Money Matters

There’s a hard truth I need to face: I am not good with money.

I did fine when I was on my own. I paid off my student loans and the car I had at the time; I started paying into a 401(k); I kept my bills modest. But whatever modicum of financial literacy I had that kept me going back then, it has not proven sufficient to the task of supporting not only myself, but a house, significant other, and pets. The 401(k) is gone; the wife’s much heftier student loans stare us down over the arm’s length of deferment; the fraction of my monthly income not consumed by bills has become a sad sliver.

The stigma of that has held me back. Mention “credit card debt” in passing on social media or in the company of successful people, and observe how quickly words like “irresponsible,” “stupid,” and “greedy” come up. It makes it hard to admit struggle, even to oneself, because that way lies the dissolution of one’s self-image as responsible, intelligent, and content.

At one layer of cynicism, it’s clear how the systems in place encourage slow-burning disaster. The declining purchase power of the dollar has made grocery trips more and more expensive despite little change in actual buying habits. The promises of prosperity from colleges, politicians, and futurists encourage optimism despite evidence for the opposite. Why bother teaching us how to stay cashflow-positive when we’re all little Zuckerbergs, each and every one on the verge of winning the American Dream lottery as reward for how smart we are? You need that house to live how you deserve, that game console to stay current with the cultural conversation. Lenders congratulate us on our payment history and raise our limits, providing more rope to hang ourselves with, and suggest zero-interest balance transfers to “get out of debt faster” when in fact it’s all a shell game to distract us from how we’re digging deeper. After all, it’s not exactly to a realtor’s benefit to say, “You know, this mortgage payment could be 30-50% higher in a few years, and that’s not even counting maintenance or improvements. Can your income handle that?”

At the next layer of cynicism, I call all that a social critic’s excuse list, when the real problems are my irresponsibility, stupidity, and greed.

I’m still privileged beyond question. While I’m one of those on the shrinking iceberg of the United States’ middle class, I’m still there, with a roof over my head and a cushy mid-five-figure job and a credit score that even now manages to hover above average. My constant low-grade anxiety about debt and its impact on my future in no way compares to the kind of daily struggle that people of fewer means must contend with.

But I still have to figure out what the hell to do about it, before it’s too late.

I recently made a pledge to write daily, and to tackle this year’s NaNoWriMo. But maybe the imminent death of my savings account should be a call to action to pursue better habits of a financial nature instead, for my own sake and that of my family.


A Brainstorm on Pricing in the Digital Age

I posted a thought a bit ago on Facebook and Google+, which didn’t at the time feel worthy of a blog post. I’ll reproduce it here, though, since the discussion around it has led in some interesting directions:

I think I’ve put my finger on the core error of thinking when people say it’s not reasonable to price digital media affordably. All this stuff about “blood, sweat, and tears,” “what about my sunk costs,” etc. frames the question of price in terms of what the product is worth to the seller. Of course it’s going to command top dollar in the eyes of the people whose hard work brought the art into the world. But the market doesn’t give a damn what it’s worth to you: it’s the value to the buyer that governs the optimal price. You look at your Great American Novel, and it stings to imagine someone buying it for $2.99 (the top-grossing ebook price point according to the data we have), because all those hours of writing and editing add up to so much more than that for you. And that blinds you to the clear fact that it’s better to make 10,000 sales at $2.99 than it is to make 1000 sales at $10.

Folks responded with a few objections, one of which struck me as particularly apt: the fact that it’s really difficult to gauge what the value to the buyer will be, sight unseen. Wherever you set your price, you’re always going to be left wondering, how many of my paying customers would have been willing to give more, had it been asked of them? And how many customers am I missing out on because the price is higher than they’re willing to pay? We can only set an optimal price if we’re armed with that sort of information, and such counterfactual data is extraordinarily hard to come by.

What if we structured a marketplace with the aim of getting that information to the sellers?

Pay-what-you-want pricing can succeed in the right circumstances. Humble Indie Bundles are a spectacular example, with their clever cocktail of buyer-set prices, bundled product, bonus content for greater contribution, and transparency. Viewed from a certain perspective, sporadic sales and markdowns for products on a platform like Steam end up with a pay-what-you-want feel too. A user puts a desired product on their Wishlist, and when its turn comes up to be marked down 10% or 25% or 75%, the user gets a notification–hey, look at the price now! Is now the right time, has it come down enough for you to buy?

I wonder if we could smash these ideas together somehow. Suppose we had a marketplace where for any item that goes up for sale, users can add it to a wish list, along with their suggestion of a price for it. You could start the process pre-release, even: announce that a product will be available for sale on such and so a date, encourage users to queue it up on their wish lists and say what they’d be willing to pay when it comes out. And all that data feeds back to the seller, with nice graphs: 100 out of 800 interested users say $1.99, 250 say $5, and so forth. The system could algorithmically suggest a sweet spot, which the seller could take, or choose their own price based on their own interpretation of the data.

As the service matures, more and more can be done with it. You’d get the Steam-like notifications of sales, with the additional nudge, well known to sellers of used cars, of “you said you’d be willing to buy at this price, and guess what, it’s now $1 below that!” (I’m sure it wouldn’t be phrased like that. Suffice to say I’m not in sales or marketing myself.) You’d accumulate data on the discrepancies between what people say they’ll pay vs. what they actually spend. You could even aggregate Netflix- or Amazon-like recommendation data back to sellers: “Users who bought similar products tended to pay $4.50 for them.”

I’m sure there are holes in the idea. As postulated, it’s maybe a little too much in the buyer’s best interest to game the system by lowballing, for instance; we’d need to monitor and correct for that. But with work, maybe something like this could help purveyors of digital goods narrow the gap between best-guess and optimal pricing. Hell, maybe this sort of calculation is already going on amid the gears and cogs of Steam…