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B2B Corner Stores
How I rebuilt B2B acquisition for a low-literacy audience by turning "audio chaos" into structured system data.
Scale order volume without hiring more CS staff.
Audience cannot read well & relies on voice notes.
If CS keeps doing manual entry, Ops collapses.
Z Systems: The unified platform connecting B2B, B2C, and Enterprise feedback loops in one space.
AWAL (My Role): The B2B arm serving corner stores. My job was to feed the Z Systems ecosystem with high-frequency B2B orders from this hard-to-reach audience.
Before this rebuild, 80% of orders came via chaotic phone calls and voice notes. The system was blind and drowning.
Survival Constraint: If we didn't automate the audio, we couldn't scale.
This wasn't a clean linear process. It was a messy overhaul of Brand, Tech, and Ops simultaneously.
I audited the entire history from top to bottom. The brand was hurting. Before we could ask them to trust an automated system, we had to fix the relationship.
I didn't just run ads. I ran a full Awareness Campaign:
→ Outdoor Series: Placed physical ads in neighborhoods where store owners live.
→ Social Proof: Filmed interviews with successful shop owners.
To manage expectations, I needed all data in one place. I installed a complete tracking suite to capture every interaction.
This moved us from "guessing" to knowing exactly which outdoor ad or digital campaign drove the most high-value leads.
We didn't fight their behavior; we upgraded it.
1. User sends audio ("I need milk...").
2. ChatGPT transcribes & formats it.
3. System replies with 2 Buttons (Yes/No in Arabic).
4. If "Yes", order generates automatically.
Automation needs rules. I set up strict logic to filter waste and build trust.
Is the order above $25?
Has user completed 3+ orders?
User is trusted. Fulfill immediately.
We could have automated every order from Day 1, but we chose not to.
The real challenge was building trust. Corner shop owners were skeptical. If the first automated order failed or had the wrong product, we would lose them forever.
The Trade-off: Keeping CS involved for the first 3 orders was "inefficient" on paper, but it was the only way to safeguard retention. We traded speed for trust.
This turned AWAL into the high-frequency engine that Z Systems needed.
See how the same growth thinking applies across industries.
Rebuilt attribution and scaled B2B/B2C funnel to seven-figure ARR.
Read Case Study →Validated Product-Market Fit in 72 hours with positioning tests and paid experiments.
Read Case Study →Want the frameworks behind these results? Browse the Growth Library →
I help companies like AWAL & Z Systems build engines that respect reality in the field, not just standard playbooks.
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