Your mobile decides online order prices:E-commerce platforms found charging iPhone users higher rates than Android users for same products and services

When Shruti and Samriddhi, two friends from Bhopal, booked a bike ride from Rani Kamalapati Railway Station to Raja Bhoj Airport, they had no idea they were about to uncover something strange about how technology shapes the way we spend money. Both initiated their bookings at the exact same time, using the same app, choosing the same pick-up and drop-off points, and even checking out the same ride option. Yet, when the fare appeared, there was a clear difference. Shruti’s Android phone showed the fare as Rs 234, while Samriddhi’s iPhone displayed Rs 249 for the same trip — a difference of Rs 15. It seemed minor at first, but this Rs 15 was not just about a ride — it was a sign of something much bigger. What started as a casual booking became a clue to a quiet digital divide emerging in India’s online marketplaces — one where your device type might secretly influence how much you pay. The hidden pattern behind everyday apps This difference isn’t limited to just ride-hailing apps. Across food delivery, grocery shopping, and travel booking platforms, a similar pattern has started to emerge. iPhone users — often categorized as “premium” consumers — are being charged slightly higher prices for the exact same services that cost Android users less. The reason? Advanced algorithms running quietly in the background, powered by Artificial Intelligence (AI) and user profiling systems. To test this systematically, Dainik Bhaskar conducted a detailed experiment. The team used two phones — one iPhone and one Android — to order identical products and services from the same apps, at the same time, from the same location. The results revealed a pattern that could redefine how we think about online pricing. Experiment 1: A 6% difference for the same ride The first test involved a bike ride booking on a popular mobility app. Both phones were used to book a ride from Rani Kamalapati Station to Raja Bhoj Airport, covering an 18-kilometre distance. That’s a 6% difference — and not because of traffic, time, or surge pricing. Everything else was identical — the same distance, time, route, and app version. The team repeated the test on another cab service app, booking a mini cab for the same route. Once again, the iPhone user was charged higher — Rs 277 compared to a lower fare shown on Android. This consistent difference revealed a silent but powerful pricing mechanism at play — one based not on your needs but on your device identity. Experiment 2: When food costs more on an iPhone The next test moved to food delivery. The reporters ordered identical meals from a restaurant in MP Nagar, located just 1.5 kilometers away. The order included a Veg Cheese Pizza, Paneer Tikka Pizza, Mint Mojito, and Blueberry Mojito — the same dishes, same restaurant, same delivery location, same delivery partner. When the bills were generated, the Android user saw a total of Rs 2,067, while the iPhone user’s total was Rs 2,073 — a Rs 6 difference. Though the gap appeared small, it confirmed one crucial point: the variation in prices wasn’t random. It followed a systematic pattern across different platforms, subtly making iPhone users pay more. Even a few rupees difference per transaction might sound trivial, but multiply that by millions of daily orders, and it turns into a massive business strategy. Experiment 3: The grocery game The final test explored quick-commerce grocery apps, a sector booming in Indian cities. During a Diwali sale, the team tried to order two boxes of chocolates using both phones from the same location and account type. Both phones displayed the same estimated delivery time — 11 minutes. But when the final totals appeared, there was a visible difference once again: That’s Rs 14 more for the same chocolates, at the same time, under the same festive discount. The findings were now beyond coincidence. They revealed a consistent price gap tied to device type — not service quality, not delivery timing, but the assumption that an iPhone user can pay more. The algorithm deciding what you pay To understand why this happens, we reached out to Yashdeep Chaturvedi, an information technology expert, who explained the mechanics behind this phenomenon. “Most e-commerce and delivery apps today use what’s called a Dynamic Pricing Algorithm,” Chaturvedi explained. “This means prices are not fixed. They change constantly depending on various factors — time, demand, location, past activity, and even the kind of device being used.” In simple words, the apps are not just selling you products — they are analyzing you as a consumer in real-time. Based on that analysis, they estimate how much you are willing to pay and adjust prices accordingly. If you’re using an iPhone — a symbol of higher income and brand preference — the system often tags you as a “premium customer.” How ‘premium profiling’ works When users sign up for any digital service, they unknowingly feed vast amounts of personal data into the system: name, email, mobile number, location, payment method, and device type. Each of these data points helps companies build what experts call a “consumer price profile.” If your data indicates that you own an expensive phone, shop frequently, or prefer express delivery, you may automatically fall into a “high-value” customer category. The algorithm assumes that price is not your biggest concern — convenience and quality are. This assumption becomes the foundation for digital price discrimination — an invisible system that tweaks costs according to perceived affordability. The psychology of spending — And how AI exploits it Digital pricing strategies have evolved to read human behavior in ways traditional markets never could. Companies track your mouse movements, scrolling speed, time spent on a page, and even how long you hesitate before clicking “Buy Now.” Every hesitation, delay, and repeated visit to a product page tells the algorithm something about you — whether you’re a bargain hunter, an impulse buyer, or a loyal customer who doesn’t need discounts. This is called “Price Sensitivity Analysis.” It determines how much pressure or price flexibility a customer can tolerate before abandoning a purchase. For instance: It’s a silent game of behavioral economics — powered by AI, invisible to consumers, and difficult to challenge. The global scene: Laws and regulation While countries like the U.S. and the U.K. have started responding to this digital pricing dilemma, India remains largely unregulated. In New York, algorithmic pricing that isn’t clearly disclosed to customers is restricted. Ohio mandates companies earning over $5 million annually to disclose whether prices were determined by AI. In the United Kingdom, a new digital markets law allows penalties of up to 10% of a company’s global revenue for deceptive or discriminatory pricing practices. In India, however, there is no explicit law addressing AI-driven or device-based pricing. India’s legal grey area The Consumer Protection Act (2019) and Information Technology Act (2000) provide broad protections against data misuse but don’t specifically address algorithmic pricing. The recently enacted Digital Personal Data Protection Act (2023) gives users some control over how companies collect and use their data — but even this law doesn’t directly regulate how AI systems use that data to influence prices. This means that as long as companies obtain user consent to access data, they can still employ that data to adjust pricing — even if it means systematically charging certain consumers more. Why this matters In a world increasingly dependent on apps for everything — from food to transport — pricing transparency becomes a question of fairness. If two people standing side by side, using the same app for the same service, are charged different rates simply because of their phone brand, it raises critical ethical and economic questions. While dynamic pricing is a legitimate tool to manage supply and demand, device-based discrimination crosses a line. It turns consumer data into a silent weapon of profit maximization — without disclosure or accountability. The bottom line Your phone isn’t just a communication device anymore — it’s a pricing signal.
Each tap, swipe, and scroll trains the algorithms that decide how much you pay online. From ride fares to pizzas to groceries, your smartphone — particularly if it’s an iPhone — could be silently costing you extra every day. Until India enacts stronger digital transparency laws, consumers will remain largely unaware of this invisible layer of pricing inequality — where the true price of convenience is paid not in rupees, but in data.