Category: Wisdom

Introduction

One of the most click-baitey articles that travel bloggers write is: “What is [Airline] Status Worth? [Year] Edition”. I’m sick of seeing these articles, so I decided it was time to come up with the equivalent of the Drake equation, but for airline status because that’s apparently the best I can do with my life, and also it marks the first time that my astrophysics training has a real world application (except not really, see below).

Background

The Drake equation calculates the probability of finding alien life, provided that you’re willing to make a bunch of hand-wavey assumptions and then plug them into a formula. This, it turns out, is exactly what those “What is [Airline] Status Worth?” articles do too, except they calculate a dollar amount instead of probability.

So, in an attempt to make “the one airline status value formula to rule them all”, let’s, shall we say, go.

The Status Equation

\$V_{status} = n_{phone}
 ⋅RH+n_{UI}
 ⋅UI+BM+n_{FPS}​	
 ⋅FPS+n_{up} 
 ⋅FU+BT+ANC+ SSW

Where:

  • nphone = The number of times you’ll make a call to the airline
  • RH = The value of reduced hold time
  • nUI = The number of upgrade instruments you’ll earn and use
  • UI = The value of an upgrade instrument
  • BM = Bonus redeemable miles you’ll earn for holding status
  • nFPS = The number of free priority assigned seats you’ll get
  • FPS = The value of a free priority assigned seat
  • nup = The number of times you’ll be upgraded
  • FU = The value of a free upgrade (unironically abbreviated, I promise)
  • BT = The value of your elite brag tags, you know, like this
  • ANC = The value of ancillary benefits, like rental car status (that you probably already get from a credit card)
  • SSW = The value of your increased sense of self worth for holding elite status

So, just like the drake up equation, make up a bunch of numbers for what could happen and you’ll come up with the dollar value of your status. For example, I decided that my AA Executive Platinum Status is worth $3,430, but that’s mostly because of SSW. Remove that, and it’s probably worth $500.

Have a nice Thursday friends!

What’s the additional value of being served in a Delta branded cup on an AA flight? Science still doesn’t know.

Background

Loops in churning are powerful because you can stack earnings as a dollar flows from a credit card, to a FinTech, to another, to yet another, and eventually (hopefully) back to your bank account to pay off your credit card. Instead of earning 3x on a single purchase, a loop might push the net earnings on that purchase well above 3x.

But if it’s good once, isn’t it better multiple times? Yes, but as you scale those loops across multiple cards, multiple players, and multiple charges in flight, tracking becomes a non-trivial load. Imagine keeping track of the following every day, knowing that any step in the chain might have a failure that needs manual intervention:

  • Buy a $499.51 sportsbook gift card
  • Load the sportsbook gift card into a FinTech account intermediary
  • Load the FinTech account’s funds into a sportsbook
  • Play through at least $499.51 in funds
  • Withdraw the $499.51±(profit/loss) into a FinTech’s rewards account
  • Use the FinTech’s platform to pay your credit card

Great! Now do that again 10 times per player, for 15 players, each with different initial gift card amounts for tracking, every day. Also, don’t forget to run your other plays that aren’t sportsbook related for the day too. Finally make sure you haven’t lost something along the way; I hope you’re good at Excel, Beancount, SQL, or something else to track it.

The Brick Wall

Some of the best churners I’ve met eventually take a few months or more off because tracking takes time, dealing with sludge when something goes wrong takes time, frozen accounts take time, and in net the mental load can push them to hit a brick wall and burnout.

Once you’ve burned out and stop manufactured spend, you earn exactly $0 per day, $0 per week, and since America Loves Math™, $0 per month too.

The Lesson

A loop can turn 3x earning into 6x, but too much looping and tracking can eventually turn into burnout which earns 0x. So, don’t forget simplicity and don’t be afraid to skip most of the steps in a loop to keep yourself sane when the world comes running at you.

Happy Wednesday!

Counterpoint: Sometimes brick walls are fake.

Sometimes the path a dollar takes through a loop during advanced manufactured spend is staggering; As a semi-real world hypothetical, a manufactured spender might loop money around with a recipe like:

  1. Run a charge with credit card on a fintech (earn on spend, perhaps pay a load fee)
  2. Use a fintech virtual card to load another fintech (earn on spend, perhaps pay a load fee)
  3. ACH out of the second fintech into a bank with a rewards debit (no earn or fee)
  4. Pay the original credit card with your rewards debit (earn on spend, perhaps pay a payment fee)

Most of those steps have an earn component, and most have a fee component too. Calculating your total earn is really just a matter of adding all the earn and subtracting all the fees, and the goal is that the entire loop earns a nice spread.

Once you’ve developed a money loop like this, it’s easy to think of all spend fitting into the loop in someway.

But, and here’s the point of today’s article:

Sometimes skipping the middle steps earns just as much as the loop you’ve developed, or maybe earns slightly less but loops faster. Sometimes simplicity wins.

Have a nice weekend!

Simplicity can go too far, or sometimes not too far enough; which one is this churner’s house?

Introduction

Alaska and Hawaiian may merge. If that happens, Hawaiian miles will transform into Alaska MileagePlan miles in a way that “preserve[s] the value of HawaiianMiles at a one-to-one ratio“. This has a bunch of people excited because:

  • Alaska MileagePlan miles are hard to earn
  • HawaiianMiles are easy to earn via American Express Membership Rewards

Alaska MileagePlan miles are valuable partially because Alaska is smaller than the big four major US airlines, and partially because again, they’re hard to earn. HawaiianMiles aren’t worth much relative to most major airline currencies, but if the merger completes then HawaiianMiles will balloon in value overnight.

The Play

Of course, gamers gonna game, and the opportunity to turn low value, easy to earn miles into more valuable miles is an obvious and attractive play. In fact, I’ll be running this play; I too like turning low value things into high value things just as much as the next churner.

The Scale

How big should you go? There are risks to going too big, namely:

On the first point, what’s the expectation value for a time to devaluation? I’d guess it falls between 18 months and 24 months based on past history. How bad is a devaluation? Usually, an average 30% increase in redemption cost is a reasonable upper limit.

The Answer

That brings a simple math formula to calculate how many miles to transfer: the number of miles I expect to redeem in the next 18 months, plus the number of miles to redeem in the following 18 months devalued by 30%, minus the number of miles I expect to earn in other ways.

The numbers for me, which are based completely on how many MileagePlan miles I earned and burned used over the last 18 months:

  • 0-18 month range:
    • 900,000 miles to burn
    • 800,000 miles to earn
  • 19-36 month range:
    • 900,000 miles to burn * 130% for a devaluation
    • 800,000 miles to earn

Running the math:

miles = (900,000 – 800,000 + 900,000 * 130% – 800,000 = 470,000 miles

And if I do it before the 20% Membership Rewards transfer bonus to Hawaiian ends on Sunday night:

miles = 470,000 / 1.20 = ~392,000 miles

So, 392,000 Membership Rewards transferred will cover me (probably) for the next 36 months. Very mindful, very demure, very cutesy. But, what about travel past 36 months from now, you ask? I guarantee my situation, the US airline situation, airline transfer partners, airline alliances, and my travel needs will be different in 36 months, and speculation beyond that timeframe is at best a guessing game, especially since an unredeemed point is worth zero.

Happy transfers friends!

Alaska’s new 2026 alliance announcement.

A balancing act that we frequently face in manufactured spend and churning is knowing how hard to hit a deal. If you push it too hard, you may kill it in days. If you don’t hit it hard enough, you’re leaving money on the table – potentially a lot.

What’s the magic behind how hard you should hit a deal and when you should back off? In my mind it comes back to two fundamental questions:

  • Who’s paying for your earnings?
  • What metrics, compliance, and regulations are important to them?

If you can answer those two questions then you’ve got a guide for how much abuse a deal will tolerate. If, for example, you’re dealing with a small, local casino’s loyalty program that’s relentlessly focused on bringing in gamblers, you can bet that they’ll know pretty quickly if they start paying out a ton of rewards due to your shenanigans. So, I’d treat such a thing as a short, surgical strike and try and run the deal low and slow over months or years.

On the other hand, if you’re dealing with a dinosaur bank that has disconnected legacy systems and trillions of dollars in assets, your debit card funding would probably have to get well into seven or eight figures before it showed up as a blip on anyone’s KPI dashboard, and on top of that they’d have to be curious enough when they see it to dig in and figure out what’s going on. So, this one is a probably a pedal to the metal play, understanding that time and not volume will probably make the deal die.

So, an unsolicited suggestion: When you encounter a new deal, think about who is paying for it and what their regulations are as a guidepost.

Good luck!

Sample bank KPI shenanigan finder.

EDITOR’S NOTE: If the math formula doesn’t render correctly in your reader, check the website at this link.

Introduction

In advantage play (gambling with an edge over the house), the Kelly Criterion or Kelly Formula gives a simple calculation for the best amount to bet to maximize earnings. We can draw an analog for resellers, whether it’s the buyer’s group kind or the gift card arbitrage kind.

The Propeller Head Part

The generalized Kelly formula, rewriting a bit to express terms familiar to resellers, is:

\%_{float} = \frac{(1-p_{loss})}{\%_{loss}} - \frac{p_{loss}}{\%_{gain}}

Where:

  • %float = The percentage of your budget to float
  • ploss = The probability that you’re going to lose your profit
  • %loss = The percentage you’ll lose if a loss happens
  • %gain= The percentage you’ll gain if you don’t lose

A Simple and Specific Example

Let’s look at Pepper, which may or may not pull the rug out from under you at any point in the next year. With Pepper, you’re probably earning about 3.9% from your credit card (4x Membership Rewards, worth 4.4% cash back, times 90% due to Pepper’s convoluted redemption). Assuming your buy rate equals your sell rate after rewards are paid out (buy at 90%, sell at 90%), then we’ve got a simple calculation:

  • ploss = 10% (pick your own number here, but let’s say there’s a 1 out of 10 chance of Pepper failure)
  • %loss = 10% (worst case you lose all of the discount Pepper gives)
  • %gain= 3.9% (the percentage you’ll gain if you don’t lose, in this case Membership Rewards)

Then run the numbers and get:

  • %float = (1-0.10)/0.10 – 0.10/0.039 = 644% (when probability of loss = 10%)

What the hell, you might ask? Why is that number over 100%, and how do I invest that much? Well, the answer is either (1) you should float all of your bank roll to maximize profit because you’re much more likely to win than lose, or (2) you need 5.44 other players to help you.

Increasing the Chance of Failure

What if you think there’s a 30% chance of Pepper failure though? The calculation is again simple:

  • %float = (1-0.30)/0.10 – 0.30/0.039 = -692% (when probability of loss = 30%)

What the double hell, you might ask? Why is that number over 100% and also negative? The formula is telling you that if you think Pepper’s got a 30% chance of failure in the next 30 days, you shouldn’t invest anything; “kill it with fire” says the formula.

Finding the Middle Ground

So, what’s the cut-off at which the formula switches from LFG to hells-to-the-no? I’ll spare you the algebra, but it’s easy to find by setting %float=0 and solving for ploss. Doing that gives:

  • ploss (cutoff point) = 0.2806 = 28.06%

In other words, if you think Pepper is < 28% likely to fail before you can cash out your rewards, you’ll maximize your profits by playing the resell game. If you think Pepper is ≥ 28% likely to fail, stay away. (I generated a boring graph illustrating how float percentage varies with the probability of loss for turbo-nerds here).

Conclusion

The Kelly criterion is surprisingly insensitive for churning problems, switching from above 100% (1.0) to below 0 very quickly. But, if you’re 3/4 certain that Pepper isn’t going to fail before your rewards are paid out, keep going.

Special thanks to John Reeder for poking me on the subject, and another special thanks to John for the idea for a follow-up piece on the subject: what if you know they’re gonna steal your money, but not when? Stay tuned, or, like yesterday, don’t; you do you.

Another helpful MEAB plot.

EDITOR’S NOTE: If you’re viewing this on a platform that doesn’t properly render the math formulas, pivot to the website for this article.

Introduction

When calculating the cash value of points redeemed for a free night at a hotel, a surprising number of blogs ignore the parking fees and resort fees charged by most programs. That disingenuously inflates the value of a hotel point, unless you’re able to talk your way out of a resort fee and you can get to the hotel without a vehicle.

Fees on Award Stays in Major Programs

Let’s interlude with a quick refresher on major programs’ rules about fees on award stays:

  • Hilton: no resort fees on points redemptions, but parking charged
  • Hyatt: no resort fees on points redemptions, parking may be charged depending on elite status
  • Marriott: resort fees and parking charged
  • Choice: resort fees and parking charged
  • Best Western: resort fees and parking charged
  • IHG: resort fees and parking charged

Calculating Cents per Point

Taken at face value, you’ve effectively got a cash co-payment on award redemptions in the form of fees with most major loyalty programs, which reduces the value of your points. The naive formula that you’ll typically see for cpp (cents-per-point) is:

cpp = \frac{rate*100}{points}

But, the total cash value of your stay is the nightly rate plus fees, not just the nightly rate. And as a result, we ought to include resort fees and parking in that valuation. Let’s introduce a MEAB reduced comparative value cv, which is a reduced overall cents per point that takes fees into account for redemptions:

cv_{meab} = \frac{(rate-fees)*100}{points}

Looking at the JW Marriott Austin for a concrete example: For a Saturday night, one-night stay in the cheapest room, the cash price next weekend is $235, plus a $25 destination fee, plus a $54 self-park fee. An award night for the same room on the same weekend is 43,000 Bonvoy points. That means we’re getting a reduced MEAB comparative value (cv) of:

cv_{meab} = \frac{(\$235-\$25-\$54)*100}{43,000} = 0.36

That works out to a whopping reduced comparative value of 0.36 cents per point, which is bad even by Marriott standards. Side note: If you instead booked this Marriott stay via the Chase Ultimate Rewards portal with a Sapphire Reserve, the $25 resort fee would be included in the cash rate and you’d end up paying 17,333 points and $54 for parking, instead of 40,000 Bonvoy points and $79 in fees. Remember this example when you’re looking the Ultimate Rewards 70% transfer bonus to Bonvoy.

So What?

Looking at reduced value comparative calculations lets you compare currencies across different programs in a more genuine and equitable way. The results aren’t always pretty, but they do make Hyatt and Hilton look better than other programs ceteris paribus.

Happy Tuesday friends!

Don’t worry friends, there’s always something more at MEAB.

In sales, computing, and likely a dozen other disciplines, there are two commonly accepted types of scale:

  • Vertical, which means making a single thing do more
  • Horizontal, which means using more things to do more

A simple example for a rideshare business owner is: do you buy a school bus or more cars to move more people, and nearly as important, does your business earn 10x on a Sapphire Reserve?

In manufactured spend, scaling is possible in both ways:

  • Vertical MS: Open more cards, visit more grocery stores, run bigger charges
  • Horizontal MS: Using more accounts, usually with more players

There’s a third type of scale for manufactured spenders too, which is often a great way to make fintechs go further, and that’s what we’re going to call diagonal scale because reasons. Examples of diagonal scale:

  • Multiple players, each with multiple phones
  • Multiple players, each with 99 employee cards
  • Multiple players, each with multiple virtual assistants
  • Multiple players, each with multiple FinTech accounts
  • Multiple players, each of whom calls the CEO simultaneously, collectively known as a basket of Jimmys

For scale, always go diagonal, and remember, a bunch of diagonals = a plaid, and a plaid = a FinTech (we’ve gone full circle friends; now, we just need another square geometry joke or two. Oh wait, we definitely don’t need that.)

Manufactured spenders going plaid.