The Subconscious Order
Most users spend 132 hours/year scrolling menus, often ending up with unsatisfying choices. HungerStation flipped the script by letting your subconscious mind choose your meal in The Subconscious Order campaign .
The app used eye-tracking technology and AI algorithms to analyze which dishes caught your attentionâwithout you even realizing it. Based on this data, it recommended meals your subconscious was most drawn to.
Campaign Overview
HungerStation, a leading food delivery app in Saudi Arabia, was facing a major challenge in a saturated and highly competitive market. While they were a pioneer in the region, numerous new delivery apps with large budgets were emerging. To maintain its market-leading position, HungerStation needed a campaign that went beyond simple discounts and promotions. The core insight for the campaign came from a common modern problem: “choice overload” or “decision fatigue.” An average person spends a significant amount of time endlessly scrolling through food menus, often leading to frustration and, ironically, an uninspired choice. HungerStation wanted to provide a solution to this problem, leveraging innovation to differentiate itself and create a deeper, more personal connection with its users.
Objective
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Solve choice overload in food delivery apps
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Use AI and subconscious cues to help users decide what they truly crave
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Reinforce HungerStationâs position as the most innovative food delivery app in a competitive market
Execution
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The Core Idea: The campaign was based on the premise of letting the subconscious mind make the decision. It was a groundbreaking concept that aimed to “hack” the indecision problem by harnessing the power of the subconscious, which processes information at a much faster rate than the conscious mind.
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Technological Innovation: HungerStation launched a new, smart feature within its app called “The Subconscious Order.” Using the user’s front-facing camera, advanced algorithms, and eye-tracking technology, the tool would meticulously track a user’s eye movements as they scrolled through a variety of enticing food images.
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AI-Powered Analysis: A smart AI, using a proprietary “Food Topic Modelling” system, would analyze what the user’s eyes lingered on the longest, effectively identifying their subconscious craving. It would then generate a data report of what the user’s subconscious mind was craving and provide a curated list of relevant restaurants to order from.
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Guerrilla Marketing Elements: The campaign was a perfect example of guerrilla marketing because it wasn’t an ad; it was a utility. It solved a real-world problem for consumers in a way that was surprising and engaging. The innovative technology became the marketing message itself, generating organic conversation and earned media without the need for a massive ad spend. The experience was so unique that people were encouraged to try it and share their results.
Results
The Subconscious Order Campaign delivered strong results, generating 2.5 million impressions and attracting 78,000 new customers. It drove 630,000 visits to the portal and achieved an average of 6,000 new customers per day, marking it as a highly impactful initiative.
Lessons Learned
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Behavioral design: tapping into subconscious cues to drive action
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Tech-human fusion: using AI to enhanceânot replaceâhuman decision-making
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Emotional branding: solving a problem users didnât know they had, in a delightful way
Conclusion
The “Subconscious Order” campaign by HungerStation is a brilliant case study in how a brand can use technological innovation and deep consumer insight to create a powerful and effective guerrilla marketing campaign. By turning a common frustration into a revolutionary, in-app feature, HungerStation not only generated a huge amount of buzz and new customers but also solidified its position as a forward-thinking leader in the food delivery market. The campaign demonstrated that the most effective marketing is often the kind that provides genuine utility and a surprising solution to a problem you didn’t even realize a brand could solve.
