Intelligente Preisoptimierung: Abschriftenoptimierung & Bestandsoptimierung mit prudsys, Spezialist für KI im Handel: Dynamic Pricing, Personalisierung & Recommendations

Pricing processes in omnichannel retail are extremely complex and rife with influencing factors. Prices on the market change constantly and the number of sales channels is always increasing. The fashion industry in particular is characterized by an extremely volatile market environment. Gone are the days when summer or winter clearances controlled when retailers made cuts. Nowadays, fashion companies are constantly changing the prices of thousands of products.

In the fashion industry there is the added factor that almost all items come in different colors and sizes. This increases the number of price variations immensely. In addition, fashion is a seasonal business in which collections are regularly changing. Up until a few weeks ago, winter boots were still in high demand. The closer it gets to spring, however, the less willing your customers are to pay full price for winter boots. So, should we just slash the entire winter collection by 50 percent and be done with it? We are confident that there are better pricing strategies. In this article, find out how to put out price reductions that optimize both earnings and your stock.

Automated pricing – what’s behind it all?

The earnings potential of the clothing industry is significant for the retail business – the industry registered around 12 billion euros in annual turnover in 2017. You can already use artificial intelligence (AI) to automate all pricing processes. Not only does that save on resources but you can also find the optimum price for every product at any time and via any sales channel.

The fair market price of an item is based on customer price acceptance, available offers and demand in general. The AI solution also includes influencing factors such as competitor prices, weather, regional and temporal factors and purchasing conditions. Pricing algorithms of an agile AI solution automatically make price decisions in split seconds based on these factors. In the fashion segment in particular, customers like to browse and compare deals, which can lead to high bounce rates. With a current, fair market price you remain competitive.

Depending on the type of products, in other words price-sensitive or not so price-sensitive, limited or unlimited life cycle and your objective, the appropriate pricing algorithm is used.

What are the benefits of automated pricing?

Artificial intelligence in the form of automated pricing gives you the following notable advantages:

  • Reduction of manual effort = increased efficiency through automation
  • Category managers can instead invest their time in strategic pricing and product range decisions
  • Increase in sales, turnover and earnings while complying with margin constraints
  • Compliance with defined sales quotas to avoid markdowns
  • Stock can be sold by a certain time
  • Increase in the speed of response to changing environmental conditions, e.g. purchase conditions, competitive offers
  • Special retailer conditions are automatically taken into account when calculating prices, e.g. price corridors, delivery availabilities or various conditions depending on the customer group

How does automated pricing optimize markdowns in the fashion business?

The topic of markdown pricing plays a central role for you as a fashion retailer in order to avoid margin and profit losses. The fast pace of the fashion industry and the number of fashion products make it necessary to constantly optimize the prices of fashion items. Major reductions at the end of the season are water under the bridge.

To optimize markdowns, the AI solution creates the prices of the items so that the stock is sold out by a certain target date. The pricing algorithm is geared towards achieving the best possible price for the fashion item along the product life cycle at any time at the respective location. That means that even omnichannel retailers are in a position to deliver the right price at the respective touchpoint – whether it’s in the online shop, in the store or in the shopping app.

The pricing algorithm uses the stock and the current/historical data to predict the realistic sell off date for each product. Depending on how much the prediction differs from the sell off date set by the category manager, the pricing algorithm adjusts the price up or down.

The AI solution optimizes the earnings of an item during its life cycle while reducing markdowns at the same time. You specify how often the prices should be updated – weekly, daily or several times a day.

Where does markdown pricing still pay?

Almost every retailer, regardless of the product range, is anxious to optimize markdown pricing. In particular, retailers that sell products with a short life cycle or products that deteriorate quickly benefit from automated price optimization. The same is true for grocery retail and its fresh items. According to a study by McKinsey, around 40 percent of turnover in the grocery retail industry can be attributed to fresh products. Your challenge as a retailer is on the one hand to guarantee the freshness of the products and on the other hand to not neglect your margins. An AI solution that adjusts the prices of each product based on shelf life, inventory and demand, minimizes markdowns and optimizes your earnings.

Would you like to know more about markdown pricing? Join one of our webinars (in German) or book an appointment.