Project Case
Pre-Master Education Service
A 0-to-1 education service built through content trust, campaign conversion, community operations, and service delivery.
Role
Content acquisition / Campaign design / Community operations / Service delivery
Stage
From demand validation to structured operations
Key Outcome
Used public content, admissions campaigns, and community delivery to validate paid consulting demand and build a repeatable service workflow.
Background
Pre-Master started from a clear education-consulting problem: students needed practical information on school selection, portfolio preparation, written materials, interviews, and application timelines before they could trust a paid service.
Problem
For an early education service, trust is the real first product. Users rarely convert only because a service exists; they need to see credible knowledge, a clear offer, and a delivery process that feels dependable.
Approach
I helped connect the front and back ends of the service: writing platform content, supporting admissions posts and campaign offers, designing service tiers, operating communities, coordinating tutors, and turning repeated questions into clearer delivery workflows.
Analysis Process
Build trust with public content
Zhihu articles answered concrete study-abroad and architecture-application questions, turning scattered user uncertainty into searchable, shareable information.
Capture demand with admissions campaigns
WeChat admissions posts acted as campaign pages: they explained service tiers, clarified what each offer included, and used group-discount mechanics to lower the decision threshold.
Turn consulting into a service system
The service was split into scanning, VIP tutoring, and mock-interview products, making the offer easier to understand and the delivery process easier to coordinate.
Use community feedback to iterate
Questions from communities, comments, and consultations helped identify what users were still confused about, which then fed the next round of content, service scripts, and delivery improvements.
Key Evidence
Paid consulting
150+
Validated that users were willing to pay for application guidance, tutoring, and decision support once trust and service scope were clear.
Community users served
1000+
Community operations turned one-off inquiries into a larger service pool for Q&A, follow-up, and repeated user feedback.
Article reach
2.6w+
A school-recommendation article became a high-reach trust asset, showing that practical application information could attract users before direct conversion.
Campaign offer
3 tiers
The admissions activity packaged services into scanning, VIP tutoring, and mock interview products, with group discounts supporting referral-style acquisition.
Education service growth loop
The core value was not a single channel, but the loop from public knowledge to campaign conversion, delivery, and feedback.
Content trust
Zhihu articles and education posts
Answer real application questions first, so users can judge expertise before entering a paid conversation.
Conversion page
WeChat admissions post and group offer
Make the service scope, price ladder, and action path explicit enough for users to decide or refer friends.
Service delivery
Tutoring, mock interview, and community support
Break consulting into deliverable modules so the team can coordinate work and users know what they will receive.
Feedback iteration
Comments, questions, and consultation records
Use repeated confusion as input for the next content topic, service explanation, and operational script.
Decision Logic
Education consulting sells trust before it sells service
High-intent users need evidence that the team understands their questions. Public content works as a trust layer before paid conversion.
Discounts should reduce friction, not weaken value
The group-discount activity made the decision easier and encouraged peer sharing, while the tiered package still kept service value visible.
A service business becomes scalable when questions become modules
Repeated user questions can be converted into content, templates, tutoring modules, and community answers instead of staying as one-off labor.
Findings
The project validated paid demand, supported a large user community, and connected content acquisition with service delivery. It also trained my ability to design a user journey across trust-building, conversion, operations, and post-service feedback.
Key Outputs
- Zhihu-style education articles and application knowledge content
- WeChat admissions campaign post and offer structure
- Group-discount acquisition mechanism
- Scanning, VIP tutoring, and mock-interview service tiers
- Community Q&A and user follow-up operations
- Tutor coordination and delivery workflow
- Reusable explanations for school selection, documents, and interview preparation
Reflection
This project made me realize that 0-to-1 work is less about making something look complete at the beginning, and more about turning uncertainty into a loop: answer what users ask, package what they need, deliver what was promised, then use the next round of feedback to make the system clearer.