Today Tab

Today Tab Definition

• Platform-level authoritative endorsement, recommended content with extremely high credibility.
• Immersive exposure in user-initiated browsing scenarios
• Supports deep linking directly to the application details page or specific event page.
• Diversified content presentation formats (storytelling with images and text, videos, interactive cards)

Core usage scenarios

New product application/game launch promotion

• Gain prime exposure through the Today Tab and solve the cold start traffic problem.
• Enhance users' understanding of the product's core features by aligning with editor-recommended stories.
• Case: The casual game "Dream Garden" saw a 300% increase in downloads during the first week after being recommended through the Today Tab story.

Brand event marketing

• Display brand-customized content (such as holiday events, IP collaborations)
• Achieve a closed loop of traffic both inside and outside the app by combining in-app activities.
• Case: An e-commerce app increased its activity page traffic by 85% during Double 11 through Today Tab story redirection.

Recall of existing users

• Recommend significant version updates or new feature modules for applications.
• Wake up dormant users who haven't opened the app for 30-90 days.
• Data shows: high-quality recommended stories can increase the revisit rate of old users by 22%-40%.

Precise reach in vertical scenarios

• In conjunction with the platform's editorial planning of special events (such as "Home Fitness Selections")
• Obtain highly matched and precise target users.
• Industry data: Health-related applications reduce customer acquisition costs by 65% through thematic recommendations.

Key Performance Indicators

Exposure layer indicators

• Daily Impressions: Measures the base of users reached by content.
• Story completion rate: Reflects content appeal, typically needs to be >60%.
• Recommended position click-through rate (CTR): Industry benchmark value 1.5%-3.5%

Conversion layer metrics

• Detail page arrival rate: reflects the match between recommended content and the landing page.
• Download Conversion Rate (CVR): Affected by multiple factors such as app icon, ratings, etc.
• Retention rate and 7-day retention: Core metrics for evaluating user quality.

Business value metrics

• Cost per thousand impressions (CPM): An important reference for bidding on recommended positions.
• Customer acquisition cost (CPI): Typically 30%-50% lower than conventional advertising.
• User LTV Improvement Ratio: Measures the long-term value of recommended users.

Advertiser Core Value

• Trust Premium: The brand value-added effect brought by the platform's editorial screening mechanism
• Scenario advantage: Users are in an active exploration state, with a stronger willingness to convert.
• Long-tail effect: High-quality recommended content can bring a traffic bonus that lasts for 2-4 weeks.
• Data collaboration: forming a combined strategy with search advertising and programmatic placement.

Optimization Practice Recommendations

Material production guidelines

• Use high-definition visual materials with a 16:9 aspect ratio (minimum size 1200×628 pixels).
• The main image must convey the core message within 0.5 seconds.
• The story copy should be limited to 3-5 screens and include a clear call to action.

Data optimization strategy

• A/B test different content combinations (video vs animated GIF).
• Monitor differences in user behavior at different times.
• Establish a correlation model between recommendation effectiveness and organic search volume.

Ecological collaborative gameplay

• Establish a deep interaction mechanism with in-app activities.
• Linking social platforms for secondary dissemination
• Collaborate with internet celebrities/KOLs to create complementary content.

Industry Trend Insights

• Test displaying differentiated content based on user profiles.
• Add a real-time data display module (such as the current number of active users).
• Explore new interaction methods such as AR preview.
• The hybrid model of algorithmic recommendation and manual editing is gradually becoming popular.