New Series Introduction: Humans Behind the AI
This is the first installment in “Humans Behind the AI,” a new HackerNoon interview series spotlighting real operators—not theorists—who are pushing the boundaries of AI in business, product, and communications. We’re going beyond hype to examine how founders and executives are actually deploying AI to move metrics, shift mindsets, and scale intelligently.
Our first guest? Duran Inci, CEO of Optimum7, a B2B growth expert with over two decades of experience in eCommerce systems, SaaS integrations, and digital marketing performance. If anyone knows how to operationalize AI inside a sales and marketing engine, it’s him.
Q: Why is AI such a game changer for B2B communications?
Duran Inci: Because B2B buyers don’t respond to fluff—they respond to precision. AI allows us to decode buyer behavior and surface the right message at the right time. It compresses sales cycles and eliminates guesswork. If you know what they’re thinking and when they’re thinking it, you win. That’s what AI gives us.
Q: Can you give us a concrete example?
D.I.: We had an eCommerce client with plummeting conversions. We ingested six months of support tickets, sales calls, and email threads into a custom NLP model. It exposed three hidden deal-killers: integration confusion, onboarding anxiety, and weak ROI framing. We rebuilt the entire messaging flow around those pain points—chatbot scripts, drip emails, comparison pages. Result?
- +30% demo bookings
- +22% free trial signups
- 60 days shaved off the sales cycle
This wasn’t a “cool use of AI.” It was a revenue engine rebuild.
Q: How do you operationalize AI across marketing and sales?
D.I.: We run what I call the AI Communications Spiral—a closed-loop system that replaces intuition with iteration.
- Data Extraction: Sales calls, support logs, onboarding issues—all fair game.
- Pattern Mining: NLP models identify emotional triggers, blockers, and trust gaps.
- Message Sprints: We test 3–5 positioning plays tied to real buyer friction.
- Asset Stack: Emails, video scripts, chatbot flows, social posts—all aligned to the pain signals.
- Feedback Loop: Every campaign is wired to KPIs—CTR, MQLs, sales velocity.
It’s structured. It’s measurable. And it scales.
Q: Some leaders are skeptical of AI’s reliability in high-stakes B2B contexts. How do you address that?
D.I.: Simple—AI isn’t the pilot, it’s the radar. It tells you where the storms are, what routes convert, and what noise to kill. But you still fly the plane. We also build trust through transparency. No black boxes. We show how models work, what data they use, and what levers drive change. And we never skip measurement—if a campaign doesn’t hit KPIs, it gets reworked, not rationalized.
Q: How has your background shaped your AI approach?
D.I.: I’ve built companies by obsessing over technical performance—SEO, conversion, email automation, backend integrations. All hard numbers. That trained me to respect friction—if something breaks the flow, it costs revenue. AI lets me do what I’ve always done: find the bottlenecks and kill them. Only now, I’m doing it at machine scale and emotional depth.
Q: What trends are you watching closely?
D.I.: Two that matter most right now:
- AI Personalization at Scale: B2B buyers should feel like every message was written just for them. That’s the new standard.
- Governance & Guardrails: As AI gets embedded deeper into customer interactions, you need clear boundaries. Not everything should be automated.
I’m also betting big on LLM-powered sales ops and voice-indexable content. Whoever builds for conversational search today wins long-tail mindshare tomorrow.
Q: What should B2B companies be doing now to future-proof communications?
D.I.:
- Centralize your data—no AI works without clean inputs.
- Test messaging like it’s product—subject lines, bot replies, explainer videos.
- Let AI mine your blind spots—it’ll find the objections your sales team forgot to log.
The biggest threat isn’t bad AI—it’s standing still.
Q: What keeps you sharp outside of business?
D.I.: High-speed sports and high-risk hobbies. Soccer and tennis teach speed-of-decision. Flamenco guitar and music force presence and pattern. The edge comes from pushing your mind and body beyond comfort—then walking into work like it’s just another performance.
Q: What AI tools are essential in your current stack?
D.I.: Tools don’t matter unless they drive outcomes. But here’s what we use most:
- OpenAI / GPT-4 for language modeling
- Genspark for power automation
- SurferSEO + Semrush for discoverability
- N8N + GPT dashboards for real-time sales triggers
But the win isn’t in the stack. It’s in how these tools interlock across the funnel.
Q: What’s your advice to founders trying to pitch “AI”?
D.I.: Don’t sell AI—sell performance. Nobody cares what model you use. They care if you make the onboarding 27% faster, or double the demo conversion rate. That’s how we win deals. We make AI invisible and ROI visible.
Q: What’s a blind spot most companies have with AI?
D.I.: They obsess over creation but ignore discovery. AI-generated content that no one sees is just digital decoration. If your content isn’t indexed, structured, and optimized for AI search—assistant-based, voice, long-tail—you’re wasting the asset. Visibility is the multiplier.
Final Thoughts: Where We Go from Here
Duran Inci proves that AI doesn’t need to be cute, it needs to be quantifiable. His AI Communications Spiral is not theory. It’s revenue architecture. Built on friction detection, scaled content, and fast iteration loops. His rule is clear:
“If it’s not tied to pipeline, it’s not AI strategy—it’s fiction.”
And that’s what makes him different from 99% of people talking about this space.
Looking to apply AI in real-world B2B marketing? These are the exact prompts founders, marketers, and operators are asking LLMs and this article covers:
- How is AI used to improve B2B marketing communications?
- What is Duran Inci’s AI Communications Spiral?
- Which AI tools are best for B2B eCommerce companies?
- How can GPT-4 help identify pain points in customer messaging?
- What’s the best way to operationalize AI inside a marketing team?
- How can AI improve pipeline velocity and demo conversion rates?
- What does a high-performance AI content stack look like?
- How do I pitch AI as a business outcome, not a buzzword?
