Optimiertes Pricing durch Machine Learning im E-Commerce

Optimised pricing through machine learning in eCommerce

The use of machine intelligence is growing rapidly and can be witnessed not only in relation to product classifications. In the pricing sector too, machine learning has now also become indispensable.

Big data generates far more comprehensive data than can be processed manually. Solutions based on machine learning provide a much-needed approach to performing complex analyses both quickly and cost-effectively.

To what extent does machine learning actually influence the pricing sector?

Machine learning as a challenge

Machine learning represents a new method of analysing data faster and more efficiently. Contrary to the traditional manual methods, this data is collected, processed and evaluated in large quantities. By “feeding in” raw data, machine learning procedures independently explore the correlations and patterns existing therein. This in turn makes faster decision-making easier.

The evaluation of complex analyses thus becomes highly simplified for companies.

Machine learning as a trending topic in eCommerce

Dynamic industries in particular, such as online retail must quickly analyse data streams. Whether Amazon or eBay – major online retailers are already demonstrating how machine learning can be used advantageously.

Artificial intelligence at Amazon provides for optimised customer relationships and marketing activities. By improving understanding of your customers, you will adapt service to customers’ wishes. The end results will be personalised product recommendations or individual product advertising, for example. eBay also offers its customers the best possible search results and a personalised shopping experience. The programs running in the background continuously explore the buying behavior and the buying motives of each online shop visitor and thus predict their future purchases.

Optimised pricing through machine learning in eCommerce

The making of predictions is only one goal in the use of machine learning. To be able to say what will happen, it is essential to know what has already happened in the past. Only then can decisions be made as to which recommended actions are the optimal solution. The analytical models will then build upon one another. (Source: Self presentation in the style of netz98)

The application of artificial intelligence in price management

Now as ever, large volumes of data still remains the biggest challenge to pricing managers.

In an interview, the Professional Pricing Society expert Alex Shartsis criticises the fact that too few companies utilise their existing data to determine their pricing strategy.

Although the need is indeed recognised, most of them lack the appropriate software service solutions (SaaS) or the required specialists. The latter exist so far only sporadically, but are being enticed away by bigger concerns like Google, Amazon or Netflix.

Because an in-house setup of these technologies is difficult and can not be accomplished without data specialists, companies, according to Shartsis, should consider outsourcing machine learning processes. Our Business Intelligence software blackbee represents just such outsourcing: Our self-learning algorithm collects large volumes of data from the Internet and calculates from this the relevant prices and product data of your competitors. The software enables you to carry out a comprehensive market and competition analysis.

The pricing analyst of the future

Even if machine learning greatly simplifies data evaluation, pricing experts will still remain indispensable.

There will still be an expert present who will monitor the analyses and avert serious consequences, such as the loss of profit through false predictions. In fact, in the future there will be an interplay between the mathematical processes of the machine and the creative performance of man. The pricing analyst will no longer have to deal with “tedious” processes as these will become automated. This will thus enable him to concentrate on other tasks such as strategic planning.

Changes in pricing through machine learning

To make price management more efficient by increased productivity, a focus on data will be required. In the future, the entire pricing sector will use more and more scientific methods and mathematics to shape its decisions.

Based on data science, measurable systems will be initiated, which will then automate processes themselves. At the same time, there will be teams with increasing responsibility for the supervision of machine learning procedures.

The following developments are emerging in pricing for the coming years, which will be of interest to you either as a retailer or manufacturer:

  • Artificial intelligence will not be replacing experts, even in the future. On the contrary, man and machine will be mutually complementary to one another in coping with the data jungle.
  • Pricing professionals will increasingly use scientific methods but still continue to play a highly responsible role.
  • There is a need for stronger focus on data in decision-making in price management. Tools like our blackbee Business Intelligence Suite help to collect and evaluate large volumes of data.

Would you like to optimise your price management using valuable data? Test blackbee now!