Algorithmic pricing is simply the use of computer programs to set prices. Many firms use these programs to set their prices real time like Amazon or Uber. Although it has been developed immensely nowadays and it has become very popular among the e-commerce platforms, it is quite an old phenomenon which finds its roots in the late 60’s. Computer programs are used to manage bookings and reservations since then. However, today we are talking about way more sophisticated algorithms which can predict your willingness to pay and can attribute you the right price. These developments bring a lot of concerns in terms of competitiveness of the market and price discrimination. In this article, I would like to show you the relation between price discrimination and algorithmic pricing by highlighting the importance of managing consumer data.
A Brief Economical Explanation
The effects of price discrimination in the market are economically ambiguous. It can contribute to social welfare by increasing the number of transactions relatively to the situation in which price discrimination is absent. However, this amelioration in social welfare doesn’t necessarily come from the increase of the consumer’s surplus, rather, it comes from the increase of the firm’s surplus. This brief explanation of the effects of price discrimination explains us the fundamental mechanism of algorithmic pricing: firms are more likely to set the maximum price that one is willing to pay (if that price is above the minimum price of the firm of course). This way, firms can increase their sales by offering everyone a price that exists in the limits of their budget and get the maximum revenue from each consumer. However, total price discrimination cannot exist because it is quite hard to predict one’s willingness to pay. At this point we have to face once again with the importance of data. In order to attribute the right price, we have to understand the consumer, analyse his behaviour on every single channel. Only this way we can predict his willingness to pay. Collecting and combining consumer’s data from various channels makes firms benefit from their pricing algorithm, in other words without having a 360° insight about consumers, pricing algorithms cannot work efficiently. They can still follow the predefined rules, compete with other firms’ algorithms and set prices accordingly. But they cannot succeed in price discrimination, they cannot benefit from the most profitable and interesting characteristic of themselves.
Connecting Data Is Essential!
Collecting and connecting consumer’s data is not only essential to create personalized marketing communications and to improve customer experience but is also essential to attribute personalized prices. Labrys helps firms to collect, process & build a 360° view of their customers in order to use these insights in many forms, like as an input for algorithmic pricing scenarios and thus allows them to monetize their data by building a complete architecture with correct applications for an integrated omnichannel data structure.
Contact us to discuss how to create a sound data driven marketing strategy and to get the maximum benefit from your existing applications such as pricing algorithms!