Airbnb, Scale, and Fraud

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Edward Nevraumont

Airbnb Fraud

If you spend any time on social media, you’ve probably noticed occasional stories about despondent travelers who arrived at their destination, only to discover that the Airbnb they booked — and paid for — did not exist. How pervasive is Airbnb fraud? On October 31, Vice published a stunning exposé on Airbnb fraud, written by Allie Conti. Her astonishing investigation connected one frustrating incident to a complex network of fraudulent reservations: 

I had unknowingly stumbled into a nationwide web of deception that appeared to span eight cities and nearly 100 property listings — an undetected scam created by some person or organization that had figured out just how easy it is to exploit Airbnb’s poorly written rules in order to collect thousands of dollars through phony listings, fake reviews, and, when necessary, intimidation. Considering Airbnb’s lax enforcement of its own policies, who could blame the scammers for taking advantage of the new world of short-term rental platforms? They had every reason to believe they could do so with impunity. [Emphasis mine]

Conti’s article was widely shared on news sites and social media. Within a week, Airbnb responded with a bold promise — they would manually verify all 7 million listings on their site. Without question, that verification process will prove costly, but what choice does Airbnb really have? The success of their platform hinges on TRUST. When you book a property, you trust that you will not be scammed. Likewise, when you rent your home, you trust that you will not be swindled. If that trust disappears, so does Airbnb’s business. Conti identified “nearly 100” listings in an organized scam. Even if those were the only fraudulent properties on a site with 7 million listings, it degrades trust in the platform. As such, Airbnb needs to act — swiftly and decisively. As Google likes to say, “competition is only a click away” (in Airbnb’s case, that competition is Expedia and the Booking Group).

Airbnb is not the only company with fraud problems.

When Google launched their original search engine, it provided significantly better results than established leaders like Yahoo and AltaVista. Google’s algorithm was surprisingly simple: it focused on the interconnection of backlinks (the incoming links to a webpage). Pages with the greatest number and quality of backlinks would receive a higher PageRank (Google’s term for measuring the importance of websites). Moreover, pages with higher PageRanks were assigned more weight for links FROM that page. (Side note: you can still read a copy of the research paper from then-grad students Sergey Brin and Lawrence Page that was used as the foundation for Google’s algorithm). 

Brin and Page devised an innovative way to (roughly) measure the quality of a webpage. Their algorithm, though, produced effective results because Google did NOT operate on a large scale. When consumers discovered Google’s quality, they abandoned other search engines. Once Google reached a greater scale, the simple algorithm began to show its flaws.


Gaming Google

When the quality of Google’s rankings started deteriorating, the changes had nothing to do with the design of the algorithm. In fact, the algorithm remained the same; what changed were the types of websites moving their way to the top of the sort order. When Google’s search engine launched, no one assumed responsibility for monitoring the behavior of people running websites. Everything shifted when people realized the monetary value of appearing on the top of the largest and most important search engine.

People developed tricks — known as Black Hat search engine optimization — to game Google’s algorithm. In one common strategy, people built “link farms,” where thousands of webpages would be created and linked to each other. In even more effective operations, people designed “link pyramids,” where thousands of webpages would link to hundreds of webpages which linked to dozens of webpages, leading to the one “pinnacle website” which sucked up all the “link juice” and dominated search results. 

In an effort to control the integrity of their rankings, Google engaged in a protracted battle with Black Hat optimizers. After Google tweaked their algorithm to thwart link farms and pyramids, SEOs attempted to reverse engineer and then change their sites to “beat” the algorithm. Google redesigned their algorithm to reward “engagement” on a site, so SEOs began introducing “slide shows” to ensure high engagement. When Google increased the weight of brand searches, SEOs hired thousands of humans in India to VPN to the United States and conduct repetitious brand searches. In short, Google faced a digital version of whack-a-mole — one that continues to this day.  

Other companies have encountered similar problems on their platforms. For years, Facebook has battled the efforts of people trying to manipulate their newsfeed algorithm. At the moment, Facebook is also dealing with “content factories” that are disrupting the authenticity of Instagram’s posts. Counter-Strike — a popular video game that allows online players to trade (virtual) items like weapons and uniforms — has been besieged by widespread issues of money laundering. Even TikTok — a playful social network for sharing video clips — is struggling to curtail the proliferation of fake news (spread through song, no less!).

Of course, fraud predates the internet.

Check out this story of the first recorded financial fraud — from 300 BC. When I lived in Nigeria, we regularly saw homes spray painted with messages that read, “419 — home not for sale.” Locals explained that the painted warnings helped prevent a scam where people would break into your home during an absence, and then sell it to someone else. Imagine returning from vacation, only to find someone else living in your house with a bill of sale they believed to be legitimate. (Side note: “419” is the section of Nigeria’s criminal code that deals with fraud. The number carries a slang connotation for fraud, as in “You don't want to get 419-ed”).

In the US, phone-based scams have existed — in one form or another — for as long as Americans have owned telephones. When email replaced phone calls as the focus of our social and professional lives, fraudsters shifted their attention to email. A recent article in The Wall Street Journal reported on a study co-funded by the Better Business Bureau, Financial Industry Regulatory Authority, and Stanford Center on Longevity. I don’t think you’ll be surprised by their findings:  

A new study of consumer behavior toward fraudulent schemes found that scammers are far more likely to succeed in engaging and stealing money from potential targets by using websites and social media than through the phone calls and emails they have long used. [Emphasis mine]

The study investigated platforms like Craigslist, eBay, and Facebook; their research concluded that fraud (or at least reported fraud) has increased dramatically in recent years:

Consumers filed 372,000 fraud complaints to the Federal Trade Commission reporting a total loss of $1.5 billion in 2018, with the number of complaints up 34% from 2017, according to tallies by the report’s authors. [Emphasis mine]

In an apocryphal story, notorious criminal Willie Sutton explained his preference for robbing banks: “because that’s where the money is.” That logic holds for this generation of digital outlaws; they conduct scams via the internet, “because that’s where the money is.” 

Why is fraud on the internet more lucrative than scams from the pre-internet era? Because the internet offers far more SCALE than any other form of communication in history. 

Share Marketing BS with Edward Nevraumont


A Fundamental Element of the Internet 

I would like to share three ideas that demonstrate how scale is a fundamental element of the internet

  • As I described in “Sign-in with Apple,” Google and Facebook consume 63% of all digital advertising spend. Apple’s new system will likely concentrate the vast majority of advertising dollars in the hands of those three companies. In the post, I explained how digital marketers ended up in this position; the short answer involves the benefits of “scale.”

  • An August newsletter explored the differences between Facebook and Reddit. Despite Reddit’s ranking as the sixth-most-visited website on the internet, it earns less than 4% of Twitter’s revenue. The reason, I argue, stems from the difficulty of advertising on Reddit. Even if the ROI from advertising is high, the scale you can reach is relatively small. As such, many companies do not bother advertising on Reddit at all. It’s just not worth the fixed cost of the effort to develop an effective campaign, given that it will never be “that big.”

  • From my upcoming book:

    • Jeff Blackburn is Amazon’s SVP of business development and one of only ten people who report directly to Bezos. ... I once heard someone ask him, “What's the most important thing when you consider acquiring a startup — is it the team or the products?” He answered, “neither.” He clarified that the most important factor was the size of the market. Even if you have a great team or fantastic product, going after a tiny reward is not worth the effort. The size of the prize is what counts.

During my time at McKinsey, we often joked that our job focused on “keeping dinosaurs from going extinct for a little longer.” We rarely worked for companies that were rapidly expanding or for ones that were small in size. Fast-growing companies don’t have a “felt need” for McKinsey, and small companies couldn’t afford McKinsey. But if the company was (1) really big, and (2) slowly shrinking, they were not only desperate for help, but also in a position to afford the most expensive consulting firm. But even more importantly, large companies have more to gain from McKinsey’s services because of something small companies don’t have: scale.

The assessments at McKinsey often targeted improvements “by percentage.” We identified recommendations to make things “better,” be that a 10% decrease in costs or a 10% increase in effectiveness. Ten percent hardly matters for venture-backed firms trying to double in size every two months, but for a company spending $1 billion in procurement costs, a savings of 10% is worth $100 million. That sum pays for a lot of McKinsey consultants.

To illustrate this concept, here’s one of my favorite stories about an unexpected business solution: stacking bananas. We were looking to reduce operation costs at a grocery chain. In a standard case, we might have identified ways to fix a step in the supply chain — something like adjusting the scheduling of delivery trucks. 

But for this particular situation, the solution was even more simple. Part of our consultancy process involved watching regular employees complete their daily tasks. In the produce department, bananas were displayed in a “banana pyramid.” Stock clerks were taught to start at the bottom, working their way around the base. They would repeat that process for each level of the pyramid until they were at the top — this was the most obvious method for arranging bananas. But the conventional approach to building a banana pyramid was not the most efficient. If stock clerks instead stacked ONE side of the pyramid from bottom to top, they could then repeat the process for each side of the pyramid — without needing to move their feet. Using this approach could save five minutes or more each time they stacked a display of bananas. Five minutes may not seem like much, but if repeated twice per day across 2000 stores, that is over 300 hours per day or ~120,000 hours per year. At $12 per hour, that’s ~$1.5 million in savings just by changing the way that stock clerks stack bananas!

What is trivial for an individual becomes significant for large entities because of scale.

And nothing provides scale better than the internet.


The Power of Scale

Scale has pushed Amazon, Apple, and Google to become the world’s most valuable companies. Scale created the conditions for the rise of Uber, Airbnb, and Stripe. Although scale has provided “your own personal driver on demand,” it’s also empowered immoral people to act with impunity. 

As everyone knows, internet fraud is rampant. But a recent report from the New York Times described an even darker side of the web:  

Pictures of child sexual abuse have long been produced and shared to satisfy twisted adult obsessions. But it has never been like this: Technology companies reported a record 45 million online photos and videos of the abuse last year.

More than a decade ago, when the reported number was less than a million, the proliferation of the explicit imagery had already reached a crisis point. Tech companies, law enforcement agencies and legislators in Washington responded, committing to new measures meant to rein in the scourge. …

Yet the explosion in detected content kept growing — exponentially.

How do we explain the rapid increase in reported cases of images that exploit children? I think two factors are responsible for the occurrence: 

  1. The internet makes many things easier, including the committing of evil acts. Modern technology allows for easier (and anonymous) transfers of files between people with similar interests, around the globe. All of the internet features that allow companies to scale also facilitate engagement in perverse and harmful actions.  

  2. As “tech companies” reach scale, they are more effective at finding the people responsible for fraud and transgressive acts. We should expect that criminality and immorality will grow at least as fast as improvements to the internet; hopefully our ability to catch perpetrators will continue to increase at an even faster rate. 

Two weeks ago, I wrote about “Facebook and Free Speech.” I mentioned Facebook’s investment in strategies to detect and block dangerous content (like the encouragement of violent terrorism). Here is a quote from Mark Zuckerberg’s contextualization of that strategy: 

Our AI systems identify 99% of the terrorist content we take down before anyone even sees it. This is a massive investment. We now have over 35,000 people working on security, and our security budget today is greater than the entire revenue of our company at the time of our IPO earlier this decade. [Emphasis mine]

Critics will always complain that Facebook is not taking enough action, but the problem they face is similar to what Google experienced when their search engine grew in size and reputation. The larger the platform, the greater the reward for people to get past the platform’s filters and algorithms. The reason Facebook needs to spend more on security than the “entire revenue of the company at the time of IPO” is obvious — Facebook is (substantially) larger and more important now than it was in 2012.

Today, Google’s search algorithm is so sophisticated at identifying fraud that many SEOs recommend that you should stop trying to game the system. In the (increasingly) rare case that you discover a way to beat Google’s algorithm, the “hack” is unlikely to last very long before the company implements a solution. As such, any efforts to use devious methods are probably not worth your time and resources. Instead, you should invest your energies toward the steps that Google states should increase your search visibility. We can hope that Facebook’s investment in AI will reach the point where defrauding the newsfeed with “evil” content is similarly a waste of time. I’m not optimistic, but if you had asked me a decade ago if Google could effectively eliminate Black Hat SEO, I would have been skeptical then, too.

Meanwhile, I don’t think you need to worry too much about being defrauded on Airbnb — at least for now. Occasional scams will probably trick users from time to time, but given the company’s new focus on establishing trust, Airbnb fraud should be less likely to happen in the near future than it ever was in the past.

Keep it simple,

Edward

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Edward Nevraumont is a Senior Advisor with Warburg Pincus. The former CMO of General Assembly and A Place for Mom, Edward previously worked at Expedia and McKinsey & Company. For more information, including details about his latest book, check out Marketing BS.

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