Consistently making the right pricing decisions is one of many things that can pave the road to success. Identifying demand and elasticity in your stock—as well as any patterns bet ween certain products—can often take your business to the next level in terms of outreach and financial objectives.
Identifying a Strategy
Before actually implementing AI to inform pricing decisions, it’s important to lay out your identity and its impact on your pricing. Your strategy could range from having the best prices and discount offers to boasting a range of quality-driven premium products—a clear strategy is one of the signs of an effective pricing system.
Next, identifying your competitors and monitoring their pricing decisions and strategy can offer a lot of hints for your own strategy. It is very important to know where you stand amongst your competitors (and who they truly are). Another crucial aspect is knowing your products. Key-value items (KVIs)—which influence demand and your brand’s image—could be the perfect place to start when considering setting attractive prices. The important part is using KVIs to attract consumers to your business over your competitors.
Building a Pricing Strategy
Implementing a data-driven pricing system requires some preparation and forethought. More importantly, having a large, reliable dataset is the first step to building your strategy. Once that’s in place, retailers need intricate pricing software to make sense of the data and offer insights. With these insights and some preparation, a relevant team can then make pricing decisions with their business goals in mind.
1. Big Data
Demand-based pricing strategies can’t be built in a day, and in order to generate reliable insights, a retailer should have a large collection of data to begin with. The most important and possibly toughest task when working with Big Data is organizing all the different types of data available. Structuring and reorganizing data collection and storage helps your advanced software find patterns that influence pricing insights.
2. Artificial Intelligence
In the modern retail sphere, making pricing decisions quickly but effectively is a priority. As a result, the traditional approach of having data analysts sift through mountains of data is simply not enough. Artificial intelligence software can analyze huge amounts of data and offer insights at a greater speed and precision than humans. These insights can then help answer a lot of questions regarding strategy, such as your competition or optimal pricing positioning for certain items.
3. Key Personnel
Big Data and Artificial Intelligence aren’t enough; to wrap everything up, you need people that can supervise the software and follow through with pricing decisions. Transitioning to such a role entails gaining a certain understanding of the tools and their decision-making process. At the end of the day, while AI does all the dirty work and comes up with insights, the supervisors have the final say in the decision-making process. It might take some getting used to, but integrating and building experience with artificial intelligence can elevate a retailer’s pricing strategy and brand perception.