Increase demand and customer loyalty: use self-learning algorithms and external data to achieve better results in promotion planning and implementation.
Promotions have been part of the everyday pricing policy in retail for years. Particularly the popularity of price promotions has recently increased significantly. Retailers use instruments such as special offers, sets or coupons to respond to temporary fluctuations in demand. However, the user often lacks knowledge about the efficiency of past promotions. Price promotions can lead to customers purchasing more in the short-term but then changing brands, categories or even shopping locations. In the long term, promotions even lead to a change in loyalty. Information about the different effects of promotions are essential success factors when it comes to planning and managing future promotions.
aifora Promotion Planning
aifora’s promotion planning relies on state-of-the-art data mining technologies and takes external market data into account. The software automatically identifies campaigns and determines optimal recommendations for future actions. Mathematical forecast models illustrate the calculated effect of promotions per country, store or channel to the user. Using defined KPIs, the user can also compare various promotions with one another. In addition, relevant evaluations with regard to performance and costs provide the necessary transparency in performance measurement.
Key Feature 1 – Campaign Calendar
The calendar function provides the user with a comprehensive campaign and promotion planning tool. The user can quickly and easily create campaigns, specifying the type, the budget and the start and end dates. The concrete design of the events is based on a rolling, interdisciplinary process. The system automatically informs the users involved about the current progress and thus guarantees a target-oriented planning of all promotions.
Key Feature 2 – Shopping Basket Analyses
With the help of intelligent shopping basket analyses, the user can understand the typical shopping behavior of customers. The software finds products that are often purchased together. It also identifies key products that bind customers to the company and useful article combinations for cross-selling campaigns. Taking into account purchase probabilities, interconnection and cannibalization effects, the compilation of promoted articles is improved and thus the overall pricing is optimized.
Key Feature 3 – Result Forecast
New price campaigns often lead to great uncertainty due to a lack of forecasting ability. The promotion planning of aifora offers the possibility to simulate different scenarios and to compare the predicted results with regard to the financial objectives. The forecasting algorithms analyze the current performance and suggest ideal promotions at all times.