Deepak Bahree’s most revealing marketing story begins with a dashboard, which is fitting for a man who studied electrical engineering before he learned to run a brand. His team at Birdeye had sent another report. This one showed that visitors arriving from ChatGPT, Perplexity, Gemini, and Claude were converting at roughly three times the rate of organic Google traffic. The volume was still smaller. The quality was not. “My team sends me a lot of dashboards,” he wrote. “Every now and then, one makes me stop.”
Many executives would turn a number like that into a trumpet. Bahree turned it into a question. If large-language-model traffic was arriving with stronger intent, how did a brand earn its place inside the answer that sent the visitor? And for a company with hundreds of addresses, which version of the brand did the machine see?
That second question is the more interesting one. A national logo suggests unity. Local commerce supplies mutiny. Store hours drift. Reviews age at different speeds. One branch becomes beloved while another becomes invisible. The corporate average sits in the middle, looking respectable and concealing the plot.
Bahree’s work as chief marketing officer of Birdeye lives in that gap between the clean brand and its messy local lives. His thesis is that AI should not merely describe the gap. It should help close it.
The engineer kept his scorecard
Bahree graduated from the Indian Institute of Technology in Varanasi in 2003 with a degree in electrical engineering. Two years later, he entered the Indian School of Business, where his MBA combined analytical finance and strategic marketing. His public education record also lists a 760 GMAT score, a tiny biographical detail that somehow feels entirely on brand: even the prelude arrives with a metric.
He then built a career inside the plumbing of modern enterprise software. Hewlett-Packard and VMware gave him early ground in digital strategy and analytics. At RingCentral, he became vice president of digital marketing. At Automation Anywhere, he led global digital marketing as a senior vice president. In 2022 he took the CMO role at strategy-execution company WorkBoard. By early 2023, he had joined Birdeye as CMO.
The companies changed with the fashions of the valley: computing, virtualization, cloud communications, robotic process automation, strategy software, customer experience. Bahree’s method remained unusually steady. He gravitated toward products that translate complex systems into repeatable work, and toward marketing that can be inspected by what happens next.
This makes him a useful character in the current AI carnival. The technology is theatrical; Bahree is interested in stagehands. He speaks less about which model wins and more about whether a connected system can complete a job. In his vocabulary, the glamorous noun is usually followed by an operational verb.
“As a CMO, I know the hard part is not talking about AI. It is turning AI into everyday execution.”Deepak Bahree, 2026
One logo, a thousand small reputations
Traditional marketing automation grew up imagining a centralized funnel. A campaign begins, a prospect moves through stages, and a dashboard records the journey. Bahree argues that this picture breaks when a brand contains hundreds or thousands of locations. Each address has its own search presence, reviews, customer messages, operating quirks, and moments of neglect. A franchise in Phoenix and a branch in Pittsburgh may share a typeface. They do not share Tuesday’s customer experience.
He calls them micro-funnels. It is not a poetic term, but it is an accurate one. A customer may encounter an AI answer, check a map, scan recent reviews, compare hours, send a message, and decide within minutes. The sequence is local, high-intent, and extremely easy for a broken detail to interrupt.
or search
and hours
and trust
or visit
Birdeye’s 2026 analysis of more than 16,000 ChatGPT scans across over 1,500 multi-location brands put figures around the problem. About one in five locations never appeared in the answers. Nearly half of the brands studied had a gap of at least 50 points between their best- and worst-performing locations. Fewer than one percent of locations returned a fully correct profile across name, address, phone, website, and hours.
These are company findings, and Bahree’s interpretation is the revealing part. “AI search is not one score,” he said. A headquarters-level view can look reassuring while a useful location disappears at the exact moment a customer is ready to choose. The average is not merely incomplete. It can be a very elegant disguise.
His preferred question is correspondingly blunt: “Which locations do we fix first, and what exactly do we do?” It moves the CMO from commentary to triage. Measurement has to identify the weak point. The system has to recommend the action. Then somebody, or something, must carry it out.
Past the demo, into the working day
At Birdeye’s View 2025 event, Bahree delivered the product keynote on the company’s move from generative AI toward agentic marketing. He described systems meant to monitor signals and act across search, reviews, listings, social content, and customer interactions. He also sat down with Sherwin Wu, then leading engineering for the OpenAI API, for a conversation about how AI was changing consumer search.
Later sessions with Neil Patel took the argument into the zero-click world, where a customer may form an opinion from an AI summary without visiting the company’s website. Reviews, brand mentions, citations, and structured local information become part of the product whether the product team likes it or not. Reputation stops being a lacquer applied after the work. It becomes an input to discovery.
By 2026 Bahree was helping turn that argument into a small media and peer network. The Agentic CMO podcast brought him together with leaders managing complicated location portfolios. An awards program selected 60 marketing executives from 750 nominations, judged on AI strategy, operational integration, speed, measurable impact, and influence. There is marketing in such a program, naturally. There is also a practical recognition that transformation spreads through examples faster than it spreads through manifestos.
His own podcast episode made the principle explicit: outcomes over models. Marketers, he argued, should move beyond debating ChatGPT, Claude, or Gemini and build connected workflows that produce business results. Model names age quickly. A completed job retains its charm.
“The harder question is operational: which locations do we fix first, and what exactly do we do?”Deepak Bahree on location-level AI visibility
A marketer of systems, not magic
Bahree’s public persona is disciplined, but not bloodless. He has called himself a tech-toy nerd. He writes warmly about customers and colleagues, and Birdeye’s own brief biography says he loves delighting customers with innovative products. After a podcast guest described using Meta glasses, Bahree admitted that the example lingered with him. The gadget enthusiast and the measurement executive appear to coexist quite happily.
That pairing may explain his usefulness as an interpreter. He is curious enough to entertain the new machinery and skeptical enough to ask for its shift report. His career has repeatedly placed him between technical products and commercial audiences. The task is translation: turn infrastructure into a reason to care, then turn attention into evidence that something worked.
The aspiration now is larger than optimizing a campaign. Bahree wants marketing systems to absorb signals, understand local context, and execute within central rules. It is an operator’s vision of the CMO role. Brand remains important, but brand alone cannot correct the wrong closing time in a search answer or rescue a location whose latest reviews have gone unanswered.
There is also a quiet argument here about scale. For years, software promised to give a small team leverage. Multi-location businesses exposed the bargain’s fine print: the same tool multiplied the setup, duplication, and maintenance work across every branch. Bahree’s version of agentic marketing asks the machine to shoulder that repetition while people decide the goals and boundaries.
Whether that promise holds will be visible in the same place his story began: the dashboard. Are more locations discoverable? Are their details right? Are customers converting? Has the work actually been done? Bahree does not need AI to sound intelligent. He needs it to make the scattered edges of a brand behave as though somebody is paying attention.
That is a less dazzling ambition than synthetic omniscience. It may also be more valuable. In Bahree’s world, the future of marketing arrives one location at a time, checks the hours, reads the reviews, and gets to work.