How 58 Household Service Transformed Home Care with Smart User‑Centric Design

Background

With rapid social change, the domestic service industry has shifted from traditional operations to a flexible "Internet+Domestic" model, using platforms to raise service quality and meet growing demand.

Current Practice

Most platforms maintain worker information through WeChat groups, using "order tossing" to let workers self‑recommend or co‑order with other merchants, completing order matching.

Problems

Worker information changes quickly, creating a short matching window.

High matching cost for merchants.

Merchants must manually maintain many WeChat groups to access fresh resources.

Passive, uncontrolled distribution can lead to order overload and unpredictable propagation.

Solution Overview

58 Household Service migrated the offline order‑tossing model online, creating an intelligent supply‑demand matching system for domestic workers and merchant orders. This lays the foundation for a streamlined flow: sales leads → worker matching → service signing → revenue distribution.

By aligning business goals with deep user insight, the platform provides a high‑quality order‑receiving environment for workers and a flexible order‑creation tool for merchants, achieving precise "person‑order" matching.

User Research & Design Strategy

The platform refers to domestic workers as "Aunties" and prioritizes their experience, aiming to improve usability and practicality.

Through multiple research methods, a accessibility‑focused design plan was created to meet Aunties' needs.

Auntie‑Side Design (Accessibility Principles)

Three core principles guide the design: clear and accurate information, clear perception, and simple operation.

Research showed a 16 px base font size best serves Aunties, establishing typography and spacing standards while allowing flexibility for visual needs and information density.

Page types are distinguished:

Browsing pages : Emphasize information readability; reduce spacing between items to increase content density while keeping font size.

Operation pages : Prioritize functional interaction; use selection‑type controls, enlarge touch targets, and provide clear feedback (e.g., checkmarks) to reduce errors.

Merchant‑Side Design (Intelligent Person‑Order Matching)

Customer requirements are finely segmented into modules, enriching each content point.

Traditional single‑choice or multi‑choice selectors are insufficient; a dual‑slider selector allows merchants to set specific values or ranges (e.g., height, weight, age, salary), enabling precise demand definition.

This enhances matching accuracy between workers and merchants, addressing information asymmetry and creating a smarter supply‑demand relationship.

Conclusion

Viewing the "merchant order demand – domestic worker" matching from a new angle reveals deeper user needs. With the established design strategy, the platform continuously refines its online service system, distilling and exposing information to improve experience, achieving coordinated optimization for both B‑side workers and merchants while satisfying C‑side customer demands.