More and more consumers are looking for a good price when shopping. The Düsseldorf-based AI company aifora helps fashion retailers to monitor the prices of competitors in order to be able to optimally adjust the prices themselves.
Consumers are increasingly price sensitive
Price has always played a key role in fashion retail. It is an important criterion for the end consumer’s purchasing decision and it determines the retail margin. But today’s consumers want to find the best price for them. They used to do this in brick-and-mortar retail, and they do it even more under the simplified conditions of the Internet. In view of inflation and rising energy prices, more and more people are paying attention to cheap prices, so the importance of price comparison portals and apps for price comparisons is growing. The fashion trade is not spared either: a whopping 71 percent of consumers stated in surveys that they compare prices before making a purchasing decision in the clothing segment.
But as a retailer, how do you keep track of what prices are currently being offered on the Internet for products that you have in your range yourself? What AI solutions are there in the field of automated pricing?
Retailers need the same price transparency as consumers
The problem is that when the end consumer makes his purchase decision, he can first compare the prices in stores. But how can retailers and brands adjust their pricing when the competition’s prices go up or down? Retailers and brands often do not have the same price transparency as consumers. This task of observing the competition can hardly be managed manually. Coupled with a solution from aifora, however, this information can be collected and used automatically. The challenge for fashion companies is therefore to know the prices of all relevant competitors for a large number of products in real time and then to use this data intelligently for their own pricing in a next step.
Competitive pricing: competitive pricing
Competitive pricing is a pricing concept in which retailers use the prices of other market participants as a benchmark for their own pricing. Often referred to as competitive pricing, this strategy is part of the broader concept of market-based pricing.
Looking at competitor prices helps brands understand the options in the market. From there you can assess how your own product is positioned in comparison to others in the market. In this way, the positioning, value proposition and price are aligned to improve customer perception.
Implementation of an AI-supported competitive pricing strategy
The process of implementing an AI-supported competitive pricing strategy starts with the question of who the relevant competitors are. The answer to this question can look different down to the level of individual products and should therefore be defined granularly at category level. Then, in the next step, you can start monitoring the competition prices. The following aspects should be taken into account:
1. Obtaining the data:
The data can be obtained via a so-called scraping service, which extracts the price information from the website data of other market participants such as dealers or marketplaces. It must be determined at what intervals this query should be made, or how quickly you are operationally able to adjust prices yourself.
2. Aggregation of data:
Due to the sheer amount of data collected (big data), the second step is to aggregate this data in order to make it usable for further follow-up processes.
3. Visualization of the data:
In order to be able to effectively keep an eye on the competition prices, the last step involves the helpful visualization of the aggregated data, for example in the form of dashboards.
Integration of competitive prices into AI-supported pricing solutions
But that’s not all. Once the data is integrated into the aifora system, it will also be a question of using it sensibly in the future. The AI-based solution for automating price decisions via the aifora platform can now pursue competitive pricing strategies. To do this, it is necessary to develop a flexible set of rules with which the individual requirements of a company can be taken into account in the algorithm. Such sets of rules can be, for example: the price should be five percent cheaper than that of my cheapest competitor, the price should be seven percent cheaper than the average price, or the price should be at least five percent cheaper than that of the cheapest competitor as long as the margin is not less than 50 percent falls.
With an integrated solution, retailers can not only create full transparency about the prices in the relevant market segments, but they can also make better decisions on this basis and even automate them according to an individual business strategy.