Maria Jose Guerrero
The retail landscape is undergoing a radical metamorphosis: the end shopper is no longer always a human behind a screen, but an advanced algorithm executing purchasing decisions. The advent of generative artificial intelligence has ushered in a new era where virtual assistants evaluate entire catalogs in fractions of a second. For ecommerce leaders, this means traditional sales tactics are losing ground to the need for structured data and a flawless pricing policy capable of convincing these new shopping machines.
Table of Contents
- What is agentic commerce and how does it change the game?
- The tech ecosystem: the race among giants
- GEO: the new frontier of organic visibility
- Pricing intelligence for AI: adapting your strategy
- Practical case: from manual reaction to automation
- Frequently Asked Questions (FAQs) about The rise of agentic commerce
- From manual reaction to proactive strategy
What is agentic commerce and how does it change the game?
Agentic commerce is a digital retail model where artificial intelligence agents act as intermediaries between the consumer and the store, autonomously searching, comparing, and selecting products based on predefined parameters. This completely transforms visibility and pricing strategies.
Delegating purchases to AI is gradually eliminating the emotional factor from the process. In fact, data already reflects this behavioral shift: according to recent reports, 28% of advanced generative AI users make fewer impulse purchases. Additionally, 31% of these profiles look for much more detailed technical information about products than they did before using artificial intelligence. Furthermore, recent industry forecasts for 2025 indicate that AI-driven agentic transactions are expected to influence over 20% of digital retail sales in the US and UK markets. In this landscape, mastering what pricing intelligence and price monitoring are becomes a critical survival need, as algorithms prioritize consistency, availability, and objective competitiveness.
The tech ecosystem: the race among giants
The development of these AI shopping agents is not a future promise; it is a reality driven by major tech corporations competing to be the gateway to consumer spending. Understanding the moves of these key players is vital to adapting your ecommerce business strategy:
- Google and search integration: The transition toward conversational models is reshaping SERPs with experiences like AI Overviews. Understanding AI in ecommerce and Google AI mode is essential, as its algorithms synthesize reviews, prices, and availability into a single response panel.
- Microsoft and the enterprise environment: With Copilot tools geared toward the B2B and B2C sectors, Microsoft is redefining retail by creating workflows where AI actively assists in the supply chain and the end customer's shopping experience.
- OpenAI and the consolidation of assistants: Although recently OpenAI rethought its strategy and ruled out integrating direct payments in the short term, its focus remains on enhancing ChatGPT's ability to act as a hyper-precise recommender and product comparator.
- Meta and automated social commerce: The integration of smart agents into WhatsApp and Instagram aims to close the sales funnel directly within chats, based on the user's history and the seller's catalog.
GEO: the new frontier of organic visibility
While traditional SEO aimed to rank links, Generative Engine Optimization (GEO) aims to rank answers within language models. To appear as the top recommended option when a user asks their AI to find "the best 4K monitor for the money," retailers must ensure their product data is perfectly structured.
Catalog clarity is non-negotiable. Conducting a competitor catalog analysis regularly allows you to ensure that your descriptions and technical attributes surpass those of your rivals in semantic richness.
"In agentic commerce, we are no longer just convincing a human buyer with emotions, but a mathematical algorithm that evaluates a product's true value in milliseconds. Precision is our best marketing campaign."
— Antonio Tomas, CEO of Minderest
Pricing intelligence for AI: adapting your strategy
Pricing for algorithms requires leaving manual price setting behind. When an AI agent compares your store with five competitors simultaneously, a difference of a few cents or a poorly communicated promotion can exclude you from the final recommendation.
To stand out in this environment, having centralized strategic control over several disciplines is vital:
- Dynamic monitoring: Understanding what repricing is and when to apply it allows you to react to market movements within your safety margins.
- Promotion analysis: AIs discount coupons and special offers. Using promotion intelligence solutions helps map out competitors' campaigns.
- Ethical and legal tracking: With the rise of AI, concepts like surveillance pricing are under intense regulatory scrutiny in the US and Europe. Extreme personalization must be balanced with transparency.
If your ecommerce still relies on fragmented spreadsheets to make pricing decisions, you are at a clear disadvantage in an automated ecosystem. Request a demo today and discover how to transform your competitive analysis.
Practical case: from manual reaction to automation
Imagine a major tech retailer expanding its catalog by adding hundreds of new SKUs every quarter. Historically, the pricing team spent weeks trying to manually map these products against competitors, losing initial sales due to uncompetitive pricing.
By implementing an automated solution like Minderest, a centralized workflow completely transforms this dynamic. For new products that do not yet have a market "match" due to a lack of history, the platform immediately applies business rules based on costs and the retailer's target margin, ensuring the product goes on sale profitably from minute one.
Later, through periodic scans (usually daily or twice a day), the system tracks the appearance of these items in competitor catalogs. Once detected, the tool cross-references the data and generates strategic price recommendations. The team shifts from executing tedious browser searches to simply approving pre-configured strategies, protecting the margin and saving vital time.
To dive deeper into how these mechanics will define the industry's coming years, we recommend checking out our report on pricing trends for 2026.
Frequently Asked Questions (FAQs) about The rise of agentic commerce: pricing strategies for new AI agents
How does agentic commerce affect consumer behavior?
It drastically reduces impulse buying. Consumers delegate research to AI, resulting in purchasing decisions based on objective data, exact technical specifications, and the best historical value for money of the product.
Why is traditional SEO not enough for AI?
Because generative AI doesn't work by showing a list of links (like traditional SEO); instead, it synthesizes information to provide a single answer. If your product's price and technical attributes are not structured and monitored, the AI simply won't recommend you.
Do pricing intelligence tools adjust prices in real time?
In more robust enterprise B2B and B2C environments, optimization doesn't aim for a chaos of second-by-second changes. It relies on periodic tracking (daily or twice a day) to guarantee margin stability, automating the workflow so the team can seamlessly approve strategic changes.
How do I price a new product for AI algorithms if I have no historical data?
The best initial strategy is to rely on strict internal business rules (acquisition cost plus target margin). Once the product gains traction and appears on the competition's radar, market-based price optimization kicks in.
From manual reaction to proactive strategy
Ecommerce is no longer a static storefront; it has become a living ecosystem, continuously crawled and analyzed by machines designed to find inefficiencies. Facing agentic commerce by trying to adjust prices manually or reacting defensively is a losing battle that drains your team's profitability.
The true qualitative leap lies in anticipation. Adopting periodic monitoring technologies and automating the response cycle allows brands to stop worrying about data extraction and focus on business strategy. If you want the new algorithms to choose you as the winning option, you must provide them with the right data at the exact price. Take the step toward absolute control of your catalog and discover the full potential of price intelligence to lead the retail of the future.
Find out how Minderest can take your business to the next level.
Contact our pricing experts to see the platform in action.
Related Articles
New EU €3 Customs Duty: Impact on Pricing and eCommerce Competition
The e-commerce landscape in Europe is on the verge of a structural transformation. The recent approval of the €3 customs duty for packages originating from outside the European Union marks the end of...
AI Agents and Holiday Season: How to Adapt Your Pricing Strategy
Holiday season planning used to revolve around creative campaigns, emotional storytelling, and optimizing the user experience. However, a silent revolution is changing the rules of the game. The rise...