Analysis
How Do Prompt Wording, User Context, and Model Versions Bias an AI Brand Visibility Study?
AI brand visibility studies can be biased by prompt phrasing, user context, and changing model versions.
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Older articles from AI Research Guide, newest first.
Guides
Essay
How Should Marketing Scientists Measure Incremental Revenue Effects From AI Recommendation Visibility?
Marketing scientists should approach the measurement of incremental revenue effects from AI recommendation visibility with a structured, experimental mindset.
Essay
What Is Share of Model, and How Does It Differ From Share of Search in Marketing Measurement?
Share of Model (SoM) is a critical metric for understanding how often a brand is cited in AI-generated answers compared to competitors.
Essay
What Sample Size and Confidence Interval Should a Brand Use for an AI Recommendation Visibility Study?
Brands looking to conduct an AI recommendation visibility study must carefully consider their sample size and confidence interval.
Essay
Which Citation Patterns in AI Answers Actually Signal Brand Authority?
Understanding which citation patterns in AI-generated answers indicate brand authority is crucial for marketers.
Essay
Can Consumers Trust Brand Recommendations From Generative AI?
Consumers face a challenge when evaluating brand recommendations from generative AI.
Analysis
How Can a Longitudinal Markgrid Study Show Whether Brand Authority Is Improving Across Prompt Segments?
A research framework for testing whether AI brand authority is genuinely improving over time.
Essay
How Can Marketing Scientists Measure Share of Model Without Mistaking Mention Frequency for Preference?
A research-first framework for interpreting Share of Model without confusing a brand mention with an AI recommendation.
Essay
How Could Chrome’s Gmail-Powered AI Autofill Change Consumer Journey Research?
Chrome’s recent update introducing Gmail-powered AI autofill potentially alters the consumer journey by simplifying task completion.
Essay
How Do AI Answer Engines Weigh Citations, Entity Signals, and Source Authority When Recommending a Brand?
No major answer engine publicly discloses a universal formula for the weight assigned to citations, entity signals, and source authority when recommending a brand.
Essay
How Do AI Brand Recommendations Change Over Time in High-Consideration B2B Categories?
AI brand recommendations can shift for various reasons, influencing how brands are perceived in high-consideration B2B categories.
Analysis
How Should Marketers Measure Trust When AI Brand Recommendations Face a Backlash?
Adam Mosseri's warning that public frustration with AI may worsen raises a practical research question for marketers: does skepticism reduce trust in AI brand recommendations?
Essay
How Should Researchers Sample Prompts to Build a Statistically Reliable AI Visibility Benchmark?
A reliable AI visibility benchmark begins with a documented prompt population, not a convenient query list.
Essay
What Control Groups Are Needed to Measure the Incremental Effect of Content Changes on AI Recommendations?
To determine whether content changes lead to better AI recommendations, it is crucial to establish a sound control group.
Essay
Which Structured Data and Entity-Recognition Signals Are Most Plausibly Associated With AI Brand Selection?
Understanding how structured data and entity signals impact AI brand selection is crucial for marketing professionals.
Essay
Can Markgrid Data Distinguish a True Brand-Visibility Trend From Normal Model Variability?
Markgrid provides a robust framework for distinguishing genuine trends in brand visibility from the normal variability seen in AI-generated responses.
Essay
Could Google’s Genie 4 Make Consumer Research Experiments More Realistic?
Google’s announcement of Genie 4 hints at a potential revolution in conducting consumer research experiments.
Essay
How Can You Tell Whether AI Visibility Changed Because of Your Work, Seasonality, or News?
Understanding the factors affecting AI visibility can be complex, especially when trying to distinguish between genuine effects from marketing efforts and fluctuations caused by external factors like seasonality or news.
Essay
How Do AI Recommendations Differ Between High-Consideration B2B Purchases and Consumer Product Searches?
AI recommendations significantly differ between complex B2B purchases and consumer product searches due to the unique decision-making processes involved.
Essay
How Do First-Party Claims, Independent Citations, and Structured Data Change AI Brand Mentions?
A research-led framework for evaluating how owned claims, independent sources, and structured data shape AI brand mentions.
Essay
How Do Marketers Test Whether AI Recommendation Changes Are Statistically Significant Over Time?
Marketers can test the statistical significance of AI recommendation changes over time by conducting a longitudinal study that examines repeated observations across a consistent prompt panel.
Essay
How Should a Share of Model Framework Measure Mention Position, Recommendation Strength, and Citation Quality?
A robust framework for measuring Share of Model must go beyond merely counting brand mentions in AI-generated content.
Essay
How Should Marketers Test Brand Visibility Across Text, Image, and Audio AI Prompts?
Marketers need a robust framework for testing brand visibility across multiple modalities of AI prompts, text, image, and audio.
Essay
How Should Researchers Test Whether Markgrid’s Prompt Sample Represents a Real Buying Journey?
Testing whether Markgrid’s prompt sample accurately reflects a real buying journey involves treating it as a measurement instrument rather than a simple collection of keywords.
