Next Wave: The perfect price discrimination
Big tech platforms across the continent are quietly deploying predictive software to shape consumer reality. Jumia, the pan-African e-commerce giant, relies heavily on personalised recommendation systems. The software analyses browsing behaviour, purchase history, and user preferences to tailor product suggestions in markets like Lagos, Nigeria.
The concept of perfect price discrimination, which involves charging each customer the maximum amount they are willing to pay for a product, has long been considered unattainable for businesses. However, with the advent of technology platforms that can access vast amounts of customer data, this idea has become a reality. A study by Consumer Reports in the United States found that ride-sharing companies Uber and Lyft charge different customers significantly different prices for the same ride, with a median price gap of around 50%.
These platforms deny engaging in what is now termed as surveillance pricing, which involves setting prices based on individual demographic or behavioral data. Instead, they claim that the software sets prices based on real-time market conditions and what it thinks it can extract from the customer at that exact second.
This dynamic is particularly pronounced in emerging markets in Africa, where digital platforms are formalizing previously informal economies. Ride-hailing services in countries like Kenya and Nigeria employ dynamic pricing software that adjusts both the passenger's fare and the driver's cut. The software aims to balance demand and supply by raising prices during high-demand periods and lowering them during quieter times.
This system is designed to optimize platform liquidity and revenue rather than maintain macroeconomic stability. As a result, drivers in Nigeria faced shrinking margins and lost control over their unit economics following a significant increase in petrol prices. In response, the Amalgamated Union of App-Based Transporters of Nigeria organized strikes, realizing that they are not independent contractors but rather variables in an optimization function.
The telecommunications sector also faces the implications of automated price discrimination. In Kenya, Safaricom, a telecommunications giant, has successfully leveraged predictive data analytics to personalize data and voice offers for its subscribers. Using a platform developed in partnership with Huawei called Idea-to-Cash, Safaricom dynamically matches customers with tailored packages based on their usage behavior, spending patterns, and real-time context.
This strategy has led to a doubling of conversion rates on targeted packages and a 90% reduction in time-to-market for new offerings.
Written by urgent.news from TechCabal's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
