AI Cites Your Brand: How to Choose Your Next Move via @sejournal, @hethr_campbell
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SEJ STAFF Heather Campbell 5 seconds ago ⋅ 5 min read SEJ STAFF Heather Campbell VP of Sales & Marketing at Search Engine Journal Bio Follow An AI answer mentions your brand. That looks like progress, but it does not tell you what to do next. A competitor may appear more often, the answer may describe an old version of your product, or important pages may never reach the bots collecting information. In this webinar, Constance Tan, Product Marketer at Ahrefs, explained how to separate those problems and choose the right response. Her starting point: look for recurring patterns across the customer journey, not a reassuring mention in one prompt. Generating hundreds of prompts does not guarantee useful coverage. Tan organized monitoring around three kinds of questions: Search queries, support conversations, sales questions, and relevant community discussions can supply the language for those prompts. Tan cautioned that the most useful forums differ by market; Reddit and Quora are not the answer everywhere. “The idea is that you want a representative view from every angle of the customer journey.” Monitor that set over time. Repeated sources, positioning claims, and factual errors give you something concrete to investigate. If competitors appear more often, share of voice identifies the gap. Reading the answers helps explain it. Does AI repeatedly favor another brand for small businesses or ecommerce? Which pages supply those distinctions, and does your content explain the same use cases? Tan recommended examining both the sources and their formats. Reviews, discussions, and videos can matter alongside articles. For outreach, prioritize pages cited repeatedly and authors you can realistically reach. Domain strength and organic traffic add context, but an influential competitor-owned page may offer little opportunity for a correction. The recording’s competitive-source walkthrough shows how Tan starts with a side-by-side visibility comparison and narrows it down to the specific sources worth digging into. Before commissioning another article, inspect your own pricing pages, product explanations, profiles, and older posts. Conflicting information can leave AI answers describing features or plans that have changed. Third-party corrections require more patience. Tan shared an Ahrefs outreach example: the team contacted 26 authors about inaccurate information, 10 replied, and four updated their content. One issue concerned older descriptions of which plans included API access. Those are outreach outcomes, not proof of a corresponding lift in citations or revenue. They illustrate why selecting reachable, frequently cited sources matters. Updating someone else’s page is not always practical. Constance Tan explained the alternative: “Sometimes outreach is not always the answer. Sometimes it’s better to create the new sources of information, new pages that answer or cover the topic in a better way, a more comprehensive way, or with more up-to-date information.” In the Q&A, Tan expanded on that choice: a warm relationship can make a correction worthwhile, while an important topic with weak coverage may justify an original guide or collaboration. If the same error appears across several sources, one new article may not be enough. Tan’s advice for community participation was not to insert a product pitch into every thread. Answer technical questions, correct factual mistakes, or offer useful guidance. Recurring complaints can also reveal product or onboarding problems worth taking back to the teams that can fix them. Missing citations can have a different cause entirely: bots may be unable to retrieve the content. Tan recommended checking firewall restrictions, broken URLs, timeouts, and pages that rely on JavaScript to display important information. Investigate those failures before treating every visibility gap as a content problem. A useful page cannot serve as a retrieved source if the bot cannot access its information. Visibility reporting also needs business context. Asked about revenue, Tan discussed Ahrefs’ self-reported discovery data, including customers who mentioned ChatGPT, rather than claiming a revenue-per-citation formula. Her recommendation was to consider impressions and share of voice alongside conversions, sales, and customer attribution information. Watch the full session for the source comparisons, outreach examples, and bot-access checks. To put the approach into practice, start with one customer segment and use what you find to choose a specific action: Join us as Lisa Salvatore, Sr. Manager of Integrated Marketing at CallTrackingMetrics, walks through how to pull AEO insights, FAQ content, and real customer phrasing out of data your team is already collecting. Her colleague Brian Barranger, Sr. Account Executive III, covers what a qualified conversion actually sounds like, and how that evidence sharpens targeting, scoring, and the gaps and integration requests you route to your product team. Add SEJ as a preferred source on Google Read Full Bio SEJ STAFF Heather Campbell VP of Sales & Marketing at Search Engine Journal Heather has over 20 years of industry experience and is the VP of Sales & Marketing at Search Engine Journal. ... Breaking news and insights to help you lead search strategies. What Google’s I/O Demos Reveal About Business Search Visibility Why Users Are Fleeing To AI-Free Search & What It Means For SEO Google’s AI Search Data Is Growing, But The Gaps Remain Turn AI Visibility Into Practical Action Watch On-Demand In a world ruled by algorithms, SEJ brings timely, relevant information for SEOs, marketers, and entrepreneurs to optimize and grow their businesses -- and careers.
Source: Search Engine Journal
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