Yesterday you checked online and saw the ticket was 100 euros, and today it’s 130 euros — you thought it was a price increase, but in fact, it was a tailored price for you after the algorithm had « observed » your behavior.
When you book a hotel on Booking, the price on your phone may be completely different from the price on your friend’s phone. If you use an iOS phone, the price you see may also be more expensive than on an Android phone. Uber also automatically raises prices during rush hour and at night. Have you ever considered why this happens?
The reason is that in this era of the digital economy, many platforms no longer use traditional fixed pricing, but instead use dynamic pricing strategies. This strategy uses complex algorithms to flexibly adjust the price of a product or service by analyzing factors such as market demand, inventory levels, competitor pricing, and consumer behavior in real time.
You may not notice, but in fact, your every move is being recorded and analyzed by the platform, and eventually becomes a « clue » used to determine the price. The algorithm is like a silent detective, watching you and then working behind the scenes.
-Clue 1: How many times have you seen this product?
If you frequently view the same item, the algorithm may judge that you « really want to buy it, » so the price might quietly increase a bit to test your psychological tolerance.
-Clue 2: What device are you using?
People who shop with Apple devices are often recommended more expensive products or shown slightly higher prices — the algorithm assumes you have « stronger spending power. »
-Clue 3: Where are you now?
Your location also affects the price. For example, in big cities or high-consumption areas, product prices are usually higher. What you see in Paris may be more expensive than in Strasbourg.
-Clue 4: When are you viewing it?
Some platforms secretly raise prices at night or on weekends, because users are more likely to place orders at those times. Food delivery platforms raise prices on rainy days because you don’t want to go out.
You may not notice any of this, but the price you see is no longer the « market price » — it’s your « exclusive price. » So is this practice fair and reasonable? Is it considered “price discrimination”? Technically speaking, this approach is not illegal. It uses publicly available data and user behavior to make dynamic price adjustments through machine learning and big data analysis. However, this lack of transparency may leave users feeling dissatisfied, and more seriously, it may deepen social inequality. Users with weaker financial ability who lack price awareness or technical tools may be repeatedly “harvested” by the algorithm.
As consumers, we can start paying more attention to these things, making it harder for algorithms to predict us. We can use incognito browsing mode when visiting websites, regularly clear our cache and cookies, and use more price comparison websites to avoid falling into the algorithm trap of a single platform.
In the world of algorithms, we think of ourselves as « rational consumers, » but in many cases, we are just targets being « pushed » by data. Algorithms are no longer just technical tools — they have quietly become part of market competition, consumer decision-making, and even the thickness of your wallet. In this reality, what really matters is not whether we can understand the algorithm’s code, but whether we can maintain enough awareness and judgment.
Consumption has never been a neutral act. Especially in the digital economy, the information gap is a money gap.
