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What about just plain old query() SQL i usually find the easiest vs. mucking around with pivot tables.

SQL is fine if you don't want to play with the data interactively - but that's the real benefit of Pivot Tables.

Things like drilling through, filtering/slicing, and then generating a graph, all in SaaS without having to run anything local.


Yes exactly, excel's Pivot tables and charts are more powerful.

His work is always a good reminder the open web is still an amazing place!


requiring a telephone contact (SMS verification or code from robocall) would provide enough sufficiency in scaring the perps to probably solve 90%+ of these.


It seems pretty clear that's what you get when you use the campaign? https://support.google.com/googleplay/android-developer/answ...

"After you make an app or game available for pre-registration, users can visit your store listing to learn about and pre-register for your new app or game.

Then, when you publish your app or game later, all pre-registered users will receive a push notification from Google Play to install it.

Eligible devices will also have the app or game auto installed on the day it launches. (more details on this in documentation)


I don't know anything about app releases, and I'm sure something like this is important to get an app into trending lists.

However I'm a bit skeptical that auto-downloads would even really be better for a free app. If the user isn't willing to accept a notification to install an app, they probably aren't going to use the app if it just auto-downloaded.

Also this just seems like a very weird app to have pre-registration ads for. If a user is looking for a "meal planner" app they obviously aren't going to just wait 2.5 months for your app (which doesn't seem particularly unique) to come out. They're going to download and try other apps that are actually available during that time.

It still seems like a rip-off though.


If you look at the first screenshot in the article it shows what the pre-registration page looks like.

It says:

Perks of pre-registering

- Automatic install

Install automatically when it's available


>If you choose to make your app eligible for auto install, Play can deliver your app to users’ devices automatically on launch day (if they’ve opted in).

It's up to the users.


And you need to still do quite a lot of leg work getting users to opt in. With the recent death of the Reddit API my favored client is being adapted to Lemmy - but the news of that happening only reached me because I was following the news on their subreddit before the shutoff. Pre-registration feels like a huge waste unless your users are literally chomping at the bit.

Users install a whole bunch of apps on their phone when looking for a solution to a problem and a fair few of those are never actually launched.


"Would you like to install this meal prep app in a couple of months time?" is a question I cannot imagine anyone saying yes to. Why would you? There are apps available today...


Is sending someone a push notification really worth $1 though?


Is paying $1-3 simply for a click on google ads worth it either?

(In my experience, no).


I don’t have experience but I thought Subprime Attention Crisis was an interesting read


Depends on your conversion rate and customer LTV.

Check Mesothelioma ad click rates on Google...


Yep, and what your CPA is.

LTV for a 30 yr mortgage is hundreds of thousands - that pushes for some expensive clicks at auction.


To the users who have actively indicated that they are interested in downloading your app, all at the same time on launch day, potentially putting you on some "most downloaded apps" leaderboards? Quite possibly, yes. It'd depend a lot on the app, though.


My partner made a lot of spelling mistakes, instant human tell :)


had a bot do this too


Would respectfully disagree. Matching a consumers query to an ad, and optimizing that outcome at a given return on investment threshold is a task best left to a computer to optimize. It is a perfect use case for reinforcement learning, and a computer can work 24 hours a day and you need to sleep. In my experience, 100/100 times the machine beats the confident manual optimizer. We (humans) don't have a great track record in beating computers at these kinds of problems, certainly not a game as simple as optimizing for a high score (driving results from an ad).


If the goals for all parties are the same, yes. Google is optimizing for their own fill rates and ePM, _then_ the advertiser's CPA/goals. If there are 100 equally valued conversions for $10 and 500 for $40, you would want all $10 conversions first. This is possible with manual bidding on exact match terms you know convert. With broader match types or many automated bidding strategies, you get a mix of everything (Epsilon greedy/multi-armed bandit strategy) and the CPA will almost always trend towards/exceed the $40 point.


The challenge with that approach is the variation in both (a) queries and (b) other players. (a) There are a small % of queries that are knowable for you to target on exact, or you are required to update and prune infinitely over time. [https://twitter.com/Google/status/1493681643290300425?lang=e...]. (b) A mix is better than a fixed CPA at a set price, up to to the player to pick the acceptable range. At a fixed price and many players competing for the same 100 10$ conversions, the price would quickly rise for those same conversions anyways. You're replicating the work the computer is doing, but doing so with the illusion of control.


It does require manual intervention, and the campaign strategy is typically called "alpha beta" where the beta is a broader match type, with the goal of a lower IS (via budget-- not always AP). As you state, there is in fact more competiton for these terms (for a reason) in efficient markets (both from other manual bidders and automated bidding), but it still works (many times you end up with competitors who hit their budget caps due to their other misaligned spend). In situations where the bids cause CPA to exceed target, you simply choose to lose IS due to bids and shift resources. With automated bidding, you don't always have this option. The key concept that people miss is that automated strategies optimize fill rate for Google-- so you end up with tons of longtail spend that will likely never convert and is hard to identify. Automated strategies will also abstain from auctions if they can't hit specific goals, or will have severely limited volume.

Auctions may vary-- most of my managed spend (mid 8 figures, so not huge) has been in high CPC (think $5-25) verticals like home services, movers, insurance, mortgage and mattresses (insane period from 2015-2018). I have set things up manually, let Google AEs setup the "recommended" bid strategies (and even run longer than their suggested timeframe) and utilized known agencies, and the manual bidding (always accompanied by aggressive negatives, high AP/IS goals) always won by large (30%+ lower CPA with higher volume) amounts. Performance may be drastically different in ecommerce niches where everyone is using automated strategies, as well as other factors like number of auction participants, participant budgets, sophistication and even objectives (executive spite is a valid reason-- hence Google's target outrank share strategy). Anyone who has done PLAs/shopping ads will be incredibly cynical due to their targeting methodology of being all inclusive with the onus of exclusions on the advertiser when the majority of errant spend is in the longtail-- good luck talking to 99% of marketers about tokenization, stemming and lemmatization for identifying negative matching strategies.

So yes, automated bidding can work better than just YOLO'ing some broad match campaigns, but most people shouting their praises, that I have encountered, are parroting their ad rep's talking points. Any competent performance marketer (not many) will be able to outperform automated bidding strategies, but things like scale (why bother saving 20% on 5k spend?), principal/agent problem, or workload (or being lazy, relying on salespeople to do their job) will also have an impact.


yes but "{person name} memo" is not the same as "Google Memo" (published and endorsed by the company)


> (published and endorsed by the company)

this is not implied by the name "Google memo".


I would agree with this, SWE is actually the easier role to replace with AI given the literal binary nature of the work. Dealing with humans is much more complicated, given they do not directly follow logic.


Doesn't work very well - asked for dramas shot in Hawaii and got a bunch of good comedies


> Cause of death: https://twitter.com/bettersoma

Why would any business set up shop in these conditions. Remote or not, plenty of safer & cleaner spots in America to do business.


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