A few weeks ago, I decided to run an experiment.
What if I handed a classic GTM challenge to AI—end-to-end—and simply watched it think?
So I gave it a fairly loaded prompt:
“Build me a 360-degree go-to-market strategy for a premium chocolate brand launching in Southeast Asia. Include market segmentation, ICPs, positioning, messaging, pricing, offline and online channels, and contingency plans.”
And then I waited.
What came back?
Not just marketing ideas.
Not just generic frameworks.
But a structured, layered, and shockingly nuanced GTM strategy that felt eerily like something you’d pay a high-end consultancy to build over 6 weeks.
Here’s a breakdown of what it delivered—and what I loved about it.
1. Market Segmentation with Contextual Depth
The AI didn’t just spit out “Southeast Asia = emerging market.”
It is sliced by consumer behavior, digital maturity, and cultural taste preferences.
For example:
- Singapore: Affluent market, values sustainability, leans toward artisanal & sugar-free options.
- Thailand: Trend-driven Gen Z buyers, big on social commerce, open to playful brand narratives.
- Philippines: Family-oriented gifting culture, impulse buys in retail-heavy environments.
- Indonesia: Health-conscious urban millennials, price-sensitive but experience-seeking.
What I loved:
AI didn’t just map the territory. It mapped the psychology of the buyer. That’s gold in GTM.
2. Intelligent Persona Crafting
It gave me three well-defined ICPs:
- The Mindful Indulger – urban, wellness-aware, interested in guilt-free luxury
- The Gifter – emotional buyer, driven by holidays, relationships, and presentation
- The Trend Hunter – young, social-first, looking for the “next cool thing”
Each came with:
- Needs & triggers
- Messaging preferences
- Channel affinity
- Likely objections
What I loved:
This is not static segmentation—it’s narrative-ready. Plug-and-play into creative briefs.
3. Full-Funnel Channel Mix & Launch Strategy
The AI proposed a phased GTM:
- Phase 1: Brand seeding via micro-influencers + curated pop-ups in premium malls
- Phase 2: eCommerce push on Shopee/Lazada with bundling + gamified loyalty
- Phase 3: In-store retail rollout with QR-driven sampling + localized promo weeks
It even optimized channel priority by country, recommending:
- LINE + TikTok for Thailand
- WhatsApp commerce for Singapore
- OOH + Facebook for the Philippines
What I loved:
This isn’t “go omnichannel.” It’s go relevant channel. That nuance is everything.
4. Pricing & SKU Strategy with Elasticity Assumptions
The AI designed 3 price tiers:
- Impulse Minis: $1–$1.50
- Gifting Packs: $4.99–$7.99
- Premium Boxes: $10–$15
Each matched to:
- Persona segments
- Basket size trends by region
- Promotion levers (e.g., bundling during Valentine’s)
What I loved:
Most marketers guess price before market fit. This built pricing around persona behavior.
5. Contingency Playbooks
Then it surprised me.
The AI added:
- If sales lag: Flash influencer takeovers + scarcity drops
- If reviews drop: Partner with nutritionists for trust boost
- If a competitor enters: Region-specific loyalty schemes + product line extensions
What I loved:
Crisis GTM planning—without being asked. That’s strategy, not just copy-paste AI.
This wasn’t about “AI doing marketing.”
It was about what happens when AI meets strategic intent.
The GTM output wasn’t perfect.
But it was 80% thinking-ready in 20% of the time.
And for someone like me—who lives and breathes GTM—it was exciting, not threatening.
Because GTM is about velocity, insight, and adaptability.
AI just gave me all three—in a single run.
Now, imagine this:
If this is what AI can unlock without any human intervention…
Imagine what’s possible when you pair it with a network of AI-mastered agencies—strategy leads, creatives, and growth experts who speak the same AI-native language.
That’s not just acceleration. That’s a quantum leap.
And that future? It's already in motion.
Drop a 🍫 below or DM me. I’ll share the behind-the-scenes.
#GTM #ArtificialIntelligence #MarketingStrategy #SoutheastAsia #ProductLaunch #AjayMohan #AIxMarketing