The Case Against Google

Shivaun Moeran and Adam Raff met, married and started a company — thereby sparking a chain of events that might, ultimately, take down this age of internet giants as we know it — because they were both huge nerds. In the late 1980s, Adam was studying programming at the University of Edinburgh, while Shivaun was focused on physics and computer science at King’s College London. They had mutual friends who kept insisting they were perfect for each other. So one weekend, they went on a date and discovered other similarities: They both loved stand-up comedy. Each had a science-minded father. They shared a weakness for puns.

In the years that followed, those overlapping enthusiasms led to cohabitation, a raucous wedding and parallel careers at big technology firms. The thing is, though, when you’re young and geeky and fall in love with someone else young and geeky, all your nerdy friends want you to set them up on dates as well. So Adam and Shivaun, who took Adam’s last name after marriage, approached the problem like two good programmers: They designed a dating app.

The app was known as MatchMate, and the idea was simple: Rather than just pairing people with similar interests, their software would put together potential mates according to an array of parameters, such as which pub they were currently standing in, and whether they had friends in common, and what movies they liked or candidates they voted for, and dozens of other factors that might be important in finding a life partner (or at least a tonight partner). The magic of MatchMate was that it could allow a user to mix variables and search for pairings within a specific group, a trick that computer scientists call parameterization. “It was like asking your best friend to set you up,” Shivaun told me. “Someone who says, ‘Well, you probably think you’d like this guy because he’s handsome, but actually you’d like this other guy because he’s not as good-looking, but he’s really funny.’ ”

Within computer science, this kind of algorithmic alchemy is sometimes known as vertical search, and it’s notoriously hard to master. Even Google, with its thousands of Ph.D.s, gets spooked by vertical-search problems. “Google’s built around horizontal search, which means if you type in ‘What’s the population of Myanmar,’ then Google finds websites that include the words ‘Myanmar’ and ‘population,’ and figures out which ones are most likely to answer your question,” says Neha Narula, who was a software engineer at Google before joining the M.I.T. Media Lab. You don’t really care if Google sends you to Wikipedia or a news article or some other site, as long as its results are accurate and trustworthy. But, Narula says, “when you start asking questions with only one correct answer, like, Which site has the cheapest vacuum cleaner? — that’s much, much harder.”

For search engines like Google, finding that one correct answer becomes particularly difficult when people have numerous parameters they want satisfied: Which vacuum cleaner is cheapest but also energy-efficient and good on thick carpets and won’t scare the dog? To balance those competing preferences, you need a great vertical-search engine, which was something Adam and Shivaun had thought a lot about.

Soon the Raffs began daydreaming about turning their idea into a moneymaker. They didn’t have the funds to compete with huge dating sites like Match.com, so they applied for a couple of patents and began brainstorming. They believed that their vertical-search technology was good — better, in fact, than almost anything they had seen online. Best of all, it was built to work well on almost any kind of data set. With just a bit of tinkering, it could search for cheap airline tickets, or great apartments, or high-paying jobs. It could handle questions with hard-to-compare variables, like what’s the cheapest flight between London and Las Vegas if I’m trying to choose between business class or leaving after 3 p.m.?