Retailers always look for new ways to ameliorate their operational efficiency as the ROI is highly dependent on how their processes work. Contemporary retail environment has become more competitive than ever and that’s why they need optimum optimization of several aspects of their business. This includes but is not confined to logistics, CRM and marketing. In this post we will see why AI (artificial intelligence) is the future of price optimization in retail and how to get started with it.
- First things first: Manage Data
If you are considering to include AI in your retail price optimization strategy, pat your back for the decision, but that’s not it. Data is the foundation of any retail price optimization strategy and that is why you need to manage your data well. Algorithms will require dependable data for effective pricing recommendations and predictions.
So, what does dependable data refer to? Dependable data is data that is useful, well-structured, fresh (so that it is relevant) and high quality. Also, very important it must be in a single format. That’s usually the problem with existing data. It is unstructured, irrelevant because it is old and not in a single format which is extremely necessary. So, if you already have some data, put in efforts to make it eligible for AI.
- Use a Robust AI Price Optimization Tool
Here you have two options- either develop an in-house algorithm or outsource it to a service provider that provides AI powered price optimization in retail solutions. The first one is not recommended because it will require a hefty investment, necessary resources and most importantly expertise. You might end up spending a huge amount of money on creating the infrastructure, hiring, and training without achieving anything. Getting in touch with a reputed price optimization service provider is your best bet if you want to get started with AI for price optimization.
- Don’t Fully Roll-Out without a Pilot
The best way to check the effectiveness of the AI price optimization tool, you need to launch a pilot first. The algorithm also needs training which is based on the retailer’s data before the pilot is launched. Once you feel that all predictions are correct, you can go ahead with the pilot and once the pilot launch results are also up to the mark, you can roll it out and have fun.
Hope you found the post useful. WebDataGuru is a renowned name in the domain of price optimization. Feel free to write in to us for more queries.