# Square: Commerce Infrastructure for the Regulated Economy The conversation began with HIPAA, the bread, the butter, and all of the data in between. At Kaiser, I was responsible for the business functionality of middleware APIs that processed millions of healthcare transactions daily. Certificate management, vetting unsupported data flows, building technical architectures to present to business partners with various avenues for completion, dialed to risk, cost, and timeline. Overseeing transparency of APIs during an extended cloud migration. HIPAA compliance wasn't a checkbox, it was the architecture. Every data flow, every handoff, every audit trail had to be airtight. When I look at Square, I see the same fundamental tension: how do you build infrastructure that's fast, flexible, and accessible while protecting the most sensitive data people have? Their money. Their business. Their livelihood. Healthcare taught me that regulated industries don't tolerate "move fast and break things." You move deliberately and build things that don't break. And when they do, you know exactly why, exactly where, and exactly how to fix it. --- ## The Familiar Square I know Square the way most people know Square: the little white reader at my favorite coffee shop, the tap-to-pay at the farmers market, the receipt that shows up in my email before I've pocketed my phone. But there's so much more, isn't there? Square is payroll, inventory, appointments, loans. A full-stack operating system for businesses that used to need five different vendors, five different logins, five different reconciliation nightmares. The thesis: **One platform. Infinitely flexible. Accessible to the food truck and the franchise.** --- ## The Competitive Landscape | Platform | Best For | Starting Point | Distribution Model | |----------|----------|----------------|-------------------| | **Square** | SMB generalist, quick-service, services | $0/month, pay per transaction | Direct marketing, self-service | | **Toast** | Full-service restaurants | $0-69/month + hardware | Direct sales force, local market expertise | | **Clover** | Retail, high-volume, flexibility seekers | $14.95-89.95/month | Indirect (banks, ISOs, VARs) | | **Shopify POS** | eCommerce-first brands | $0 with Shopify plan | Cross-sell to 3M+ existing merchants | | **Lightspeed** | Multi-location, inventory-heavy | $89/month | Direct + channel partners | ### Where Square Wins - **Accessibility:** No contracts, no hefty upfront costs, no "call for pricing." A food truck owner can download the app, plug in the reader, and start taking payments in an afternoon. That's democratization. - **Ecosystem cohesion:** Toast owns restaurants. Shopify owns eCommerce. Square owns *everything in between*. The salon that sells products, the cafe that does catering, the consultant who invoices and takes card payments. - **Financial services integration:** Square Capital, Cash Flow management, and Bitcoin acceptance are embedded at the point of sale. No context-switching to a bank portal. ### Where Square Gets Challenged - **Depth vs. breadth:** Toast's restaurant-specific features (tableside ordering, tip pooling, kitchen display systems) go deeper than Square for F&B. Shopify's eCommerce engine is more powerful for DTC brands. - **High-volume economics:** As transaction volume grows, Square's flat-rate processing (2.6% + $0.10) can become more expensive than interchange-plus pricing offered by Clover or Helcim. - **Enterprise complexity:** Multi-location chains with complex inventory, supply chain, and compliance needs may outgrow Square's generalist approach. --- ## The Prospect Cost Formula A PM thinking about seller acquisition might model the decision like this: ``` TCO = Setup + (Monthly × 12) + (Transaction × Rate × Volume × 12) + Hardware + Migration + Downtime ``` ### Example: Coffee Shop Processing $30K/month | Platform | Setup | Monthly | Processing (annual) | Hardware | **Year 1 TCO** | |----------|-------|---------|---------------------|----------|----------------| | Square | $0 | $0 | $9,756 (2.6% + $0.10) | $149 (Stand) | **$9,905** | | Toast | $0 | $0 | $10,440 (2.9% + $0.15) | $0 (free terminal) | **$10,440** | | Clover | $0 | $1,079 ($89.95 × 12) | $8,640 (2.3% + $0.10) | $849 (Mini) | **$10,568** | Square wins on TCO for this profile, but the formula changes as volume scales. ### The Hidden Variable: Time If Square AI saves 100 hours/year (per their case studies), and a small business owner values their time at $50/hour, that's $5,000 in implicit savings that doesn't show up in the TCO formula but absolutely factors into the decision. --- ## What Metrics Might a Square PM Obsess Over? ### Seller Health Metrics - **Gross Payment Volume (GPV):** Total transaction value processed - **Seller Retention Rate:** Month-over-month, cohort-based - **Multi-Product Adoption:** % of sellers using 2+, 3+, 4+ Square products - **Time to First Transaction:** Onboarding velocity - **Net Revenue Retention (NRR):** Do sellers grow with Square over time? ### Product-Specific Metrics - **Square AI Query Volume:** Questions asked per seller per month - **AI Resolution Rate:** % of queries that surface actionable insight without human escalation - **Voice Ordering Adoption:** % of eligible F&B sellers using AI phone ordering - **Feature Activation Rate:** % of sellers who enable a feature within 30 days of availability ### The North Star **Seller Success Rate:** What percentage of businesses that start with Square are still operating (and growing) one year later? This is the metric that ties everything together. If Square is truly an "always-on partner" for local businesses, the proof is in their survival and growth. --- ## Square in an AI-First World Willem Avé, Square's Head of Product: *"Local businesses face the same complexity as large enterprises, but with fewer resources. Owners juggle marketing, bookkeeping, customer service, and operations. Square AI is our small, early, but ambitious start to being your thought partner."* Today, Square AI is a conversational assistant in the Dashboard, answering questions about sales, inventory, and staffing while pulling in weather, local events, and reviews to contextualize decisions. But where does this go? ### The Vision: Square as the Seller's Second Brain Imagine a future where the Square interface isn't a dashboard you check. It's a partner that checks on you. - **Proactive alerts:** "Rain forecast tomorrow. Last three rainy Tuesdays, your foot traffic dropped 40%. Consider a promo push to your loyalty members?" - **Automated actions:** "Your oat milk supplier raised prices 8%. I found a comparable option at your current rate. Want me to switch your next order?" - **Cross-seller intelligence:** "Coffee shops in your neighborhood are seeing a 15% bump in afternoon sales from adding cold brew nitro. Here's what the top performers are pricing it at." The AI asks the questions first. --- ## What Would a Square-Only AI Interface Look Like? Forget the dashboard. Forget the app. What if Square was just... a conversation? ``` ┌─────────────────────────────────────────────────────────────────────┐ │ ╔═══════════════════════════════════════════════════════════╗ │ │ ║ SQUARE AI ║ │ │ ║ Your business, one conversation. ║ │ │ ╚═══════════════════════════════════════════════════════════╝ │ │ ┌─────────────────────────────────────────────────────────────┐ │ │ │ Good morning, Aleks. Here's your daily briefing: │ │ │ │ 💰 Yesterday: $2,847 (↑12% vs. last Tuesday) │ │ │ │ 📦 Low stock: Oat milk (2 days), Cup sleeves (4 days) │ │ │ │ 👥 Staff: Maria called out. I've texted backup list. │ │ │ │ 🌧️ Weather: Rain at 2pm. Last rain day: -23% afternoon. │ │ │ │ [Reorder supplies] [Approve shift coverage] [Run promo] │ │ │ └─────────────────────────────────────────────────────────────┘ │ │ ┌─────────────────────────────────────────────────────────────┐ │ │ │ You: "What's my best margin item this month?" │ │ │ └─────────────────────────────────────────────────────────────┘ │ │ ┌─────────────────────────────────────────────────────────────┐ │ │ │ Square AI: │ │ │ │ Your top 3 by margin: │ │ │ │ 1. House drip coffee 82% margin $1,240 profit │ │ │ │ 2. Avocado toast 61% margin $890 profit │ │ │ │ 3. Cold brew (16oz) 58% margin $720 profit │ │ │ │ Insight: Your cold brew margin dropped 8% since you │ │ │ │ switched suppliers in January. Want to compare options? │ │ │ │ [Compare suppliers] [See full margin report] [Dismiss] │ │ │ └─────────────────────────────────────────────────────────────┘ │ │ ┌─────────────────────────────────────────────────────────────┐ │ │ │ You: "How do I compare to other coffee shops nearby?" │ │ │ └─────────────────────────────────────────────────────────────┘ │ │ ┌─────────────────────────────────────────────────────────────┐ │ │ │ Square AI: │ │ │ │ Compared to coffee shops within 2 miles (anonymized): │ │ │ │ Avg ticket: You: $8.40 Area: $7.20 (↑17%) │ │ │ │ Loyalty rate: You: 34% Area: 28% (↑6pts) │ │ │ │ Peak hour: You: 8-9am Area: 8-9am (same) │ │ │ │ Weak spot: You: 2-4pm Area: 2-4pm (industry) │ │ │ │ Idea: Top performers in your category run 2-4pm promos │ │ │ │ via loyalty. Want me to draft one? │ │ │ │ [Draft promo] [See what's working] [Not now] │ │ │ └─────────────────────────────────────────────────────────────┘ │ │ ───────────────────────────────────────────────────────────── │ │ │ Ask anything about your business... 🎤 │ │ │ ───────────────────────────────────────────────────────────── │ └─────────────────────────────────────────────────────────────────────┘ ``` ### The Interface Principles 1. **Ambient, not intrusive:** The AI surfaces what matters. You engage when ready. 2. **Action-oriented:** Every insight comes with a next step. Not "here's data" but "here's what to do about it." 3. **Contextual intelligence:** Weather, events, local trends, your history, your competitors (anonymized). All synthesized. 4. **Voice-first optional:** The coffee shop owner checking in at 5am while prepping doesn't want to type. 5. **Trust through transparency:** "Here's why I'm suggesting this. Here's the data behind it. Here's what I don't know." --- ## The Deeper Point Square's AI ambition is fundamentally changing the relationship between a business and its tools. Today: You go to the tool. You pull reports. You interpret. You decide. Tomorrow: The tool comes to you. It synthesizes. It recommends. You approve. The seller becomes the decision-maker, not the data-gatherer. That's the unlock. And for someone who spent years building systems where compliance, auditability, and trust were non-negotiable, I see the same challenge ahead: **How do you build an AI partner that a seller trusts with their livelihood?** The answer is building systems that explain themselves, that fail gracefully, that know when to ask for help. That's the work I want to do. --- ## Links - [[Pylon Case Study]] - Omnichannel support platform analysis - [[Product Explorations]] - More product thinking --- *Last updated: February 2026*