IAB Introduces Framework for Measuring Brands’ AI Visibility

As artificial intelligence becomes increasingly embedded in everyday life, sending marketers racing to ensure their content is seen and surfaced by automated tools, the Interactive Advertising Bureau has put out a new set of guidelines around measuring AI visibility. 

The playbook, published this week, aims to define “what good AI visibility measurement looks like.” It lays out a unified language for evaluating visibility among tools like ChatGPT, Google Gemini, Claude and more, as well as a set of quality and transparency requirements for use in assessing AI visibility measurement tools. 

On the vocabulary front, the IAB introduced the “four Ps of AI visibility.” First in the hierarchy is presence, defining whether a brand appears in AI discovery at all, tracked by metrics like mention rate, citation rate, share of voice and visibility momentum. It’s followed by prominence, assessing where and how prominently a brand appears, and portrayal, evaluating the context and accuracy of that appearance, measured via sentiment, framing, hallucination rate and factual inaccuracy rate. Rounding out the quartet is persuasion, to determine whether a brand’s AI visibility actually drives action, as determined by recommendation strength and post-citation click-through rate. 

When it comes to assessing the metrics behind each of the four Ps, the report suggests that marketers evaluate AI visibility data by understanding the differences between directional and decision-grade measurement and by ensuring their measurement partners have methodologies in place to account for hallucinations, factual inaccuracies and biases. 

The IAB offers a set of criteria for evaluating the quality of the data used in AI visibility measurement tools, as well as a list of the baseline information that the makers of those tools should be disclosing so that marketers can adequately assess the validity of their resulting measurements. 

“Consumers are increasingly discovering and considering brands and products in AI platforms, but measurement frameworks haven’t kept pace,” Caroline Giegerich, VP of AI for the IAB, said in a company release. “This playbook gives the industry a common foundation for evaluating AI visibility consistently and with confidence. The brands, publishers, and agencies that embrace it now will better understand their presence in AI-powered discovery and be able to take informed action to improve their visibility.” 

solli’s Final Thoughts 

A standardized framework around measuring AI visibility could be hugely beneficial to the pharma media industry.  

Marketers are moving quickly to optimize content to be picked up in Google’s AI Overviews, in answers to ChatGPT queries and beyond, and they need a way to measure how well those efforts are working. Dozens of tech solutions have popped up with promises of doing just that, but there’s little to no standardization yet in the wild, wild west of this brand-new field. 

It’s crucial, then—while the practice of measuring of AI visibility is still in its infancy, even as it appears poised to become one of those important metrics in media—for marketers to agree on and adopt guidelines like those set out by the IAB to ensure that AI visibility metrics are as accurate and comprehensive as possible.