From Visibility to Revenue: The New Funnel
From Visibility to Revenue: The New Funnel
Tarun Babbar explains why AI visibility is not a marketing metric but the first stage of a new revenue funnel that most companies have not yet mapped.
Haritha Kadapa
'A Conversation with Gravton Labs' Founder & CEO'
The middle of the funnel has not disappeared. It has just moved.
Buyers still go through a discovery phase, a shortlist phase, and an evaluation phase before they talk to sales. What has changed is where those phases now happen. More of them happen inside AI tools, before a buyer visits your site, before they fill out a form, before your team ever sees their name.
That is the shift Tarun Babbar has been watching since founding Gravton Labs. And in his view, most revenue leaders are still measuring the funnel from the wrong starting point.
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Q: Why do you call this a "new funnel" rather than just a new traffic source?
Because the dynamic is structurally different from anything that came before.
When search engines changed how buyers discovered vendors, companies adapted by investing in SEO and content. The funnel still started at roughly the same place; the buyer had intent, they searched, they landed on your page, and the conversion process began.
What is happening now is different. AI tools are not just delivering buyers to the top of your funnel. They are doing a significant part of the funnel work themselves. They are comparing vendors, summarising category options, surfacing pros and cons, and in some cases telling the buyer whom to call first.
If you are not shaping what AI says about you at that stage, you are not missing traffic. You are missing the opening stages of your own revenue process. That is why I think of it as a new funnel, not a new channel.
Q: Where does this new funnel actually begin?
It begins with a question.
Not a search query in the traditional sense, but a conversational question a buyer asks an AI tool. Something like: "What are the best platforms for managing X?" or "How do companies in our industry solve Y?" or "What should I look for when evaluating Z?"
Those questions are happening millions of times a day across ChatGPT, Perplexity, Google AI Overviews, and similar tools. The answers those platforms give are shaping how buyers define their problem, which vendors feel credible, and who ends up on the first shortlist.
That is the new funnel. Most companies have no visibility into what is being said there, let alone a strategy for influencing it.
Q: Why did you build Gravton around this problem specifically?
Because I had seen the attribution gap get worse before this, and I knew this would be a step change.
I spent years working at companies where growth and revenue teams were constantly trying to understand how customers actually found them, not just what the last click said, but the real story of how awareness became consideration became a deal. That has always been hard to measure.
AI has made it dramatically harder. The buyer's journey is now partially invisible. A prospect can develop a clear point of view about your category, your competitors, and your value proposition entirely inside AI conversations, and none of that shows up in your analytics.
The moment I saw how much of the pre-purchase journey was migrating into AI interfaces, I knew the infrastructure to measure and influence that journey did not exist yet. That is what we are building.
Q: How does the new funnel map to the stages most revenue teams already use?
The stages are similar. What sits above them is new.
Think of it this way. The funnel that most teams operate, awareness, consideration, intent, evaluation, decision, has not gone away. But there is now a pre-awareness stage that feeds into it.
Before a buyer becomes aware of your brand, AI tools may already have indicated whether your category is worth exploring, which vendors are considered established players, and how to approach the problem your product solves.
If AI consistently names your competitors and not you or describes your category in a way that does not fit your positioning, the rest of your funnel is running uphill. You are trying to convert buyers who arrived with a framework you did not help build.
The companies that will win in this environment are the ones who understand that visibility in AI is not a vanity metric. It is a stage-zero funnel problem.
Q: You talk about influencing what AI says. How does that actually work? Is it just content?
Content is part of it, but only part.
AI models form their understanding of a company, a category, and a competitive landscape based on a wide range of signals, the clarity of your owned content, what third-party sources say about you, how consistently your positioning appears across the web, what comparison and review content exists, and how authoritative your coverage appears relative to competitors.
If your website is vague about the problem you solve, AI will describe it similarly. If your competitors have stronger third-party coverage, better comparison content, and clearer category narratives, AI LLMs will use them.
What we have built at Gravton is the infrastructure to measure those signals, identify the gaps, and systematically close them. That means understanding which prompts buyers are actually using, what answers they are getting, where you are absent or misrepresented, and what specific changes to content, positioning, and source coverage will shift the outcome.
But you have to understand that it is not a one-time fix. It is an ongoing discipline, just as SEO was never just a one-time fix.
Q: Where does measurement come in? How do companies know if this is working?
That is exactly the problem we built Gravton to solve.
Right now, most companies cannot answer a simple question: when a potential buyer asks an AI tool about my category today, what does it say? Who gets named? What context is given? How does that compare to six months ago, or to my closest competitor?
Without that data, you are flying blind. You might be doing all the right things on your website and in your content programme and still losing ground in AI conversations. You would not know until it showed up as pipeline softness or sales friction, quarters later.
We give companies a continuous view of how they appear across the major AI platforms. We map whether brands get mentioned, in what context, at which stages of the buyer journey, and against which competitors. Then we connect those signals to the downstream revenue data so teams can see what is actually influencing the pipeline.
That measurement layer is what turns AI visibility into something a CMO or VP of Revenue can actually manage.
Q: Who in the organisation should own this?
Whoever owns the top of the funnel needs to be working closely with sales.
The instinct in most companies is to put this with marketing, and I understand why. A lot of the inputs, content, positioning, messaging, and third-party coverage are traditionally marketing's domain.
But the outcome of this work shows up in sales. It shows up in whether reps start calls with buyers who already know you, and whether competitors are being recommended before your team gets a chance to speak. Plus, whether the deals your team is seeing are shaped by a narrative you controlled or one your competitors controlled.
So, the ownership question matters less than the alignment question. Marketing needs to understand what the AI research phase is surfacing. Sales need to feedback signals about what buyers say, which competitors they mention, and where the narrative is already set before the first call. And leadership needs to treat AI visibility as a revenue input, not a marketing experiment.
The companies getting this right are the ones where the conversation is already happening across those functions together.
Q: What does a company that is doing this well look like in two or three years?
They look like the companies that understood content marketing in 2012 or search intent in 2016.
There will be a group of companies, in every category, that moved early on this. They built the measurement infrastructure, they developed the content and positioning discipline, and they earned consistent presence in AI-mediated buyer research. For those companies, AI becomes a durable source of pipeline quality.
The companies that wait will find themselves in the same position as companies that ignored search a decade ago. The gap becomes structural. The cost to catch up is high. And by the time the data proves the problem clearly, the window to establish early authority has already closed.
I think the window right now is still open. But it is not as wide as it was twelve months ago, and it will be narrower in another twelve.
Q: What should a leadership team do this week if they want to start?
Start by auditing the conversation you are not seeing.
Pick the five or six questions a real buyer in your market would ask an AI tool before ever talking to your sales team. Category questions, comparison questions, implementation questions, use case questions. Run those prompts across ChatGPT, Perplexity, and Google AI Overviews. Read what comes back.
Ask yourself: does this accurately represent our category position? Are we present? Are our competitors better represented? Is the framing of the problem one we would have chosen?
That audit takes an afternoon. It will tell you more about the first stage of your new funnel than most marketing reports can. And it will tell you exactly where to focus.
VISIBILITY & CONTENT STRATEGY
