Deliver's growth stagnated until they shifted from complex, variable fees to a simple flat rate. This treated pricing not as a billing model but as a product feature that solved the customer's core need for financial predictability, which became their primary growth catalyst.
The entrepreneurial journey is mentally taxing due to constant high and low swings. The founder's coping mechanism is to anchor himself to what's controllable: delighting the customer. Focusing on product and user feedback cuts through the noise of fundraising, competition, and existential dread, providing a stable focal point.
After 9 months of stagnation, Deliver implemented two key changes based on customer feedback: a "Prime-like" badge to surface the value of fast shipping earlier in the funnel, and a flat-rate pricing model for predictability. These two changes combined created an immediate inflection point, leading to explosive growth.
To scale, Deliver needed a self-serve system for a high-stakes transaction: taking custody of a merchant's entire inventory. They achieved this by building systems that fostered trust through radical transparency, like photo evidence for discrepancies. This proved self-serve can work for complex, high-trust sales.
Contrary to the "growth at all costs" mantra, early Amazon showed that rapid scaling can be done responsibly. The key was a disciplined financial model that clearly projected how unit economics (e.g., cost of goods) would improve and lead to profitability as the company reached specific scale milestones.
Deliver's founder admits their logistics model (distributed inventory) wasn't a unique insight; Amazon had already mastered it. The true innovation was recognizing that the rise of Shopify created a new, underserved market of small merchants. By aggregating their inventory, Deliver could offer them Amazon-level fulfillment infrastructure.
To find product-market fit, Augment's team shadowed logistics operators for 60 days. This revealed a deeper problem than leaders described: massive email noise from listservs used as a workaround for 24/7 coverage. Building for the operator's messy reality, not the CEO's summary, is crucial for adoption.
Past tech solutions for fragmented industries like logistics often failed because they required universal adoption of a new platform. AI can succeed by meeting users in their existing, messy channels—email, texts, calls. It automates work within current workflows rather than forcing a difficult behavioral change, lowering adoption barriers.