Rankfor.AI ads

Is your company on AIs list of the best in your field? ... It may depend on how long the list is. We asked Gemini the kind of questions buyers ask, in the fields of 45 fast-growing European companies from earlier FT 1000 rankings, and counted how often those companies were named. When the question asked for ten companies, these firms came up 3 times in 300 chances. When it asked for twenty, they came up 16 times. 11 of those 16 were in places 11 to 20. So when a growing company does make the AIs answer, it often sits just below the cut most people look at. For marketing and PR teams, are we in the top ten? is only part of the picture. The useful questions are how far down the list you are, which names come first, and what would move you up. And the work counts. Rankfor.AI measures what AI says when your buyers ask for a recommendation, and whether your brand is named. Full method and the charts: link in the first comment. #AIVisibility #AISearch #MarketingAnalytics

ChatGPT Ads vs Rankfor context-driven placements in conversations. ChatGPT: 1. ChatGPT Ads are on cheap/free accounts. 2. Ad is visible under chat, and people know it. 3. Conversion - same or worse comparing with Adwords. Cost - pretty same. 4. Available only in ChatGPT. Rankfor: 1. Context is available to AI-agents, if it is relevant to buying persona. 2. It is visible in the conversation, with the attribution to the link where the customer wants to direct traffic (even thought CTR is 0.6-1.5%). 3. Conversion - 3x-10x higher, as it comes from decision-making process buyer does while reads the answer. 4. Optimized for every major model: ChatGPT, Gemini, Perplexity, Claude, Grok, or Mistral. Who's eager to boost Q4 revenue to hit yearly sales targets?

Right now, buyers are asking ChatGPT and other AI tools who to trust. Will they find you-or your competitor? With Rankfor.AI’s 90‑day Managed AI Search programme, you approve the facts and we handle the research, content, publishing and follow-up for one product in one language. You stay in control of the message while our team does the work that gets you into the AI-powered shortlist.

I wrote a book about AI recommendations. Where does the argument break? Become the Answer is for marketing teams asking a practical question: what should we change when buyers use AI to choose a provider? I cover how to check whether a brand appears, examine the sources behind an answer, and decide what to work on next. The difficult part is knowing what the evidence actually supports. Bart Goralewicz, Kevin Indig, Lily Ray, Ethan Smith, Michael King, Aleyda Solís, Jason Barnard: I'd value your critical reading. I have a complimentary PDF for each of you, if you'd like it. No obligation to review or post. One question in particular: which recommendation in the book would you challenge before a marketing team spends money on it? Private feedback is welcome. A specific disagreement gives me something useful to work with.

“Do I have to run this too?” A CMO should be able to ask that before buying any AI visibility service. With an AI PR Office, your team provides one approved brief: the buyer questions, markets, product facts and people who can sign off changes. Rankfor monitors the agreed answers, finds the important gaps and prepares the work. That can be a correction brief, a page update or a source brief for a publisher or partner. The work comes back with the claims that need approval. After it ships, Rankfor checks the agreed questions again and reports what changed. The CMO owns the priorities and company facts. Rankfor owns the operating work between the brief, approval and follow-up. You still make the important decisions. You do not have to coordinate every task in between. #AIVisibility #PublicRelations #BeVisible

Ranking is the wrong frame. AI visibility is not really about where you rank. It is about whether because of AI reputation, it chooses your brand when a buyer asks. Our main KPI is simple: The probability of being recommended for a specific buying question. The loop? Measure → map the evidence → run an intervention → measure the lift → learn what worked → repeat. Not: “Did our AI visibility score go up?” But: Did changing this evidence make AI more likely to recommend us? Monitoring tells you what happened. AI Reputation Management tells you what to change - and proves whether it worked.