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Welcome to the Core Report Special Edition. I’m joined by Kirthiga Reddy, co-founder and CEO of OptimizeGEO, we’ll find out more about that.
Kirthiga has a background as the first female investing partner at SoftBank Investment Advisors. She also worked for six years as Managing Director of Facebook India and South Asia, and was the first employee of Facebook in India. Thank you so much for joining me.
Excited to be here.
Let’s talk a little about Optimize. But before we get into the company, what made you choose this particular problem to address?
Govind, I’ve had the privilege of working with both innovative startups and leading Fortune 500 companies through the last major consumer transition — to social and mobile — helping them stay relevant during that shift. So as I saw what was happening now, with consumers going to ChatGPT, Perplexity, Claude, and the like for everything from skincare advice to news to which enterprise solution to buy, it felt like a real privilege to be back again, helping brands stay relevant in this new consumer shift. That’s what drew me to this problem.
We have over a billion people on ChatGPT now, coming back 14 times a day. If brands aren’t visible there, they’re effectively forgotten. I want to help them be on the winning side of this transformation.
What was the world like before ChatGPT and other LLMs came along, and what’s it like today from a brand’s vantage point?
Totally. The biggest thing brands used to think about was: when someone goes to Google, searches for their category, what links come up, where are they ranked, and how can they improve that ranking? Now the shift is that people are no longer searching — they’re asking. They’re asking deep questions, like, “What’s the right CRM software for a small-to-medium business in financial services?” If the company serving that customer isn’t visible in the answer, they’re forgotten by this modern decision-maker.
That’s the change, and it’s happening at a staggering pace. Today, over 60% of Google searches don’t result in a click-through — just two years ago, that number was 20%. People are asking, getting their questions answered, and moving from awareness to consideration to decision in a matter of minutes.
If you look at a range of brands, what were they doing right before, and what are they getting wrong now in terms of their online presence?
I’d encourage the leaders watching this to go to their favorite LLM, ask questions about their category, see which brand comes up, and get curious about why the LLM is giving that answer and how to make sure their product or service is represented accurately and in the right context.
So what were people doing, and what are they doing now? It starts with: see it, understand it, fix it. First, do you know where you appear? What’s your “generative engine scorecard” your visibility, your share of voice, your favorability? If you’re appearing, is the sentiment positive, negative, or neutral?
Most companies are still in the phase of figuring out where they stand. The leading brands have moved past treating this as a vanity metric, they’re using it to understand what’s happening behind the scenes: why LLMs are answering the way they are, and what they need to change across their marketing mix, creative, content, PR so that LLMs pick up the right answer.
The most advanced brands are also acting with real urgency. Market share is won or lost during times of transformation. Challenger brands see this as their opportunity to lead, and if you’re a dominant incumbent, this is your chance to act like a challenger because that’s exactly what the number two or three player is doing.
Does this mean the LLM itself isn’t being “honest” in how it picks or chooses what to surface? For example, a popular soap brand with more or less of some ingredient, a search might have shown me that product, but an LLM might not, unless you’ve done work on the back end.
The beauty of it is that LLMs are almost your BS detector. If you say one thing on your website, but a creator or a user survey forum says something very different, LLMs get confused. So they end up rewarding trust and consistency. Our platform, OptimizeGEO, actually helps with that, we generate an accuracy score and a trust score, and we can identify things like a global beauty brand listing different ingredients for the same product on their own website versus a retail site. We help them fix that inconsistency so LLMs aren’t confused and can answer correctly.
Previously we used to think about a “social graph.” Today there’s an “AI graph” and whether your products and services are represented accurately depends on how consistent you are across every consumer touchpoint.
From a company’s point of view, how do you build trust at a broad level and specifically in the LLM era, assuming you’re starting from scratch?
It starts with an audit: where are LLMs picking up information from, and where are the discrepancies? For example, we worked with a global detergent brand and pointed out that 400,000 people were talking about detergent on Reddit and they needed a presence there. Or, for that same brand, a competitor might get recommended because of a specific environmental certification. Or for a business brand, the product itself might be rated highly, but post-sale customer support is being criticized. Those are the kinds of things LLM answers uncover and business leaders need to pay attention, because it reveals something about every touchpoint of the business.
You mentioned people discussing detergent on Reddit. What are the common themes people typically seek answers for in any product category and does that reflect gaps in available information?
Great question. Even leading brands that invest heavily in media and show up with a high AI visibility score shouldn’t treat that as a vanity metric, if you dig deeper, you often find that for nearly 40% of the questions people ask in that category, the brand has zero visibility, simply because they haven’t produced content addressing it. For example, a leading baby-care brand had a huge content gap around safety-related concerns. Brands need to align their content, creator strategy, PR, and media strategy to answer those questions. AI search effectively becomes your user research, PR research, and product research all at once, it touches every part of the business.
You’ve mentioned creators twice, I assume that’s now a critical part of the marketing ecosystem. Is that also where the disconnect happens, between what a brand says officially and what a creator says?
I’m a huge believer in the creator economy. We saw new businesses and the creator economy rise on Meta and Instagram, and creators are just as much a force in the LLM search era, because LLMs place a lot of weight on trust and authoritative sources.
You’ll see a wide gap between what’s spent on media and what actually shows up in AI visibility, you can buy reach, you can buy attention, but you can’t necessarily buy the answer. A coordinated creator strategy matters. Platforms like ours help brands understand who holds authority in LLM responses within their category, and who they should be engaging with.
You’ve been around for about 18 months. What’s changed? LLMs keep evolving, new ones keep emerging, including a wave from China competing with U.S. models. What shifts have affected your work, or your clients’ efforts to be present and convey the right message?
We ran a landmark study with the Media Marketing Alliance in India around the IPL, looking at the correlation between media spend and AI visibility. What we found, maybe intuitive given this discussion, is that the biggest media spend doesn’t translate to the biggest AI visibility. Brands that paired a strong media strategy with an AI-visibility optimization strategy got significantly more value from the same spend, even compared to others in the same category spending similar amounts.
On the change side, midway through, Gemini updated its algorithm, which dropped visibility across the board for many brands. Brands that weren’t actively optimizing stayed down. Others, because of their media-mix optimization, climbed back and gained both visibility and share of voice. We also found that brands optimizing for only one platform saw a bigger dip, some sources drive prominence on ChatGPT but do nothing for Perplexity or Claude. Brands with a diversified strategy across two or three key platforms fared much better.
So if I’m launching a major brand or a new product variant around the IPL, which many companies do, say a new insurance product, I should be working on AI visibility in parallel, since people will ask more questions via AI rather than just using Google search?
Exactly, you should be ready for it, and you should start well ahead of your big investment in properties like IPL, FIFA, or other major events.
So essentially, we’re in a hybrid world right now.
Absolutely.
Okay.
But with real differences in how that hybrid, the internet side of it, now works, especially accounting for LLM search, because that’s where consumers in India are going. You have over 100 million people on ChatGPT in India, and that number is growing at a staggering pace.
You mentioned Gemini changing its algorithm. Can companies prepare for that kind of shift, or do they just get hit and have to adjust after the fact?
There are fundamentals that help. You’ll see signals like your citation score, the number of places your brand is mentioned, start creeping up well before changes show in AI visibility or share-of-voice sentiment. Strong fundamentals help you recover gaps quickly if you’re caught off guard. You need to be prepared for that kind of roller coaster but this is the moment to act.
Let’s talk about the transaction side. All of this presumably leads — or should lead — to actual transactions, whether detergents or moisturizers. What are you seeing in terms of how people are buying, and where is that headed?
We worked with a B2B advisory firm that saw 3x growth in visibility, 131%+ growth in traffic from AI-attributable sources, and 2x growth in revenue from AI-attributable sources. Their CEO told us that more than 50% of those new customers had never visited their website before people who wouldn’t have found them if not for showing up in AI answers.
That said, attribution is still messy there’s no clean pixel-based tracking, so it’s hard to separate what came from visibility work versus organic growth in ChatGPT traffic generally. It reminds me of the early days of Facebook, when success was measured by “likes,” and then the first real measurement studies came from Nielsen and Millward Brown. We’re in a similar experimental phase now, and we’re excited to work with leading brands to innovate on measurement.
What about agentic commerce, how does that fit into what you’re doing?
We’re increasingly in a world where AI agents make research and purchase decisions on behalf of humans, so companies have to think about marketing to agents.
One client we work with is Glance, which is present on hundreds of millions of devices. We help them understand what users are asking for, for example, “What’s a personal AI styling assistant that customizes recommendations for my skin tone?” We helped grow their share of voice by over 10% and sentiment by over 20%. People are using AI for efficiency, decision-making, and personalization — this is the wave of the future, and leaders need to think about marketing and selling to agents, not just to humans.
I want to come back to what enterprises, CTOs specifically, should be doing. What’s your sense of overall enterprise preparedness, based on the work you’ve done? Your clients clearly respond with urgency but is that urgency enough, or is the world changing faster than companies can keep up?
The world is definitely changing faster than most companies can respond. AI moves at AI speed, but business still has a human component. We see the most effective, efficient movement where there’s strong C-level buy-in, a clear focus on business outcomes, willingness to invest and fail fast, and patience, you try five things, four might not work, but the one that does could be a game-changer. Whatever companies are doing now, there’s room to move ten times faster, and honestly, we’re all still slower than we need to be.
Going back to your detergent and moisturizer examples, that might surprise people, that there’s so much discussion happening around those categories. Are there geographic or other trends? For instance, is India searching for different things than Southeast Asia?
Definitely. One example that comes to mind from our IPL research is how conversation around jewelry and gold is far more significant in India than elsewhere. There are also generational nuances — in skincare, Gen X asks more about prevention, while younger generations ask more about sustainability and the environment alongside prevention. We see this play out geographically and demographically — our tool can show what’s happening in South Mumbai versus Thane versus Navi Mumbai, or break things down by persona. For an auto manufacturer, what’s the consumer thinking versus the dealer network? For a healthcare provider, what’s a patient thinking versus a prospective patient? You can slice AI visibility across any part of the ecosystem.
Let’s dig into CTOs and CMOs, they have to sit together and figure out how much to actually respond to. Say I make a product that’s 100 years old, that’s the original brand, and we do incremental innovation over time. Do I really need to respond just because 400,000 people online say a particular soap isn’t working well in my country? How do you calibrate that response, and what’s your advice?
For me, the tipping point is roughly 10% of your consumer base being active on these new platforms, at that point, as a business leader, you have to be where your consumers are. It’s that simple. ChatGPT and Perplexity, and Claude, are hitting those numbers in India very quickly. The old approach of “let this play out for a year or 18 months before I jump in” doesn’t work anymore, those windows are compressing to weeks and months, not quarters and years.
So once roughly 10% of your customers are using AI to ask about your product or service, that’s when you need to actively engage?
Absolutely. And even if the percentage of traffic from AI is lower than other channels, it converts four to five times higher than any other channel, so factor that multiplier in.
Among your clients, what kinds of changes are they actually making beyond aligning communication across platforms? What about the product or service itself?
There’s a lot of focus on training and understanding the platforms. We’re traveling globally to help clients understand how to use this. A lot of adoption spreads by word of mouth, one Fortune 100 company started with three brands in Q1, grew to 13 in Q2, and now has over 30 brands across five countries using the platform. That growth comes from word of mouth plus our execution-agent infrastructure, which helps close the gap between awareness and actual execution.
What do you see ahead? Before we started, you mentioned plans to grow further, possibly merging with or acquiring other players in this space. What challenges do you foresee, I’d assume the LLMs themselves are one, since they keep changing, along with consumers who are endlessly curious for more?
The way we look at it: first, how do we help CMOs and CEOs understand what their consumers are asking and how their brand is represented? A big area of investment for us is helping both companies and agency partners execute on recommendations, so the brand is presented accurately and in the right context. We’re also thinking a lot about inorganic ads, OpenAI is already doing this elsewhere, and it’s only a matter of time before it reaches India. How do organic and inorganic visibility interact? And how do we think about the broader world of AI-driven e-commerce? Those are our key areas of focus.
You seem to be working mostly with the more alert, agile enterprises. But for companies that have started this journey but still have a long way to go, how should they think about this opportunity, and how should they align their teams and build capabilities?
First, think of this as an ongoing engagement.
Particularly for large consumer-facing companies.
Right. It’s not a one-and-done project. Larger companies often tier their brands, some get an always-on strategy, with ongoing commitment to the right content, PR, partnerships, and creator strategy. Other brands might just want a “dipstick” check, say, five recommendations they can execute over three months. Companies are tiering their investment based on priority. My advice: start somewhere, and plan to scale quickly, that’s what will put you ahead.
Obviously most companies won’t have someone like you in-house. What kind of team should they build? Technology backgrounds? Something else entirely?
One thing we pride ourselves on is that our platform can function as an extension of lean marketing and agency teams. We also work extensively with partners like WPP and Performics, who bring structure and thought leadership to help clients execute.
Let me follow up on that for a mid-size, consumer-facing company trying to figure out how their internal team should look to navigate this world: some companies already have younger employees who intuitively understand this and are trying to fit them into the broader organizational structure. Others are trying to build an AI-ready team from scratch, potentially to work with companies like yours. What skills should they be looking for?
Great question. Typically, we see someone in the organization who’s forward-leaning, sees where things are headed, and champions the effort, it can come from anywhere. Sometimes there’s a Chief Innovation Officer or Chief Digital Officer already positioned for this. But often, it’s someone two or three levels down who spots the shift, champions it internally, and eventually connects it back to leadership. My advice to business leaders: identify the person with the foresight to match business problems with consumer and technology trends, and empower them to work across the organization, even if that means empowering someone one or two levels below the C-suite.
Earlier I asked what drew you to this problem but this is also your first entrepreneurial venture.
I’d actually consider building Facebook India an entrepreneurial venture in itself. It was a joy to build, back when—
Where did you come from before that? Were you hired elsewhere and sent to India?
For Facebook India specifically I actually came to India with Motorola. The startup I was working for got acquired by Motorola. I came expecting an 18-month assignment and ended up loving being back in the country. It was the early days of the internet in India. I reached out to Sheryl Sandberg and told her I’d love to be part of Facebook’s operations in India. We explored a few different roles and stayed in touch. About a year later, Facebook announced its intention to open an office in India, and I was honored to be part of that being part of the country’s shift to digital and mobile. Now I’m excited to be part of India’s AI-first journey.
Is your team based here?
We have a global team. My co-founder, Saurabh, and I know each other from our Meta days over a decade ago, he ran the creator economy, media, sports, and entertainment side there. He’s based in Oxford. We have teams across India, as well as in the UAE, Latin America, and the US. We believe we’re the only globally native company from day one addressing this problem, most other players started in the United States and expanded outward. We have a deep passion for global markets, and a particular passion for this region.
I wish you all the best, and thank you for joining us.
It’s great to be here, excited to be on this journey.
Thank you, and I look forward to doing this again.
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