Last week, AI-enabled ad technology firm Mobian announced a new generative engine optimization (GEO) product for brands, creating additional commercial opportunities for publishers.
Speaking to the product’s contextual capabilities, Time COO Mark Howard said on LinkedIn about his company’s latest partnership, “By cross-referencing brand ads and sentiment against AI prompts, Mobian provides the data-driven insights necessary to track and score how closely AI platforms match a brand’s true positioning.” Read more. (April 1)
More: “Time pitches GEO insights into a new brand offering” (March 31) – Digiday
Mobian CEO Jonah Goodhart answered a selection of follow-up questions from tipsheet via email.
tipsheet: How do you determine whether something is aligned or not?
Jonah Goodhart, CEO, Mobian: We look at content cited by AI through a brand suitability lens, which is one of our core competencies at Mobian.
We are known for evaluating content with nuance, and we’re doing it at scale with our contextual intelligence models processing over 1 trillion tokens a month across tens of millions of pieces of content spanning text, images, audio, and video. That volume and depth gives us a unique understanding of the shape of content: archetypes, how stories are told, tone, sentiment, and emotion across formats, environments, and contexts. Those models are informing how we evaluate content for brands whether that’s where their ads show up or what AI engines are citing.
One strong signal for how a brand wants to show up is how they tell their story in paid media.
- Our creative intelligence platform spans over 700,000 creatives scored by our proprietary creative model across the largest couple thousand brands, and we evaluate thousands of new creatives every day, giving us real-time visibility into how brands are evolving their messaging.
- Our dataset covers the largest video, social media, and CTV platforms.
- Our prompt generation for AI is informed by live signals from authentic online communities, major video platforms, search trends, and cultural trend analysis, combined with purchase intent signals. Once established, queries can be held constant to track how responses change over time, while new signals can be periodically introduced.
Aligned means the content supports the brand’s narrative. Misaligned means it may contradict that narrative, introduce competitors when a brand is explicitly queried, or surface information that is outdated or inaccurate.
Brands are ultimately in control and can customize what is aligned or not for them, and we look not just at the brand level but at the product and category level, doing portfolio analysis across thousands of citations customized to whatever cadence a brand wants.
What is Mobian seeing regarding LLM citation volatility across engines? How fine can orchestration get?
Every engine is different, and that matters. In a recent portfolio analysis across 23 products and 5,400+ citations, OpenAI had the highest flag rate at 21%, Perplexity had the lowest at 14% but with nearly 5x the citation volume, and each engine has different source preferences and refresh cycles.
Another interesting finding is persistence: we’ve seen recall articles from years ago still being surfaced on neutral brand prompts, with AI engines latching onto sources and citing them long after the issue is resolved. You can’t control what any engine cites on a given query, but you can influence the source ecosystem, and that’s where publishers like Time with strong domain authority become valuable. It’s about making sure credible, on-message content exists where AI looks.
The takeaway is that citation behavior is highly fragmented across engines, which makes measurement and comparison critical.
Is managing LLM citations a daily battle? Best practices?
It’s a new discipline. There are some similarities to SEO, credibility matters for instance, but there are also significant differences.
Each model is different and there is no single winner. Brands now have to market to two audiences: humans and AI systems. Humans respond to emotion and storytelling. AI systems prioritize structured, credible, and up-to-date information. That requires a different set of inputs and a different level of discipline around how content is created and maintained.
Best practices: measure and understand AI visibility regularly, prioritize brand-specific, competitor, and category prompts since those generate the most actionable insights, and keep owned content fresh and structured since we’re seeing AI engines cite outdated pricing, discontinued features, and resolved issues. Structured data drives token and compute efficiency, and in a world where token usage has increased 20x in the last two years, that matters a lot, but credibility is critical too, just as it was for PageRank and search.
What are the traits of a publisher for GEO? Does it need to look like Reddit?
It comes down to credibility and authority. Reddit is important because it’s authentic in many cases and clearly AI sees it as valuable. YouTube is always rapidly gaining in citation popularity. A publisher like Time works through editorial authority and trust signals, which is a different but equally powerful mechanism.
What matters is domain authority, topical depth, content freshness, and the ability to create structured content AI can cite. Brands have limited resources, so they want to focus on where they have the biggest opportunities and the biggest gaps.
What Time is doing that’s smart is connecting the AI visibility analysis directly to content strategy: identify the delta, understand where the brand narrative breaks down, and focus resources on closing those gaps. It’s designed as an ongoing strategic content partnership.
What unique capability is Mobian bringing?
We have some interesting assets that we’re applying to this area. The creative intelligence and contextual intelligence capabilities I described above are the foundation. We evaluate tens of millions of pieces of content across text, images, audio, and video, which gives us a unique understanding of narrative structure, archetypes, and how stories are told. Those same models are now being applied to AI citations.
Creative intelligence shows brand intent, contextual intelligence scores whether AI citations support or undermine that intent, and the gap between those two is the product. Through our strategic partnership with Attain, we are also able to connect context to Attain’s outcome dataset, the largest commercial purchase dataset available in the US, closing the loop from content to real-world purchase behavior. Our intelligence and measurement feed a partner like Time so they can walk into an advertiser meeting with creative intelligence showing how the brand tells its story, AI visibility showing where it breaks down, and contextual depth explaining exactly why and what Time can do to help close the gap. It’s really powerful.