If they know we have savings. They’ll just increase prices again to take them.

Social/Mobile games. So an already predatory industry. Let’s get people addicted to a game, and then suck as much money from them as possible.

In the industry, we definitely weren’t the only ones doing it. And really we were only doing basic stuff (it was all in house developed middleware, so effort vs reward didn’t make much sense to go hard) I wouldn’t be surprised if others were going deep.

• the hardest part is getting someone to part with their money. But once they’ve done it once, even for the smallest amount, the second purchase will be easier.
• conversions that stopped playing got emails with discounts.
• whales got freebies when they lost to keep them happy.
• everything else was just finding the customers perfect price.
• ultimately we were selling noting. So any sale is better than no sale. You can’t make a loss on a number in a database.

Everything was broken down into campaigns (we’d have multiple running at any one time) targeting different segments. Then we’d track the conversion, sale, and retention numbers of those campaigns against each other. Sometimes one campaign might flop for one segment but not another, so we’d retarget with a new one.

I don’t think it’s used much in other markets. I know Twilio has Segment, that could be used to do segmented pricing but I’ve never really seen it done in other industries.

I wouldn’t say it’s jaded me. It has made me conscious of my data footprint. I don’t play mobile or f2p games. But I am weary. The COVID greed-flation showed the mindset of businesses. It might not be long until targeted pricing becomes worthwhile to make number go up (still), and hidden under the guise of “lowering prices”.

You don’t need a monopoly for this to be a problem.

Databrokers can offer data sets of “customer price elasticity”. Tables of “how much we think X would spend on these generic item categories”. Eg “booly would pay $15 for a burger, vs $10 average”

Point of Sale systems could start offering integrations to these data sets.

All shops have to do now is set a list price, a minimum price, a category, and leave it up to the PoS to (not) give discounts.

You want a burger, you’re fed a single-use short lived discount “$5 off a $20 burger. Today only” While someone else gets “buy one get one free”.

It’s then a ‘fair’ market. Shops have and ‘compete’ with their (high) list prices, data brokers compete with “excess profit” statistics (ie, how much more money above the minimum price they made). Nobody is colluding, they’re just basing discounts off external arbitrary signals.

It slowly becomes the norm to get just-in-time discounts, and the consumer gets shafted. If you’re not in the system, you’re paying more than everyone else.

(And all of this has been happening in some markets for over a decade)

In a past life I wrote the software that did this.

It’s not just about charging more when you’re desperate. It’s also things like charging you less to keep you addicted, or getting you hooked. Exploiting your emotions and behaviour to make it effective. A small loss on you now could be a long time gain for them.

Some more scenarios:

• you’ve decided to quit alcohol. Your social media accounts are used to identify you’re looking for advice. They advertise more, and send you heavy, heavy discounts a few days in to keep you on the wagon.
• Your cars insurance tracker has picked up your erratic driving. Your phone has tracked more forceful interactions, your works email provider has revealed you’ve been in a minimum of three meetings all day; You’re having a shit, stressful, day. They can’t give you discounts on your cigarettes but they do know they can get you to buy two packs instead of one by serving you ads that suggest stock levels are low. You buy two and chain smoke all day, your daily average goes from 0.5 to 0.7 packs a day.
• You go to a chain restaurant often. They know they can get you to buy more in the long run if they increase the volume you eat gradually. Every visit they goad you into buying more. Didn’t do it last time? Steeper discounts next time. Until one day you buy the extra side. That’s now your new baseline. A few weeks of that and back onto the stair climb. A little by little. You’re spending more and more.
• you’re on holiday. everyone knows you’re not coming back anytime soon so they charge full price. But move to a new city? Everyone has discounts for you to get you in the door.

The data available back then was pretty minimal, effectively only the data we generated. But it was still enough to prey on your lizard brain. With data brokerage I’ve got no idea what level of evils we could have done.

Explain what you want. It’s that easy.

I did many years of “I want something simple that I can maintain easily, and will still look ok when I drag my ass out of bed at 10am, an hour late for work. Anything but a buzz cut”

Eventually I found something that I can touch up at home myself, and can explain to even the shittiest of barbers.

It’s hair. Nobody really gives a shit. You’ll get some shit ones, some good ones, a buzz cut you explicitly didn’t want. Nobody got hurt, and it grows back.

Doesn’t stop them opening up as “Hungry Janet” or something.

Burger King opened as Hungry Jacks in (Queensland?) Australia as “Burger King” already existed. But is also now trading under the “Burger King” brand in some places.

It’s America, so the answer is probably “No”.

Do you not have consumer protection laws?

We’ve had digital price tags for decades. But you couldn’t do this in NZ. Stores are obligated to sell you a product at the price they advertise it for AND have a reasonable quantity of units at that price… you couldn’t sell 1 TV for $1.

So these systems would need to track what price you saw it at.

(Caveat: Our stores are still cunts and have been found to overcharge people)

They are also IR controlled. A lot of them have a little window on the front of the unit, and an array of transmitters in the ceiling.

Same volume, just increased length but reduced girth.

The problem occurs when house prices tumble from an influx of sales, and the 32% (In NZ) of your population that are paying their mortgage off on their primary residence are potentially plunged into negative equity on rising interest rates.

Once you’re there, you’re kind of fucked. You can sell, but you’ll still owe the bank money, so you can’t buy/downsize. You can’t even change banks. You’re a risky customer, so you get higher interest rates. All you can do is hope the market rebounds or declare bankruptcy.

So you’re risking fucking over 30% of your nation (and arguably the most productive segment of your country as they’re earning money to pay that mortgage), to appease a fraction of (as not every renter can/wants to buy. Eg, students, temporary immigrant workers etc) the 30% of renters that are being fucked over by high house prices.

Not to mention, all the renters you’ve displaced into an even more competitive rental market.

But that’s not to say the solution is to shrug your shoulders and let the landlord class continue to punch down.

It would be expensive, but you could guarantee (current) mortgages for primary residences in cases of financial hardship. Buy mortgagees out and turn the houses into state housing, renting them back to the previous owners at fair prices.

Man outraged map of Western Seaboard doesn’t contain directions to the moon.

The number 3 doesn’t exist at Valve

Ohio rolling paper France France France.

Ohio rolling paper France France France.

Could a hypothetical attacker not just get you to visit a webpage, or an image embedded in another, or even a speculatively loaded URL by your browser. Then from the v6 address of the connection, directly attack that address hoping for a misconfiguration of your router (which is probable, as most of them are in the dumbest ways)

Vs v4, where the attacker just sees either your routers IP address (and then has to hope the router has a vulnerability or a port forward) or increasingly gets the IP address of the CGNAT block which might have another 1000 routers behind it.

Unless you’re aggressively rotating through your v6 address space, you’ve now given advertisers and data brokers a pretty accurate unique identifier of you. A much more prevalent “attack” vector.

It’s a poorly worded article that (intentionally or not) ends up sowing resentment between the have nots, and have nots with a family home. (As opposed the haves, with a rental portfolio, holiday home overseas, trust funds, etc)

Makes the boogeyman the people that are seen, the peers in (relative) poverty. While the actual boogeyman can hide away out of sight. Be it overseas land barons, corporate landlords, or just straight up wealthy living in their large secluded properties.

Nah we want you to start all your fucking about, get any beverage or condiments you might want, wash your hands, and have everyone at the table ready to eat when the food is ready.

And subsequently, not get any criticism while we’ve finished our meal and you’ve just sat down because you had to go to the garage to get a new bottle of OJ, pee that became a poop, wash your hands, and find the sauce you’ve suddenly decided to dig out from the back of the pantry.

CGNAT is good. One more layer of obfuscation between me and the internet.

Sucks for those wanting to run services from home I guess.

If you still do the sizing (it’s not entirely wasted as it’s a reasonably effective tool to gauge understanding across the team), This can still be done without the artificial time boxing.

“How much work have we done in the last two weeks?” Just look at all the stories closed in the last two weeks. Easy.

“When will X be delivered?” Look at X and all its dependencies, add up all the points, and guesstimate the time equivalence.

Kanban isn’t a free for all, you still need structure and some planning. But you take most of that away from the do-ers and let them do what they do best… do.

Israel better start to follow the Geneva convention and start building particle accelerators under their cities.