Kroger / Albertsons: Buying Data in Bulk

Today's post begins grocery week on The Diff. The grocery business is around 3.3% of US GDP, and it's one of the toughest businesses around. Big grocers make margins in the low single digits, and a decent fraction of their inventory literally rots if it doesn't get sold promptly. This industry is simultaneously going through M&A, new kinds of competition, and a change in the strategic value of some of their key assets. Over the course of this week, we'll look at large chains, small chains, and challengers, and then close with thoughts on what other industries can learn from grocers.

Kroger / Albertsons: Buying Data in Bulk

Last month, grocery chains Kroger and Albertsons announced their intention to merge, in a complex deal in which Kroger buys Albertsons, but not before Albertsons pays a substantial dividend to its existing shareholders, and the combined company would spin off a single-digit percentage of their stores in order to ensure that the deal had regulatory approval.

The proposed deal set a price of $34.10 for Albertsons shares, less the $6.85/share value of the dividend and spinoff. Since the dividend's record date has passed, the current merger price for existing shareholders is $27.25/share, and Albertsons closed last Friday at $21.26, implying significant skepticism that a deal can get done. That skepticism is pretty fair. For one thing, there's already an organized effort to halt the deal. And there's a temporary restraining order against the dividend, which the companies are fighting.1

What do the companies aim to achieve by combining the #2 and #4 grocers in the US into an entity with 15% of the overall market? The press release has some nice remarks about improving food freshness and selection, and offering better wages for workers. It even identifies ESG as a reason to pursue the merger (Know your audience!). But the meat of the argument is that they'll have first-party purchase data on 85 million households, covering around $220bn in annual expenditures at both chains' stores. So the combined Kroger-Albertsons will be one of the country's dominant ad data companies—and, unlike most pure-play ad companies, will often be the reserve bidder for their own ad inventory.

The consolidate-and-spin structure is designed so it can partially preclude certain kinds of synergies that the FTC wouldn't look kindly on. If there's a town with two grocery stores, one owned by Kroger and the other owned by Albertsons, a high-margin synergy would be to have both stores jack up prices by an amount based on the cost of gas for getting to a grocery store one town over. But that's not part of the (stated) plan, and given that they specifically promised to spin off stores—and gave a range of 100 to 375 for the number of stores they'll spin off—they're basically promising the FTC that if they merge, either a) that's not part of the plan, or b) if it is part of the plan, and they get away with it, it will be entirely the FTC's fault.2

There is some room to optimize supply chains through raw scale, even if there are deliberate limits to the geographical overlap of stores. Some kinds of purchases will be cheaper—the company expects prices to drop, though by an aggregate of 0.2%—and bigger customers get qualitative privileges that smaller ones don't. (If there's an operational slip-up and one of two customers is getting their order a little later than planned, the customer who gets theirs on time is probably the bigger one.)

And there are some economies of scale from private label products. The company cites a combined $43bn in annual sales from these products in the last fiscal year, and some private label brands end up with recognizable brand names. (Review the list of private label brands from any big retailer you patronize, and you may be surprised by how often you're actually buying the company's own products.)

But the ad business is the big one. No retailer looks at AWS and says "I could have done that," but plenty of them look at Amazon's ad revenue—$9.5bn last quarter, or 11% of all of Amazon's retail revenue, and with much higher margins—and see an opportunity. That opportunity is especially timely for three reasons:

1. Apple's privacy changes make it harder to match purchase data to specific users, weakening ad targeting for the companies that relied on being able to do this. The companies that naturally collect first-party data can still use it to target ads (stay tuned for a writeup on Instacart later this week!). And that's powerful in the grocery business, where products are evaluated both based on their contribution margin and their ability to generate store visits that lead to higher-margin goods. A $4.99 rotisserie chicken is a low-margin product on a standalone basis, but it's a very cheap way to get someone into a store where they might fill up the rest of their cart with higher-margin goods.
2. The pandemic moved more ordering onto apps and websites, even when the orders were being picked up in store. If shoppers are already omnichannel, then even a store visit that doesn't involve an app interaction can still produce data. And that data can actually be used, not just to target ads within the app, but to get people to use the app more by sending targeted offers. (McDonald's is running billboards right now advertising discounts that are only available within the app, as are other fast-food restaurants. If you thought ads for ads were just part of the ad arbitrage/chumbox model, think again: McDonald's is using billboard ad spend to get temporary gross margin compression in order to use their app as captive ad inventory with first-party data.)
3. Inflation makes tradeoffs more salient. Shoppers are trading down as they either literally can't afford some products or as they decide that some premium indulgences aren't worth the cost anymore. It's hard for retailers to navigate this change, because they basically need a demand curve for every customer and every product. And owning lots of first-party data gets them close to approximating this! There are many other goods on the continuum between rotisserie chicken and, say, a high-margin bottle of private-label vitamins or vodka.

The irony of modern antitrust is that across the industries that rely on advertising, there's a new urgency to hoard first-party data, and to build in-house capabilities to turn that data into high-margin ad revenue, which spurs deals like this one—and this is all because Apple, a company with market power in a completely different area, decided to cripple the ad business (while growing their own ($)). From the perspective of avoiding market concentration in general, there might be a case for nixing the Kroger/Albertsons deal. But from the perspective of not letting a monopolist or near-monopolist ruin someone's day, these deals are an antidote rather than a poison.

Further reading: Matt Stoller has a piece attacking the deal—understandable, since that's his beat—with lots of helpful links.

A Word From Our Sponsors

Tegus is the first port of call for M&A professionals and institutional investors ramping up on an industry or company.

Get access to a database of 35,000+ expert call transcripts, spanning 5+ years, or schedule expert calls through the platform for a fraction of the usual cost.

When thousands of research analysts are pooling their expert calls into an on-demand database, using Tegus is table stakes. It's the leading platform for due diligence and primary research.

See the power of a Tegus subscription, and get up to data parity with your competitors, with a two week free trial through the Diff.

Elsewhere

Meme Shorts in Crypto

Last week, a balance sheet from Alameda Research leaked (story here, covered in The Diff here). As a quick reminder, Alameda Research is a crypto prop trading firm with the same owner as FTX, the crypto exchange. This has always been a bit weird, though as last week's piece noted, the NYSE was basically an exchange owned by prop traders who used it for most of its existence.

At this point it's basically a natural law of finance that any vague and complicated information about a levered entity will lead to wild rumors on Twitter. This piece argues that Alameda's biggest asset, a position in the FTT token issued by FTX, is being manipulated, and that the fund has effectively no equity. Alameda counters that the balance sheet is for a subset of their assets, and doesn't include hedges.

For an institution with sufficient leverage, insolvency is as a matter of opinion is insolvency as a matter of fact; even if Alameda is partly hedged, a combination of lenders calling in loans and speculators betting against their known positions can, in an extreme case, kill them. (And while Alameda may have some hedges, it's hard to imagine which counterparty would be willing to take the other side of a hedge covering $5.8bn of FTT.)

The latest development in the story is that Changpeng Zhao, CEO of FTX competitor Binance, has announced plans to sell all of Binance's position in FTT. This is, generously, about 5% a prudent diversification decision given fundamental questions about FTT's long-term performance, and about 95% an opportunity to seriously disrupt a major competitor. For Alameda, one of the nice things about having an organization where the CEO is a trader who does their PR on Twitter is that they can quickly offer a pretty definitive counterargument, specifically offering to buy the entire position for right around the market price.3 "if you're looking to minimize the market impact on your FTT sales" was a nice touch there.

There's a long history of stepping in to counter asset price collapses. This is part of what Warren Buffett did with his preferred stock deals in 2008: he was paid (well) by GE and Goldman Sachs to show the market that he believed they were solvent. On the other hand, during the crash of 1929 a group of bankers put together a syndicate with investor Richard Whitney to give him enough capital to place above-market bids on a selection of blue-chip stocks. The market crashed anyway, and Whitney ended up in prison for embezzlement.

So it's a tactic with a mixed record. On the other hand, it serves the twin mandates of successful traders—take positive expected value bets, even if there's going to be some volatility along the way. And do anything necessary to avoid the risk of getting wiped out.

Unfiring

Twitter, which laid off half of its employees on Friday, has asked a few dozen to return since then. As with any layoffs, productivity goes down between when layoffs are expected and when they actually hit, both because workers are worried and because they're busy looking for other jobs. So companies won't generally lay off the theoretically optimal set of employees—a 10% layoff is never just the bottom 10%, and that's even more true for a 50% layoff. For a company that's overstaffed, it may make sense to stress-test things by cutting more than necessary and hiring back; over the long term, figuring out whether the right employee count was 60% of the original total or 80% will be bigger than the cost of temporarily overshooting. But it's a messy process that's brutal to the people involved.

(Interestingly enough, one Musk biography claims that when his assistant asked for a raise, Musk's response was to suggest that she take a two-week vacation so he could see if she was really so essential, after which he fired her. Musk strongly disputes this, though.)

Will Expensive Food Cause Expensive Food?

The Economist draws attention to research showing that military conflict and insurgencies reduce food security, while noting that one cause of unrest and insurgencies is expensive food. This is less impactful in stable countries with high standards of living, where food is a small proportion of expenditures and where voters register most of their complaints through the political system. But present the possibility that developing countries will go through a spiral where high food prices weaken governments and weak governments lead to higher food prices.

The Outrage Cycle

The more senior an executive is, the more likely it is that their compensation will take the form of incentive payments rather than fixed sums. And because the arrow of time points one way, this means that they will get high pay in the year after times were good, even if at the time they receive that pay times are not nearly so good. CEOs of FTSE 100 firms, for example, will see a 23% pay increase this year ($, FT) on average, at a time when the UK's stock market is flat for the year and the economy is struggling.

This kind of sequence of events happened in the US after the dot-com bubble, with outrage over high CEO compensation dovetailing nicely with outrage over actual fraud. (The Tyco case, for example, seemed to be less about how Dennis Kozlowski reported his earnings numbers and more about things like a $2.1m birthday party for the CEO's wife, half paid for by the company, featuring an ice sculpture of Michelangelo's David ($, WSJ).)

Stability and Financial Repression

One part of China's economic development approach is to limit the mobility of capital in order to encourage domestic investment. If people are forced to save, and if their savings get channeled into the banking system, then economic growth funds more investment in infrastructure and property. This has worked for a while, but it means that the investable universe is skewed towards direct and indirect bets on property prices. And now that property prices aren't rising, defaults have gone up ($, Economist):

Between 40-60% of assets at three large trust firms—Minsheng, Wanxiang and Huachen—are non-performing this year. Anxin, another large company, reports that almost all of its assets have gone south. Out of the 57bn yuan in investments on which trust firms defaulted in the first seven months of this year, some 80% were linked to property loans.

The benefit of limiting savers' investing options is that it channels money into areas the government prioritizes, and also reduces the inflationary impact of higher earnings since those earnings don't translate into higher consumer spending. The downside is that if the investment target wasn't chosen well, savers lose their money—and worry that they can't trust the system overall.

Diff Jobs

Companies in the Diff network are actively seeking talent! If you're interested in exploring growth opportunities at unique companies, please reach out. Some top current roles:

• A company bringing machine learning tools to everyone is looking for experienced ML engineers with strong product sense. (NYC)
• A new service that's trolling the dating market with a better product and better monetization is looking for a full-stack founding engineer. (Los Angeles)
• A company that helps emerging tech businesses identify and hire top talent—and that gets paid in equity—is looking for new team members. A great way to build a startup portfolio and a great network without an in at a VC firm. (US, multiple locations)
• A company that's building a new hyperlocal bricks-and-clicks business seeks a strategy and operations expert who can help them scale. (SF & LA)
• A crypto data company is looking for a frontend developer who can build powerful interfaces for working with large amounts of data. (US, remote)

If you’re looking for talent, we should talk! Diff Jobs works with companies across fintech, hard tech, consumer software, enterprise software, and other areas—any company where finding unusually effective people is a top priority.