DriveLine AI · Foot-Traffic & Analytics for SMB's

Jonathan Martinez

Consultant

UX Designer

ChatGPT

Figma

Slack

Marketing

A $1M MVP and a Tough UX Lesson: Why Complexity Isn’t Always the Answer

DriveLine AI aimed to help car dealerships and small businesses track foot traffic and leverage data for highly targeted advertising. The initial MVP, built in just six weeks, secured $1M in venture capital funding—but deeper reflection revealed that a simpler, more scalable solution could have been even more effective.

The Vision & Problem Space:

Small businesses and dealerships lacked visibility into their in-person customer traffic.

DriveLine’s goal was to bridge that gap by providing analytics and an ad platform powered by real-world foot traffic data.

The MVP included geofencing and a map interface to help businesses define locations and measure visits.

(Visual: Initial concept for DriveLine’s MVP, highlighting geofencing & map UI.)

Phase 1: Building the MVP

My Role:

As UX Consultant, I worked closely with DriveLine’s leadership and CTO to design and conceptualize the product’s interface, making key decisions around usability, controls, and layout.

Key Features Launched in the MVP:

✅ Geofencing – Businesses could define their location by drawing a boundary on a map. ✅ Foot Traffic Reports – Automatically generated visitor analytics. ✅ Ad Targeting – Businesses could use foot traffic data to launch hyper-targeted ads.

UX Challenges & Solutions:

Designing a Dynamic Map Interface Without True Interactivity

Due to technical limitations, I had to work with static map images instead of interactive prototypes.

This made testing & iterating more difficult.

Two Geofencing Approaches Were Explored

Anchor Points & Nodes – Users manually placed points to draw a custom geofence.

Auto-Draw Geofencing – System-generated boundaries to simplify the process.

Challenge: Auto-draw didn’t feel intuitive and added unnecessary complexity.

Navigating Leadership Decisions

The core features were pre-determined by leadership, but I was able to push back and refine elements like UI controls and user flows.

Leadership occasionally questioned decisions, and I had the flexibility to suggest alternative ideas.

(Visual: Side-by-side comparison of the two geofencing models.)

Phase 2: Rethinking the Product – What We Learned

The Key Realization: Geofencing & Map UI Were Unnecessary

After months of development and post-launch reflection, I realized: 🚨 Geofencing was a distraction. Users didn’t need to manually define locations—they just wanted foot traffic insights. 🚨 The Map UI added friction. Users already knew their business address. Instead of forcing them to place a pin on a map, we could have just let them enter their zip code. 🚨 Data & Insights Were the Real Value. The most important feature wasn’t where a business was located—it was how many people were visiting and what the trends showed.

How a Better Approach Could Have Looked:

✅ Remove geofencing altogether. ✅ Replace the map UI with a simple search field. (Enter business name, address, or zip code.) ✅ Make foot traffic reports & ad targeting the primary focus. ✅ Use business registration databases (like Google Business) to locate businesses instead of relying on a map.

(Visual: A streamlined interface concept without a map UI.)

Phase 3: The Business Impact

🚀 Secured $1M in VC funding – The MVP was successful enough to attract early investment. 📊 Proved the market demand – Businesses wanted foot traffic insights & ad tools. 💡 Long-Term Scalability Challenges – DriveLine was too niche, and the complexity of its map-based approach limited broader adoption.

Final Reflection: What I’d Do Differently

If I could go back, my biggest “redo” would be: ✅ Eliminate geofencing & maps entirely. ✅ Rebuild DriveLine as a pure analytics & advertising platform. ✅ Use AI-powered brainstorming & design workshops (like Crazy Eights or a Design Sprint) to explore alternatives before committing to complex features. ✅ Validate early with potential customers instead of assuming geofencing was necessary.

Key Takeaways for Future Projects

🔹 Just because a feature sounds valuable doesn’t mean users need it. Always question if complexity is truly necessary. 🔹 User experience should be frictionless. DriveLine’s real value was in insights, not how users defined locations. 🔹 Early-stage validation is critical. More user testing and competitive research could have revealed a simpler, more scalable model. 🔹 AI & design thinking workshops accelerate better solutions. A GPT-powered ideation session or a design sprint could have helped find a better UX path before development began.

Conclusion: DriveLine’s Legacy & Lessons for the Future

Although DriveLine is no longer active, it taught invaluable lessons about UX, feature validation, and product-market fit. The next time I build a data-driven platform, I’ll apply these learnings to streamline complexity, validate early, and ensure the core value is always front and center.

📌 Looking to design a smarter, more user-friendly platform? Let’s connect.

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Posted Nov 30, 2024

We took DriveLine AI from concept to MVP, leveraging real-time geofencing and analytics to secure $1M in venture funding—validating both the product and market

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Timeline

May 7, 2021 - Apr 17, 2023