Artificial Intelligence and Its Role in Price Optimization

If I want my business to succeed, what am I to do?

You likely toss and turn all night long trying to find an answer to that query. One strategy that might aid in the expansion of your business is price optimization.

You may and should put money into enhancing your marketing, inventory management, and in-store experiences. However, consumers are more influenced by a product’s price when deciding which store to patronize. If you want proof that pricing is king, just look at the research done by Deloitte and PricewaterhouseCooper. Consequently, that is where you need to begin.

Optimal pricing attracts as much as 60% of customers. To maximize profits while simultaneously satisfying clients, artificial intelligence (AI) may assist you in optimizing pricing in real time. As a result, your price managers will be free to focus on more strategic activities, which will ultimately lead to additional profit.

Algorithms Propose Optimal Pricing

First, we need to figure out what the best pricing is.

You may set these prices without alienating your consumers, increasing your marginality, or reducing sales of other products in your portfolio.

Your managers would need extraordinary speed, intelligence, and computing prowess to determine ideal pricing for a thousand goods every week — if not every day. Alternatively, have artificial intelligence installed.

There are typically many steps that retailers take when they decide to use AI price optimization. As a cherry on top, they learn to determine optimum pricing per consumer in addition to stock keeping unit (SKU), product portfolio, channel, and point of sale.

Maximizing profits is the result of using optimal pricing across the board. Optimizing prices may increase sales by 24.7 percent and income by 9.7 percent.

Why does AI work so well?

Algorithms that learn on their own may sift through mountains of data, consider an infinite number of possible prices, and then propose the best one at any given time.

When recommending individual prices that optimize revenue and sales of the entire product portfolio, algorithm-powered models take into account thousands of hidden relationships (such as how a change in price for one product can impact sales of multiple other items sold by the retailer) among the products in the portfolio.

Awaiting the Arrival of AI-Assisted Pricing

In most cases, five stages are involved for shops looking to optimize their pricing using AI:

1. Data

In most cases, the algorithmic model requires comprehensive, high-quality, well-structured data that covers a minimum of three years. There are a few choices available to retailers if it is not feasible to recover or standardize the lost data: wait a certain amount of time (at least one year) and gather the data in one format, or purchase or model it.

2. Construct or Purchase

Modern retail success demands a blend of core competencies — like negotiating buy prices with vendors — and supplementary competencies — like determining ideal pricing, which calls for a wholly distinct set of abilities.

In such a case, some companies, like Amazon, put money into creating an internal price center. Other companies, such as Target or Metro, establish startup laboratories to evaluate and adopt new ideas.

Partnerships between independent firms with market traction and companies with less capital are common.

3. Product Suggestions for AI Pricing

Price suggestions driven by algorithms aren’t necessary for every product in your portfolio. In what ways are these goods identifiable?

In most cases, algorithmic suggestions are required for private label goods, which are unique to your business and may be offered at a higher price point than rivals’ products. Items that you provide alongside your rivals but which do not need the cheapest price to attract customers might also benefit from AI ideas.

4. Team

Your pricing managers must become proficient in interpreting and relying on the pricing system’s suggestions before it can be implemented. Keep in mind that your team members have complete control over the pricing process. If they are unsure about how an algorithm will perform in practice, they might test it with certain parameters or limitations before implementing it.

5. Upkeep of the system

Your system needs up-to-the-minute information about your pricing strategy and company objectives to generate the most relevant scenarios. It is important to keep an eye on its progress and make adjustments as you go along. Not only that, but the system needs to have all the necessary technological developments to maintain productivity.

Conclusion

Envision a future where you make the most money possible with every product you sell. With this extra time, your pricing managers may devise better pricing strategies and negotiate better purchasing prices. You consistently get repeat business from clients who prefer you over your competition. A steady expansion characterizes your company’s trajectory. Thanks to AI, that future is rapidly approaching.