Earlier, using analytics and AI for pricing required a team of technical experts. These experts were responsible for coding algorithms, building dashboards, and translating raw data into actionable insights. Such pricing tools were limited to subject matter experts.

‍

This slow progress led to suboptimal outcomes as they relied on inaccurate data. As markets change and become more dynamic, businesses need something substantial to hold their ground. At this time, the unavailability of technical experts may make it worse. Hence, the modern AI models take charge.

‍

Now, AI and pricing analytics are accessible to all business users. Anyone can operate the software packages without being a subject expert. This allows more companies to adopt modern AI pricing solutions and gradually transform their pricing affairs.

‍

In this blog, we’ll discuss these two key areas where AI pricing and analytics have significantly impacted.

‍

‍

What does Intelligent Pricing mean Today?

‍

"Intelligent pricing" is a customised strategy that adapts to a customer's willingness to pay. It considers factors like the time of day, location, real-time demand, and purchase history.

‍

Unlike traditional rule-based methods, it relies on data and advanced algorithms. These tools use customer insights to provide dynamic and personalized pricing. This approach ensures prices are contextual and relevant.

‍

Demand and market shifts happen during a recession or holiday season. Both need you to be prepared with a strong pricing foundation. Pricing during a recession could be challenging. So is managing pricing during the peak holiday season. You need to make prompt and accurate pricing decisions after analysing data. This is how analytics and AI in pricing could help. With it, you can tap into customer’s willingness to pay and capitalise during the seasonal peaks. You can even stay afloat with healthy returns during economic turmoil.

‍

Also Read: What pricing strategies are best during high inflation rates?

‍

1. Easy User Experience to Handle Complex Tasks

‍

Technical expertise is no longer a barrier today. With the advancement of AI, you can simplify most rote tasks through built-in algorithms without any expert guidance. These tools have intuitive interfaces that allow non-technical users to drive powerful insights.

‍

Imagine a tool where you input your business goals, and the AI takes care of the heavy lifting—whether it’s crafting dynamic pricing algorithms or predicting future trends.

‍

A pricing manager without a coding background can now implement sophisticated pricing strategies by using AI-driven tools. Further, these platforms allow users to focus on their core expertise: understanding their business and customers.

‍

Here’s a simple example of how SYMSON’s  predictive AI pricing model works:

A business with excess stock might lower prices to attract more customers. This can increase sales and free up warehouse space, reducing pressure on working capital. The next day, your predictive algorithm might detect high online traffic for a product. This could prompt a slight price increase to boost profitability.

‍

Along with all this, you must also know things like how seasonally sensitive your market is or what are your plans for an upcoming major holiday.

‍

Also Read: What is Stagflation? How to Beat Stagflation with Pricing?

‍

2. A Slight Change in Skill Requirements

‍

The evolution of analytics and AI in pricing changed a professional’s skill set. Instead of acquiring deep technical knowledge, you must understand your key business questions. Then, you can strategically train the AI pricing tools to address those questions.

‍

It’s not about being an expert coder, it’s about asking the right questions that matter:

‍

• How can AI optimise our pricing to improve profit margins?
• What customer insights can analytics reveal to refine our pricing strategies?
• How can we predict demand more accurately to stay ahead of competitors?

‍

It’s critical to focus on the business challenges that matter the most. Then, using the power of AI to automate and manage all complex and rote tasks. This lifts the pressure off your team. You will then rely on accurate data and make price changes in a whiff. Time is money.

‍

‍

Disrupting the Pricing Domain with Explainable AI Pricing

‍

‍

‍

AI in pricing is no longer just smart—they’re now explainable. This shift has made pricing decisions more transparent, allowing businesses to understand the "why" behind every recommendation. Teams will access the insights into the logic behind the prices calculated. Likewise, pricing teams will continue to learn and train the model to be even better.

‍

Explainable AI fills the gap between advanced algorithms and human understanding. It makes complex processes easier to manage. With this clarity, companies can focus on what matters the most— driving growth, improving profits, and strengthening customer relationships. Pricing is no longer a black box—it’s a clear and actionable advantage.

‍

‍

‍