Sam Profile picture
Sep 15, 2020 3 tweets 2 min read Read on X
A3: Always - but as with anything, it's a cost/benefit analysis. It's a question of understanding what channels are contributing positively to the business, as well as the risk profiles associated with each. I expect October/November to be pretty bad + BF/CM to be $$$$ #ppcchat
A3.1: I think I have the most direct concern with the FB/IG + Twitter ecosystems; but the most indirect/2nd order concern with Google, Snap + YT.

Basically I think some advertisers are going to run from FB/IG/TW, but that $ needs to go somewhere.

#ppcchat
A3.2: The most logical place for it to go is G, YT + Snap/TikTok* - so the economics of those platforms could get hit pretty hard, which creates a really interesting (read: awful) situation for brands between advertising in hell (i.e. FB/IG/TW) and doing nothing #ppcchat

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More from @DigitalSamIAm

May 8
There's a lot of discourse on here (and on LI) about AI companies "stealing" copyrighted materials for training.

There are - fundamentally - two different issues at play. The fact that most conversations conflate them creates more problems.
The first issue is the use of publicly- available data to train models.

The second (and more serious) is companies using LLMs to unbundle content from creators (people, businesses, organizations, whatever) in a way that could cause real harm.
Issue #1: Training Data -- LLMs are trained on vast amounts of data, ranging from patent filings and old novels to newspaper articles, blogs, reviews, forum content, encyclopedias, etc.

This content is used by the LLM to generate patterns.
Read 29 tweets
Jan 9
There's a lot of commotion, confusion and fear about Google's removal of 3P cookies + what that means for advertisers.

Much of this is unwarranted and ridiculous:
First, there's a misconception that the removal of 3P cookies from chrome somehow impacts Google's data (1P cookies) - nope.

This will impact many third-party services, from smaller (relative to Google/Meta/Apple) ad platforms, to attribution platforms, to certain UI/UX platforms, to other website service providers (basically - any third party that uses a pixel/tracking tag).
Whenever major changes occur, there are winners & losers.

I view this as an overwhelming positive for Meta, Google, Amazon & Apple.

It is an overwhelming positive for marketers.

It is likely a massive win for most users, who will get better, faster, cleaner web and ad experiences.

It is a massive negative for parasitic data leeches, along with the brands that rely on their less-than-optimal 3P data for marketing, to the exclusion of building 0P/1P audiences.

It is a massive negative for publishers + brands who have not invested in building their 0P/1P data capabilities.
Read 10 tweets
Aug 15, 2023
Just spent some time playing around with the Google Demand Gen Beta. Initial reactions & takeaways:
1. RIP Discovery - I've long been a big fan of discovery campaigns, though DG appears to be a level-up from existing Discovery for 4 reasons:

(1) Inclusion of YT placements
(2) ML-driven targeting options (similar to Meta)
(3) Ability to create LALs
(4) Standard Bidding Strats
2. Lookalike Segments - I love a good Lookalike. Done well, it jump-starts machine learning + helps reduce wasted/unproductive spend. This is a HUGE benefit to organizations that have invested in their zero-party data infrastructure.

samtomlinson.me/insights/zero-…
Read 10 tweets
Dec 5, 2022
Google Ads is an area where brands invest heavily, all with little-to-no transparency on what that investment is returning. I've done 100+ audits covering hundreds of millions in spend - and here are the 10 things that result in suboptimal outcomes (+ lots of wasted $$$)👇
"Let's break this down into five core buckets -

1. Strategy & Research
2. Account & Campaign Structure
3. Data Flows
4. Creative & Landers
5. Management

High performance in each of these areas is *essential* if your goal is to build + maintain a highly profitable account."
Strategy & Research

In roughly ~90% of audits, the biggest failures are NOT a result of tactical mistakes; they are a result of strategic failures. Just as a house built on a crappy foundation will fail, so too will a Google Ads account built on a flawed strategy
Read 33 tweets
Dec 17, 2020
So #MarketingTwitter you've heard about the big scary antitrust case against Google that was brought by a bunch of states you wouldn't expect to be suing big business (TX, KY, AK, ID, IN, MI, MS, ND, SD, UT) + wondering what's it all about, here are some (preliminary) thoughts:
(Disclaimer: I have no idea how long this thread is going to go so :shrug: and stop reading whenever you get bored)

2/x
From a high-level, the case is primarily focused on a vulnerability for Google (AdX), with some (IMO) stupid digressions around search market share and an illicit agreement with Facebook to cripple header bidding. In that sense, it's a case that has some merit.

3/x
Read 70 tweets
Oct 5, 2020
@NeptuneMoon I don't know if I'm an "expert" -- but as someone who worked in finance + now does lots of digital things, this is a really, really dumb take, for (at least) 5-6 reasons:

Thread time, because I want to procrastinate and way too many people don't understand how MBS or ABS work.
@NeptuneMoon Reason #1 - MBS issues resulted in a systemic failure due to a heinous combination of securitatization, proliferation of CDOs, deregulation, fraud + general stupidity (simplified).

The *combination* is what allowed the situation to go from an isolated bad to a global really bad.
@NeptuneMoon As I understand it, Hwang's argument is (basically):
1. online advertising doesn't deliver the value it claims
2. but people keep buying it, so prices keep going up
3. lots of companies rely on it for $$$
4. so if people figure out (1) + stop (2), then BOOM.
Read 21 tweets

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