapier joins Tealium and Segment on the list of billion dollar valuations for powering the next generation of ad tech.

As cross-site cookies and browser pixels are increasingly blocked, ad platforms are moving from browser-based tracking to server-side data transfer.

Like those other companies, Zapier provides a single integration point that funnels user and conversion data to dozens of marketing companies' server-side APIs. A few clicks allow you to transfer your customer data to/from hundreds of different platforms.

Statistically speaking, you're more likely to buy a second object right after you bought one than someone who has not shown interest in the product. Things break, you might want to return it for a slightly different version, you might buy one for a friend.

For you, it might be wrong, but when the advertiser is buying millions of ad impressions and is looking for a 0.01% hit rate, the math shows that you're one of the more likely future customers.

Right now, that's extremely difficult to do without leaking private data. Google and Facebook experimented with it for a while, but both killed the test products because it would require them to trust advertisers with data that could easily be de-anonymized. It's kind of a funny twist that Google and Facebook are able to avoid offering this in the name of user privacy, while the advertising industry is begging them to share more user data.

That said, they're all part of an industry consortium that's working on differential privacy algorithms that will ideally allow businesses to check each other's attribution without actually sharing the personal data involved. https://developers.googleblog.com/2019/09/enabling-developer...

Page Like ads are the least ROI effective ads on Facebook. You tell their machine learning algorithm to optimize for people who will click "Like" on every page they see. That'll increase your vanity metric and meet your stated objective, but it doesn't drive business results for you because you're getting the wrong type of customer.

If you tell Facebook's machine learning algorithm to optimize towards purchases on your website or visits to your stores or to users onboarding to your app, then you'll really see the power of their beast. Those are the ads that people are spending billions of dollars on, because the outcomes drive real business value and have too much friction to be faked at scale.