A New Column Asks Why SEOs Still Ignore ‘Decision Distance’ in the AI Search Era

A new column on Search Engine Journal argues that SEO teams are still measuring the wrong layer of performance. Giulia Panozzo, founder of Neuroscientive Bio, writes that traditional metrics such as clicks, impressions, and rankings only capture what happens after a decision is made. With AI-generated answers increasingly shaping choices before a user visits any website, she proposes a metric she calls “Decision Distance” to measure the gap between a user’s decision drivers and a brand’s messaging.

The premise is that AI Overviews and conversational search have moved a large part of the research process out of the search results page and into the answer itself. Users now evaluate a synthesised response before deciding whether to click, which means the deciding moment often happens outside a brand’s visibility.

What the column says about traditional metrics

Panozzo argues that metrics like CTR and bounce rate describe outcomes, not motivations. A CTR shows that someone clicked, but not why one result felt more compelling than another. A bounce rate shows that someone left, but not which expectation went unmet. By the time these numbers are recorded, she argues, the decision has already been made and can no longer be influenced.

The column also notes that recent analyses of Google’s ranking systems suggest traditional signals, along with user interactions, help search systems infer content value. So the issue is not that these metrics are useless; the problem is that they all measure the result of a choice instead of the reasoning behind it.

Datos clave

Aspect	Detail
Metric introduced	Decision Distance
Author	Giulia Panozzo, founder of Neuroscientive Bio
Core argument	Traditional SEO metrics measure decisions already made
Source type	Opinion column on Search Engine Journal, August 2026

How Decision Distance is defined

The proposed metric estimates how far a brand’s messaging and offer sit from the functional, emotional, and social drivers that influence a decision. The closer the messaging aligns with those drivers, the more likely someone is to move forward. The column argues that people rarely convert because of content itself; they act because the content moved them closer to a decision they were already evaluating.

Panozzo uses everyday examples to illustrate the idea. A commuter may not always take the fastest route, choosing instead the option that fits what matters in that moment, whether that is avoiding traffic, stopping by the gym, or getting home quickly. The same logic applies to choosing a streaming service or software. The column suggests that LLMs are mirroring this filtering process by trying to match answers to the user’s values, preferences, and even temporary states. For a brand, failing to align with intent, values, or emotional context can push it out of the options the AI presents.

What this means for Indian marketers

The column’s relevance for Indian SEO teams is not about adopting a new dashboard. It is about recognising that rankings alone will not show whether a brand’s messaging aligns with the motivations behind a query. In a market where businesses compete for visibility across Google AI Overviews, chatbots, and social platforms, the question shifts from “did we get the click?” to “were we even considered as an option?”

Marketers can use the framework to audit content along the customer journey: whether a homepage, product page, or campaign message addresses the emotional and social factors behind a purchase, not just the functional features. The column leaves the actual calculation method open, so teams will need to develop their own way to assess that alignment.

Caveats and open questions

Decision Distance is a conceptual argument rather than a tested methodology. The column is an opinion piece, and it does not offer data, benchmarks, or a standardised way to measure the gap. The author herself presents it as a shift in thinking about the decision process, not as a finished tool. Readers should treat it as a starting point for internal audits rather than a confirmed performance metric.

Next checks for the reader

For Indian SEO professionals and content teams, the practical takeaway is to map the motivations behind key queries and compare them with the messages currently published at each stage of the funnel. The concept also raises a broader question: if AI answers are becoming the new first step in the journey, how should brands measure influence before the click? The column does not fully answer that, and the discussion remains open.

Source: Search Engine Journal – “The Metric Most SEOs Are Still Not Measuring In The Age Of AI” (https://www.searchenginejournal.com/the-metric-most-seos-are-still-not-measuring-in-the-age-of-ai/584027/)