TCPW Activity Insights

activity_insight.md

Activity Insights

Query window: 2026-05-13T18:56:26Z to 2026-06-12T18:56:26Z

Filter: excludes admin tiers -1 and -2.

Summary

Metric	Value
Total activities	57,878
Active users	1,285
Avg activities / active user	45.0
Median activities / active user	9
P75 activities / active user	28
P90 activities / active user	97
P95 activities / active user	183
Top 10 users activity share	24.8%
Top 50 users activity share	49.1%
Avg daily activities	1,867
Highest activity day	2026-05-14, 3,440 activities
Lowest activity day	2026-05-13, 403 activities

Engagement is highly concentrated. The average active user generated about 45 activities, but the median user generated only 9. This means a relatively small group of heavy users is pulling the average upward. The top 10 users generated about one quarter of all tracked activity, while the top 50 users generated almost half.

Top Activity Types

Rank	Activity	Count	Unique Users	Avg / User	Share
1	x_posts_view	9,041	358	25.25	15.62%
2	options_gamma_view	8,769	183	47.92	15.15%
3	home_view	8,216	914	8.99	14.20%
4	post_view	7,181	906	7.93	12.41%
5	options_flow_view	5,730	209	27.42	9.90%
6	search	3,752	246	15.25	6.48%
7	stock_view	3,429	233	14.72	5.92%
8	login	2,354	859	2.74	4.07%
9	section_view	1,709	398	4.29	2.95%
10	profile_view	1,558	636	2.45	2.69%
11	economic_insights_view	1,310	305	4.30	2.26%
12	ai_query	817	101	8.09	1.41%
13	rrg_view	745	127	5.87	1.29%
14	language_toggle	698	168	4.15	1.21%
15	economic_calendar_view	605	230	2.63	1.05%
16	earnings_calendar_view	563	157	3.59	0.97%
17	courses_view	468	197	2.38	0.81%
18	portfolio_view	263	122	2.16	0.45%
19	interest_rate_view	208	107	1.94	0.36%
20	theme_toggle	132	59	2.24	0.23%

The broad user base behaves differently from the top 10 most active users. For the top 10, activity was heavily dominated by x_posts_view, options_gamma_view, and options_flow_view. Across all users, home_view and post_view become much more important, which suggests casual and mid-engagement users still center their usage around the main content feed and article/post consumption.

options_gamma_view is the strongest power-user feature. Only 183 users used it, but they generated 8,769 events, averaging about 48 views per user. This is much stickier than broad features such as home_view, which reached 914 users but averaged only about 9 views per user.

x_posts_view is also a major retention feature. It reached 358 users and generated 9,041 views, combining meaningful reach with high repeat usage.

Activity By Tier

Tier	Activities	Share
0	12,678	21.90%
1	4,452	7.69%
2	3,682	6.36%
3	37,066	64.04%

Tier 3 users dominate activity, producing about 64% of all tracked non-admin activity. This confirms that the heaviest engagement comes from Max users. The product's most valuable usage loop appears to be premium market tools, X/news content, search, and stock detail views.

Top Countries

Rank	Country	Activities	Share
1	US	32,690	56.48%
2	VN	10,563	18.25%
3	unknown	4,182	7.23%
4	CA	3,731	6.45%
5	DE	1,799	3.11%
6	JP	668	1.15%
7	AU	629	1.09%
8	KR	622	1.07%
9	SG	525	0.91%
10	FI	488	0.84%

Activity is mostly concentrated in the US and Vietnam. Together, these two countries account for about 74.7% of all tracked activity in the period.

Product Takeaways

The app has a broad content-consumption base through home_view and post_view, but retention and depth are driven by premium analytical workflows, especially options_gamma_view, options_flow_view, and x_posts_view.

The highest-impact product opportunities are likely:

1. Improve onboarding from home_view and post_view into sticky premium surfaces such as options gamma, options flow, X/news content, search, and stock detail pages.
2. Improve speed, freshness, filtering, alerts, and cross-linking for x_posts_view, options_gamma_view, and options_flow_view.
3. Treat options_gamma_view as a key retention surface for advanced users because it has the highest repeat usage per active user among major features.
4. Use search and stock_view together as a research workflow, since both have similar user reach and strong repeat behavior.
5. Investigate why tier 1 and tier 2 activity is low relative to tier 3; there may be an upgrade, activation, or feature-discovery gap between mid-tier and Max users.

Main takeaway: casual users consume the feed and posts, while the most engaged users repeatedly use premium market intelligence tools. The best growth path is to move more casual content consumers into those high-retention analytical workflows.

Time-Based Activity Patterns

Additional query window: 2026-05-13T19:02:03Z to 2026-06-12T19:02:03Z

Total activities counted in this query: 57,875.

Peak Hours

New York local time is the most useful lens for market behavior. Singapore/Vietnam evening hours are also useful because many Vietnam-based users appear to follow the US market session live.

Rank	NY Hour	SG/VN Hour	Activities	Share
1	10:00	22:00	5,891	10.18%
2	09:00	21:00	5,726	9.89%
3	11:00	23:00	4,723	8.16%
4	12:00	00:00	3,706	6.40%
5	13:00	01:00	3,497	6.04%
6	14:00	02:00	3,322	5.74%
7	15:00	03:00	2,600	4.49%
8	22:00	10:00	2,266	3.92%

Activity peaks sharply during the US market open. NY 09:00 to 11:00 accounts for about 28.2% of all activity. NY 09:00 to 15:00, roughly the main live trading window, accounts for about 50.9% of all activity.

For Singapore and Vietnam users, the strongest window is 21:00 to 23:00, which maps directly to the US market open. This is an important retention signal: users are already building a live-market habit around the product.

Day Of Week

Day, NY Time	Activities	Share
Sunday	5,491	9.49%
Monday	7,921	13.69%
Tuesday	8,283	14.31%
Wednesday	9,182	15.87%
Thursday	11,880	20.53%
Friday	10,919	18.87%
Saturday	4,199	7.26%

Thursday and Friday are the strongest activity days, with 39.4% of all activity. Weekend usage drops meaningfully, especially Saturday. Sunday still has more activity than Saturday, likely from users preparing for the trading week or reading market content before Monday.

Top NY day/hour slots:

Rank	Slot	Activities
1	Friday 09:00	1,422
2	Thursday 10:00	1,391
3	Thursday 09:00	1,290
4	Friday 10:00	1,223
5	Tuesday 10:00	1,079
6	Friday 11:00	1,065
7	Thursday 11:00	1,042
8	Tuesday 09:00	957
9	Wednesday 09:00	944
10	Wednesday 10:00	865

The best engagement windows are concentrated around the US market open, especially Thursday and Friday.

Feature Timing

Activity	Peak NY Hours	Pattern
options_gamma_view	09:00, 10:00, 11:00	Highly market-open driven. Almost 38% of gamma views happen at 09:00-10:00 NY.
options_flow_view	10:00, 09:00, 11:00	Also market-open driven, with strong use through midday.
x_posts_view	10:00, 11:00, 13:00	Used during market hours, but less narrowly tied to the open than options tools.
home_view	09:00, 10:00, 11:00, 21:00, 22:00	Has both market-open and evening/morning catch-up behavior.
post_view	22:00, 21:00, 23:00, 10:00, 14:00	More asynchronous. Users read posts outside the live trading window.
search / stock_view	09:00, 10:00, 11:00	Research behavior clusters around the market open.
ai_query	10:00, 15:00, 11:00, 12:00, 14:00	AI usage happens through the live market day, not only at the open.

The key split is live tools versus asynchronous content. Options gamma, options flow, search, and stock views are market-session tools. Posts are more flexible and can support off-hours retention.

Retention Recommendations

1. Build Around The Market-Open Habit

The clearest retention pattern is the NY 09:00 to 11:00 activity spike. Users are already coming back when the US market opens, especially for options gamma, options flow, search, and stock views.

Actions:

1. Add a market-open dashboard state from NY 09:00 to 11:00 that prioritizes options_gamma_view, options_flow_view, top tickers, unusual flow, and relevant X/news posts.
2. Add a pre-open digest 15-30 minutes before market open with key tickers, overnight news, earnings, macro events, and yesterday's high-interest tickers.
3. Add contextual prompts from home_view during market open: "View gamma levels", "Check options flow", "Search ticker", or "Open today's X feed".
4. Make the first screen during market hours more operational and less general, because heavy users are clearly task-oriented during this window.

2. Convert Feed Readers Into Tool Users

home_view and post_view have broad reach: over 900 unique users each. But repeat depth is much higher in premium tools like options_gamma_view and options_flow_view.

Actions:

1. Add inline links from posts to the related stock page, options gamma, options flow, and X/news feed.
2. For posts mentioning tickers, show a compact ticker action row: stock detail, options flow, gamma, AI summary, add to portfolio.
3. Use post_view as an acquisition surface for advanced workflows, especially outside market hours when users are reading asynchronously.
4. Create a "continue research" module after reading a post: recently mentioned tickers, related X posts, related options flow, and recent searches.

3. Treat Options Gamma As A Core Retention Surface

options_gamma_view has the strongest repeat behavior among major features: 183 users generated 8,769 views, or about 48 views per user. This is a clear sign of deep product-market fit with advanced users.

Actions:

1. Improve gamma load time, chart readability, and ticker switching first. Small improvements here likely affect the most retained users.
2. Add saved tickers or watchlist shortcuts directly inside the gamma experience.
3. Add alerts around key gamma levels, large changes, and market-open shifts.
4. Add "what changed since last visit" summaries for gamma so repeat users immediately see why to come back.
5. Cross-link gamma to options flow for the same ticker and timestamp, because the highest-value users often use both.

4. Make Options Flow A Live Monitoring Product

options_flow_view is lower reach than home_view and post_view, but much higher intent. It peaks during market hours and is a likely premium retention driver.

Actions:

1. Add stronger filters: unusual premium, sweep/block, expiration, ticker watchlist, sector, bullish/bearish.
2. Add a "live now" state during NY market hours with clear freshness indicators.
3. Add user-personalized default filters based on prior activity.
4. Add one-click navigation from flow item to stock page, gamma page, X posts, and AI explanation.
5. Consider a daily "top flow recap" for users who missed the live session.

5. Use Time-Aware Notifications Carefully

Since activity is heavily time-bound, notifications should respect user timezone and market context.

Actions:

1. For US users, test pre-open notifications around NY 08:45 and market-open notifications around NY 09:30.
2. For Vietnam/Singapore users, test evening notifications around 20:45 to 21:15, before the US market open.
3. Send fewer, higher-value notifications: unusual options flow, major gamma shift, breaking X/news posts for watched tickers, and end-of-day recaps.
4. Avoid broad generic notifications. The activity data suggests users return for specific market intelligence, not generic reminders.

6. Create Off-Hours Retention Loops

Weekend and off-hours usage is weaker, but post_view has more off-hours behavior than options tools. This makes content the better off-hours retention layer.

Actions:

1. Publish or surface weekly recap content on Sunday, when users are more active than Saturday.
2. Add "week ahead" content with earnings, macro events, key tickers, and major technical/flow setups.
3. Add saved reading lists or "missed since last login" summaries for users who do not log in during market hours.
4. Use off-hours posts to route users into watchlists, alerts, and Monday market-open workflows.

7. Improve Tier 1 And Tier 2 Activation

Tier 3 users generate 64% of activity. Tier 1 and tier 2 users are much less active, which may mean the product's strongest retention loops are either locked behind tier 3, under-discovered, or not clearly valuable enough in lower tiers.

Actions:

1. Query activation by tier: percentage of users who used options gamma, options flow, search, stock view, and X posts within 7 days of subscription.
2. Add upgrade nudges based on behavior, not generic paywalls. For example, if a user repeatedly searches tickers, show the value of gamma/flow for that ticker.
3. Give lower-tier users limited but meaningful previews of high-retention features.
4. Build a tier-specific onboarding path: free users to content/search, tier 1 to market posts, tier 2 to research tools, tier 3 to live options intelligence.

8. Measure Retention More Directly Next

The current data shows activity depth, feature usage, and timing, but not true retention cohorts. The next queries should measure whether users return after first using specific features.

Recommended next analyses:

1. D1, D7, D14, and D30 return rate by first major activity type.
2. Retention by feature adoption: users who used options_gamma_view versus users who only used home_view or post_view.
3. Time-to-second-session by tier.
4. Conversion path from home_view or post_view into search, stock_view, options_gamma_view, or options_flow_view.
5. Churn-risk users: paid users with no activity in the last 7 or 14 days.
6. Power-user journey: first 20 events for users who eventually reach more than 100 activities in 30 days.

Main retention thesis: use content to acquire and reactivate users, but use live market tools to retain them. The strongest retention opportunity is to make the US market open feel like a daily must-check workflow, then use off-hours posts and recaps to bring users back into the next live session.