English Product Growth

From March through October 2025, I led the English app and its iteration portfolio. I reframed the work from operating translated content to building a growth product where content, social, growth, service design, and engineering shared the same goals and evidence.

The initial data showed English free-reading usage at 44.75%, compared with 67.82% in the Korean app. New users who used one free reading had 8.89% retention, while the ten-use cohort reached 30.86%. I translated that gap into a product mission: help new users discover value sooner and return to it more often.

English free-reading usage

44.75%

Korean app benchmark

67.82%

One-use vs ten-use retention

8.89% / 30.86%

Usage · new-user retention goals

60% · 15%

My first priority was clarifying the team structure and each person's roles and responsibilities across content, social, growth, service design, and engineering.

I established a weekly meeting rhythm: review the data, check the previous week's work, agree priorities for the coming week, and align on strategy. Each owner executed their area, while I kept the team focused on shared goals and the next decision.

Instead of sending every campaign to one generic store page, I established content-specific ASO pages aligned with each ad and content promise. The team ran 29 Android and ten iOS experiments and reused proven structures as the standard for the next page.

Android install conversion grew 2.05x, from 16.3% to 33.4%, while iOS improved from 2.6% to 4.8%. Content-specific store pages averaged 28.9% conversion.

ASO portfolio

39 experiments

Android install conversion

16.3% → 33.4%

iOS install conversion

2.6% → 4.8%

Custom-page average conversion

28.9%

I moved the core action ahead of product explanation, inviting new users to enter their birth data and start the experience immediately. We also rebuilt access to the daily content that could create a repeatable habit.

Comparing the March average with the first three weeks of October, new-user Daily Horoscope touch rate rose from 27.24% to 51.40%, and Daily Luck usage from 25.05% to 39.76%. Free-reading visits increased from 69.43% to 79.34%, while free-reading EPU grew from 9.65 to 13.63.

Daily Horoscope touch rate

27.24% → 51.40%

Daily Luck usage

25.05% → 39.76%

Free-reading visits

69.43% → 79.34%

New-user free-reading EPU

9.65 → 13.63

To help users discover more of the existing free-reading catalog, we expanded and reorganized the home’s content-discovery sections from seven to 16. We also consolidated 79 inconsistent tags into 22, then prioritized related interests and removed recently used content to give each result a relevant next step.

Recommendation touch rate rose from 30.4% to 41.5% on question pages and from 45.8% to 50.3% on result pages. Result-page recommendation EPU increased 40%, from 4.5 to 6.3. Section names also shifted from functional labels to language that described the user's expectation.

Question-page recommendation touch

30.4% → 41.5%

Result-page recommendation touch

45.8% → 50.3%

Result-page recommendation EPU

4.5 → 6.3

Recommendation frequency

+40%

We shortened the path to results by simplifying the separate action that opened detailed reading information. The share of users viewing a result increased from 47.87% to 51.97%, and the question-to-result CTA rose from 53.39% to 57.23%.

EPU remained nearly flat at 8.20 to 8.24. That result showed that reducing interaction cost could improve completion, but repeat use needed recommendation and personalization to move with it.

Users viewing a result

47.87% → 51.97%

Question-to-result CTA

53.39% → 57.23%

Free-reading EPU

8.20 → 8.24

I connected in-app content and social distribution as one story. After free readings became the primary social acquisition vehicle, four-month cumulative app downloads grew 206%, from 277 to 847.

Share EPU also rose from 1.4 to 2.0 after adding sharing to result pages. The end of one content experience became the beginning of the next acquisition loop, connecting product and marketing in the same system.

Four-month cumulative app downloads

277 → 847

Social-linked download growth

+206%

Result-sharing EPU

1.4 → 2.0

The hypothesis that more free content would steadily lift retention did not repeat across weekly cohorts. Retention moved significantly depending on which content launched, showing that supply alone could not create durable growth.

I shifted the roadmap from content volume to personalization quality. The most important operating principle from this project was to look beyond successful averages, find the conditions that repeat, and separate unsupported hypotheses from the next decision.

From content volume to personalization quality—growth comes from connecting each user to the experience they need now.