How Real-World User Motives Shape Modern Map Design

Every day countless position migrations occur around us; behind these simple displacements lie deeper user details. Former Baidu Maps travel direction design lead Zhu Hequn shares insights on real‑world travel motivations and how to better understand the essence of travel.

Mapping the Real World

Accuracy is essential for maps, but the core value of a map tool product is to answer three questions: Where am I? Where do I want to go? How do I get there? Beyond the A‑to‑B journey, we must consider why users travel, such as visiting a discount store during Double 11.

Digging Into User Value

Optimizing the A‑to‑B process involves offering multiple transport options—bus, subway, shared bike, taxi, walking—and handling incidents like accidents, bad weather, or congestion. Users decide based on time, cost, and comfort.

Maps now go beyond simple navigation to provide diversified services. For example, a user searching for a location may actually want to eat at a nearby restaurant, making proximity more important than the exact address.

Map 3.0 Services

4K Map : Offers richer, more precise road details (overpasses, one‑way streets, pedestrian paths, highway exits) and recommends clear pick‑up points for taxis, improving driver parking and reducing wait time.

3D Map : Provides depth for cities with complex geography, helping users understand their exact position.

Aggregated Service Information : POI pages display surrounding housing, traffic, and other services, aiding decisions about residence and commute.

AOI (Area of Interest) Scenario Maps : Context‑based services that prioritize nearby amenities (e.g., recommending a restroom on the same side of the street).

Mixed Travel Modes

Travel decisions consider time, cost, and comfort. Users may combine modes—driving to a park, then biking five kilometers, then driving back—to achieve a higher quality of life.

Understanding true user needs involves not just solving A‑to‑B but also leveraging big data to weight various dimensions and present optimal solutions.

Balancing Travel Variables

Environmental Weather Variables : • Flood maps help drivers avoid water‑logged roads. • Smog maps guide users to choose healthier travel modes.

Incident Variables : • Road condition predictions use accident data and congestion handling efficiency to forecast future traffic states.

These variables together enable precise, real‑world mapping and deep human insight, delivering effective travel solutions.

Q&A Highlights

1. What can interaction or research roles do for tool‑type products? Zhu emphasizes efficiency as the core value, recommending design principles (addition/subtraction, consistency), maintaining uniformity across industry standards, and fostering creativity. He suggests using the Kano model to prioritize features.

2. How to uncover simple tool product needs? By packaging services—e.g., streamlining phone‑bill recharge with auto‑fill, adding “order again” shortcuts, and considering the broader context (who the recharge is for, frequency) to enhance the core function.