Pricing is the most effective way to raise the Net Profit. A 1% increase in the price equates to a 10% increase in Net Profit (McKinsey). The key for a robust pricing strategy is to switch the pricing paradigm and charge what every customer is willing to pay, not a blanket charge, and the key to that is AI.
AI is critical in outperforming competitors in the pricing domain, particularly compared to the market leader Excel, which accounts for 97% of all pricing decisions.
AI as a Pricing Solution
The history of AI started in World War 2, and recent progress has enabled us to leverage AI as we see it today.
AI has allowed the pricing domain in B2B business to flip the pricing paradigm and to look at the customer's willingness to pay using the companies' internal transaction data by:
- Micro-segmentation, where customers are grouped based on a similar behaviour pattern
- Micro dynamic, analysing the single customer behaviour changes over time
- Pricing alignment, optimising the price according to the customer price acceptance
- Feedback loop, analysing customer’s acceptance and behaviour changes and continually optimise
Role of AI Pricing Tool
The role of an AI application is to work alongside the pricing team and remove the mundane element of analysing every price manually, which can take months.
Businesses need to consider the following, for efficient use of AI Pricing Tools:
- Data: Ensure good quality data is available; AI initiatives can fail because of poor data.
- Technology: Leverage the cloud
- Humans: All disciplines must work together to make it right
Not everything that says AI is AI check!
Developing an AI pricing solution should be considered as a journey. The good news is that the data set used by the AI pricing tool can also solve other related problems, i.e., identifying churning customers. AI pricing tools can deliver a 3% uplift in your gross margin and raise Net Profit by 10%.
Start the journey and learn.
This article was contributed by our expert Alan Timothy
Frequently Asked Questions Answered by Alan Timothy
Q1. What is the major impact of artificial intelligence in the pricing domain?
There are many improvements compared to Excel, where 97% of the pricing is managed today. The more complex the pricing decision is, the more significant the impact, whether complexity is measured by the number of customers and products or the variables that can impact the price.
Using the power of AI allows you to flip the pricing paradigm and calculate what a customer is willing to pay for the product, updated live, instead of a static calculation managed in a conventional spreadsheet.
The heart of AI is a feedback loop that will automatically review the price recommendation and adjust it based on the customer behaviour changes and the risk associated with the price change. The net result is less money left on the table and increased profit.
Q2. How do we integrate AI into the pricing domain?
Price is usually displayed in the ERP system and provides the most recent price for a given product and customer. It can also be shown in the peripheral system like CRM or a Quoting Tool if it's considered part of the sales process. However, the price calculation is usually done outside the ERP or CRM and uploaded back.
AI solution replaces the pricing calculation task and leverages companies’ same integration protocol. Therefore, the AI output can be tailored to the same format used by the business, mirroring the existing upload template. And more importantly, it does not require heavy investment to modify the current ERP or CRM APIs, which can be very costly for some platforms.
Q3. What is a price optimisation strategy?
Price optimisation, is finding the sweet spot between the customer's willingness to pay and a target product volume.
You can choose to sell a lower volume of product at a high price, i.e., Marks & Spencer, or sell a lot at a low price, i.e., Aldi, each focused on a different customer group. If an item is priced too high, it may sell in small numbers or not sell at all, while if the price is reduced too much, you may run out of stock or have a negative profit.
Once the business knows what margin volume it wants to achieve, it uses a price optimisation formula based on the overall demand for its product and its level of competition.
Finding the perfect balance between profit and value is essentially what price optimisation is all about. Because the relative values of goods and services constantly change, this is a never-ending task for most businesses.
Q4. What strategies should be adopted by companies to use AI successfully?
The key to all AI is data quality; quality is more important than the volume of data.
The good news for AI in pricing is that the data comes from the transaction file from the ERP. And, as it is used in preparing accounts, the quality is good. The further away from the transaction data, the quality of the data can deteriorate. The sooner a company starts putting effort into the data quality, the better the results will be when using AI.
Start small, take small steps, and learn. Pricing is a critical part of a business. Once a partner has been selected, it is best to start with a pilot, with a limited number of customers and products.
One of the benefits of AI is the speed and integration of the feedback loop so that the impact can be visible in weeks. Based on the results, the company can slowly scale in a controlled manner by adding customers and products, letting the business gain the benefits without the risk.
