Introduction
For years, SEO was mainly about getting a page to rank and earn a click. Now, more users get an answer straight from an AI system that reads, compares, and recommends options.
It’s important to be cognisant of that shift because ranking is no longer the finish line. In many AI-driven experiences, the system tries to pick the best few results and explain why. If you are not in that short list, you may not get seen at all, even if you rank well in normal search.
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What Traditional Search Ranking Does
Traditional search ranking is built to show a list of links that match a query.
It usually works like this:
- A search engine crawls and indexes pages
- It matches the query to pages based on relevance signals
- It sorts results using many ranking factors
- The user chooses a link and clicks through
The goal is visibility in the results page so you can earn traffic.
What the AI Reasoning Phase Does
The AI reasoning phase is built to produce an answer, then recommend options that fit the user’s request.
Instead of showing a long list, it tries to:
- Understand the exact intent
- Apply filters and constraints
- Choose a small set of best matches
- Explain the choice
- Sometimes complete the task, not just recommend
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Example
User query: best trail shoes under $150 that are waterproof and in stock near me.
Traditional ranking may show pages that mention trail shoes, waterproofing, and price ranges.
The AI reasoning phase tries to solve the request:
- find trail shoes
- confirm waterproof
- confirm price under $150
- confirm in stock
- confirm availability for the user’s location
If any key detail is missing or unclear, you are less likely to be recommended.
Clicks or Influence?
If influence matters more than position, then you need to optimise for the AI reasoning phase because traditional ranking aims to get you high enough in the list to win clicks. If you are in the top results, you can still get traffic even if you are not number one.
On the other hand, the reasoning phase aims to recommend the best options for a specific person and situation. In many cases it returns a shortlist. If you are not selected, you may not appear at all.
What Are the Data Sources of the AI Reasoning Phase?
In the reasoning phase, the system does not rely on one source of truth. It combines multiple inputs.
Crawled Web Pages
This includes your site and other pages the system can access. It helps the AI understand:
- what you sell
- what category you belong to
- how you describe products and services
- how the market talks about your brand
Product Feeds & APIs
These provide current facts such as:
- price
- stock status
- delivery estimates
- product variants and sizes
- technical specifications
This layer often decides whether you are eligible to be recommended. A strong article will not help if the feed says out of stock or the price is above the user’s limit.
User Context
The system may also use context such as:
- location
- language
- brand preferences
- sizing needs
This is why two people can ask a similar question and get different recommendations.
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Is the Evaluation Process Active or Passive?
Traditional ranking sorts results. The reasoning phase works through the problem, but how?
Breaks the Query into Requirements
A single query becomes a checklist. For the shoe example, the system can treat these as required:
- waterproof
- under $150
- trail running use
- in stock
- suitable for the user’s location
If your product pages or feeds do not clearly provide these facts, you will not make the cut.
Checks Commercial Fit, Not Just Text Match
Traditional ranking can reward pages that mention the right terms. The reasoning phase checks whether the product solves the real problem at the right price, with the right availability, in the right place.
Often Picks a Small Shortlist
In traditional search, being fifth can still drive traffic. In the reasoning phase, selection matters more than ranking position. If the shortlist is three items and you are not in it, you lose the moment.
Real-time data can knock you out fast. If your inventory is backordered or your delivery times fail the user’s needs, you can be excluded even if your SEO is strong.
Does Agent Behaviour Change the End Goal?
Traditional ranking ends at the click. The user does the work. The reasoning phase can be the step before an AI system takes action. If the system believes it has found the right option, it may move from recommendation to completion.
That can include:
- navigating your site
- filtering products
- filling forms
- starting checkout
This only works when your site data is consistent and machine-readable.
What to Do If You Want to Win in the Reasoning Phase?
You will have to make your business easy to understand and easy to trust. How do you go about that?
Make Key Facts Obvious on Every Product Page
At a minimum:
- current price
- stock status
- delivery timeframes
- returns and warranty
- core specs that buyers filter by
Do not hide these in tabs, images, or vague marketing copy.
Keep Feeds Accurate and Complete
If you use Google Merchant Centre, retailer feeds, or ecommerce APIs, treat them like a ranking factor. Outdated price or inventory data makes you a bad recommendation.
Use Schema That Connects Your Entities
Basic markup helps. Connected schema helps more. Your brand, products, categories, reviews, and policies should link together in a way machines can follow. This improves clarity and reduces the chance the system guesses wrong.
Prove Claims with Evidence
If you claim performance benefits, show proof:
- test standards where relevant
- reviews and ratings
- clear policies
- third-party mentions that confirm credibility\
A Note on Chain-of-Thought and Reasoning Models
People often describe AI reasoning as the model thinking through steps before answering. That general idea is useful, but the details differ by platform and change quickly.
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Conclusion
Traditional SEO helps you get discovered. The AI reasoning phase decides whether you get recommended. If you want to show up in that decision, get UR Digital involved to help you prioritise accurate product data, clear page content, and connected structured information. That is what makes you easy to select.