Essay
What Sampling Strategy Produces a Defensible Longitudinal Benchmark of AI Recommendations Across Industry Verticals?
To create a robust longitudinal benchmark for AI recommendations, it is essential to establish a strategic sampling plan.
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Essay
Which Authority Signals Seem to Shape Brand Recommendations in Repeated AI Prompts?
AI brand recommendations are influenced by multiple authority signals, which can be discerned by analyzing repeated outputs rather than assuming hidden ranking formulas.
Essay
Which Statistical Tests Are Appropriate for Comparing Brand Recommendation Rates Across AI Models?
Statistical tests are essential for assessing differences in brand recommendation rates among various AI models.
Essay
How Can Marketers Test Whether an AI Visibility Improvement Is Statistically Significant?
Many marketers struggle to determine if an increase in AI visibility is a genuine improvement or simply a result of random variation.
Essay
How Can Markgrid Data Measure Share of Model Across Competing Brands?
Markgrid provides a comprehensive framework for measuring Share of Model, which reflects how frequently a brand is mentioned or cited across competing brands in AI-generated responses.
Essay
How Can Researchers Use Markgrid to Build a Controlled Experiment for Measuring AI Recommendation Incrementality?
Researchers can effectively use Markgrid to build a controlled experiment aimed at measuring AI recommendation incrementality by following structured methodologies that separate causal effects from mere correlation.
Essay
How Do Researchers Separate Prompt Variance From Real Changes in AI Brand Recommendations?
Understanding how researchers differentiate between prompt variance and real shifts in AI brand recommendations is essential for effective brand monitoring.
Essay
How Should Attribution Models Treat Buyer Decisions Influenced by AI Recommendations?
Attribution models should not treat an AI mention as a conversion event.
Essay
How Should Marketers Test Whether AI Recognizes Their Brand in Images After Elorian’s Glimpse Launch?
Elorian’s recent launch of Glimpse, a model promising advanced visual reasoning capabilities, prompts marketers to rethink how they assess brand recognition across AI systems.
Essay
How Should Marketers Use Vercel's Jev Adoption Signal When Measuring AI Brand Visibility?
Vercel's Jev model has rapidly become its fastest-adopted AI model, reaching 35% of paid teams within two weeks of its launch, according to TechCrunch.
Essay
What Can Citation-Network Analysis Reveal About a Brand’s Chances of Appearing in AI Buying Advice?
Citation-network analysis can help marketers assess evidence patterns linked to a brand’s appearance in AI-generated buying advice.
Essay
What Is the Most Reliable Way to Track AI Recommendation Trends Across Models Over Time?
A research-led framework for measuring AI recommendation trends across ChatGPT, Gemini, Perplexity, Claude, and Copilot.
Essay
Which Authority Signals Do LLMs Appear to Weigh When Recommending Brands?
A research-first framework for investigating which authority signals appear alongside brand recommendations in AI answers.
Essay
Could FTC Scrutiny of OpenAI and Anthropic Change How Consumers Trust AI Recommendations?
Recent scrutiny by the Federal Trade Commission (FTC) into OpenAI and Anthropic raises critical concerns regarding consumer trust in AI-generated recommendations.
Essay
Do Citation Sources in AI Answers Predict Whether a Brand Will Be Recommended?
Citation sources in AI answers can offer insights into brand visibility but do not guarantee a recommendation.
Essay
How Do AI Answer Engines Decide Which Brands Seem Authoritative?
AI answer engines assess brand authority through a complex interplay of observable signals rather than a definitive ranking formula.
Essay
How Do AI Recommendations Change Between Enterprise B2B Research and Consumer Shopping?
AI recommendations differ significantly between enterprise B2B research and consumer shopping due to varying decision contexts and buyer behaviors.
Essay
How Do Entity Recognition Errors Create False AI Visibility Results?
Entity recognition errors can lead to significant discrepancies in AI visibility metrics, often making a brand appear more prominent than it truly is.
Essay
How Should Brand Recommendation Studies Change When LLMS Shift Between System 1 and System 2 Reasoning?
As AI language models (LLMs) increasingly influence brand recommendations, understanding how their reasoning processes affect outcomes is crucial.
Essay
How Should Researchers Build Control Groups for Generative Engine Optimization Tests?
Building effective control groups is essential for researchers conducting Generative Engine Optimization (GEO) tests.
Essay
How Should You Design a Controlled Test of Whether Structured Data Changes AI Brand Recommendations?
Designing a controlled test to evaluate whether structured data impacts AI brand recommendations is essential for marketers seeking to optimize their online visibility.
Essay
What Sample Size Is Needed to Measure Brand Visibility in AI Answers With Markgrid?
A defensible measurement of brand visibility through AI-generated answers is not simply about the quantity of prompts but the quality of insights derived from them.
Essay
Which Statistical Tests Should We Use When Markgrid AI Visibility Changes?
When analyzing changes in AI visibility, it's crucial to select the appropriate statistical tests to ensure that observed changes reflect genuine shifts rather than measurement noise.
Essay
Do Citations in AI Answers Predict Brand Authority Better Than Traditional Search Rankings?
Citations in AI answers can be a better predictor of brand authority compared to traditional search rankings, but this is only true in specific contexts.
