The Algorithm Behind Restaurant Hype How Your Feed Decides What You Eat

A handwritten waiting list is already affixed to the door of a cafe in Surry Hills, Sydney, at a quarter past ten on a Saturday morning. Six months prior, you could walk right in. While her buddy crouches with a Nikon, aiming for the ideal shot, a woman in a beret stands at the entrance with a takeaway flat white in hand. Before a single bite is taken, their food buttermilk fried chicken, waffles shimmering in syrup will be captured on camera, edited into a fifteen second video, and shared. Barely touched, the plates will return within. Meanwhile, the algorithm has already started working.

Cities like Melbourne, Manhattan, Lagos, and London are all experiencing this scene, or a variation of it. A restaurant may now attract a ninety minute line without a Michelin star. It requires a thumbnail with a cheesy pull, a laptop sized croissant’s molten cross section, or birria tacos oozing into polystyrene consommé cups. The grammar is written in short form film, and the language of food fame has evolved. There’s a feeling that we’ve reached a point where the feed is more important than the flavor, but depending on who you ask, that may or may not be a tragedy.

The mechanics are very straightforward. A new area is visited, a video is shot with the tagline I tried the Viral X at X, a series of emoji hieroglyphics are dropped, and the location is tagged. The platform’s recommendation engine determines whether to send the video to 500 or 500,000 users based on engagement signals like watch time, shares, and saves. In this case, the restaurant itself has very little influence. Actually, neither does the creator. The algorithm, which acts as a silent curator, consistently favors spectacle over nuance.

The benefit is evident to Joaquin Saez Binder, owner of Sydney’s Mediterranean eateries Ikaria and Iberica. He notes that the algorithm allows smaller eateries to connect with customers they would not have been able to reach through conventional advertising. Before reels and TikTok, a neighborhood location without a PR budget just didn’t have that level of attention.

However, there’s a chance that this democratization has its own flaws. Cheyenne Bardos, a freelance food journalist and culinary programmer at the Powerhouse Museum, carefully phrases it modern customers are more sophisticated and discriminating, consulting a variety of sources before selecting a restaurant. In today’s noisy ecosystem, reviews, reels, and community word of mouth coexist. The problem is that opinions can be influenced by commercial interests, taste is subjective, and the loudest voice isn’t always the most reliable. It’s a market for attention rather than quality.

A quieter, more deliberate mechanism operates behind the apparent turmoil of viral food culture. In order to forecast what people would want to eat before they even realize it, companies like Tastewise, the Israeli AI platform developed by Alon Chen and Eyal Gaon, are analyzing enormous amounts of data, including over 150,000 restaurant menus, a million internet recipes, and millions of social media posts. Their algorithms analyze motivations in addition to identifying trends. Consider ube, the purple Filipino yam that was popular on Western restaurants a few years ago.

According to Tastewise’s investigation, flavor wasn’t the only factor. The veggie was visually appealing for Instagram, sweet, vegan friendly, and foreign. It fulfilled all the requirements of the current cultural period. Tastewise’s own statistics indicates that conventional trend analysis fails up to 85% of the time. Although the AI substitute isn’t flawless, it is quicker and more detailed than any store report or survey.

Beneath the excitement, there’s a darker undertone as well. Algorithms choose what we see and what we don’t see. The Culinary Edge strategists Julia Segal and Haley Kabus have written persuasively about the confirmation bias inherent in recommendation algorithms. By displaying more of what consumers already enjoy, these systems aim to maximize user engagement. The end effect is a sort of gastronomic echo chamber, where the Senegalese thieboudienne or the Oaxacan tlayuda never show up, while your feed continues to serve you ramen variations if you ever lingered on a ramen reel.

The unfamiliar is subtly hidden due to optimization logic rather than malice. Whether the business can or even wants to address this narrowing effect is still up for debate In the meanwhile, eateries that do become viral may face severe pressure. Can a little matcha cafe truly withstand the unexpected onslaught of a fifty person line before doors open? Bardos poses a question that isn’t often answered.

Can a modest Filipino restaurant match the expectations of patrons whose anticipation was heightened by a slow motion 4K reel? In a city like Sydney, cultural pride and culinary underrepresentation might generate immediate excitement. There is actual operational strain. Wait times can reach 70 or 90 minutes. burnout among employees. decreases in quality.

And when reality falls short of the shiny promise of a fifteen second film, the very hype that packed the seats can become a reputational disaster. Naturally, corporations have figured out how to precisely take advantage of this ecology. For example, the collaboration between Popeyes and Don Julio Tequila did not naturally result from customer excitement.

Celebrity endorsements, viral jingles, and targeted social media placement were all designed to create a cultural moment. Sales at Don Julio increased by 20% in 2023, following the pattern of the 2019 Popeyes Chicken Sandwich mania. As this develops, it’s difficult to avoid wondering how much of what appears to be grassroots culinary culture is really corporate strategy disguised as TikTok.

The manager of Sydney’s Corner 75 and Baba’s Place, Jean Paul El Tom, adopts a more realistic perspective. He is adamant about keeping reel culture at far and concentrating on the things he can control, including wholesome food, ethical sourcing, and a product he is proud of. Online criticism erupted as soon as Corner 75’s ownership shifted. However, the anger lessened when the quality of the schnitzel and goulash remained mostly unchanged, perhaps even slightly improved. El Tom’s stance is practical a dining room can be filled with viral content, but if the cuisine is truly awful, people will ultimately realize it. When a robust internet presence offers cover, it simply takes longer to sift out the subpar.

We seem to be at a peculiar turning point. According to industry reports, about 70% of restaurant operators are currently testing or preparing AI deployments. McDonald’s alone has spent more than $300 million on AI and machine learning, including drive thru systems that use license plate readers to record orders and adjust recommendations in the future. Prediction is the goal, not just efficiency. becoming aware of your desires before they arise. However, it’s unclear if an algorithm that keeps suggesting Big Macs because you ordered one last Tuesday is actually helping you or if it’s just benefiting itself.

The best form of this technology would do something more intriguing, more akin to a superb restaurant server’s intuition when they see that you’re in the mood to try something new and recommend the off menu special because they read your energy rather than your past purchases. Prediction and true hospitality continue to diverge greatly. The algorithm powering restaurant buzz will continue to feed us what it believes we already want, one auto play reel at a time, until it narrows.