2023: Unveiling the Traffic Distribution Strategy of Xiaohongshu

Unlocking Xiaohongshu's Traffic Distribution Logic

1. Precision Exposure through Traffic Recommendation Mechanism

To stand out on Xiaohongshu and create remarkable notes, understanding its inherent recommendation mechanism and traffic distribution pattern is crucial. Mastering Xiaohongshu's traffic dynamics is the key to success.

- Pinpointed Exposure:Xiaohongshu's centralized recommendation model.

- First Wave of Traffic Recommendation: After publishing a note, the platform extracts high-frequency words from your tags. It initiates the first wave of traffic recommendation by associating these words with relevant keywords and topics that might captivate potential users.

- Content Alignment: The direction of your account's content matters. Platform algorithms evaluate note quality based on user interactions (likes, saves, comments, shares). If your note resonates with the target audience, it progresses.

- Reaching the Recommendation Threshold: Meeting the criteria for the first wave expands your note's exposure to a larger traffic pool, providing more opportunities for visibility.

- 1. Connecting great content with the right audience.

- 2. Clearly defining your account's focus.

- 3. Utilizing precise note keywords and topics.

2. Riding the Second Wave of Viral Traffic

This pattern continues until engagement with your notes stabilizes. The better your notes and their positive interactions, the higher the chance of achieving viral success.

- Niche Account, Targeted Recommendations: Specialized content results in more accurate system recommendations.

- Dominance of Quality Content: In Xiaohongshu's traffic recommendation logic, quality content prevails. Success breeds success, and exceptional content stands out. Quality is the core of virality.

3. The Power of Inclusion

Once your notes are included on Xiaohongshu's platform, they become eligible for recommendations and searches. Daily, millions of users search for notes that align with their needs, seeking relevant and useful information. These users display intent and precise preferences.

- Long-Term Traffic: High-quality notes consistently receive platform recommendations and exposure over time.

Xiaohongshu's 4 Core Aspects of Notes - Traffic Sources

1. Discovery Entry: Automated Information Flow

Driven by user interactions with content, this platform proactively recommends high-quality content based on commonalities in user likes, saved content, and followed tags. Note recommendations rely on aligning user preferences with note keywords.

Key Points:

- Accurate Tags + Niche Content

- Specific User-Generated Information Flow

2. Search Entry: Customized Information Flow

Users mainly find note content through direct searches. Incorporating relevant keywords is crucial, increasing note relevance and recommendation probability.

3. Following Entry: Following-Based Information Flow

Content from bloggers users actively follow is recommended, making this entry significant for increasing traffic. This content flows in an ever-scrolling manner.

Key Points:

- High-frequency Words + Tags + Keywords

4. Location Entry: Location-Based Information Flow

City-specific recommendations provide comparatively less traffic but are valuable. Incorporating location information in tags enhances recommendations to local users.

Especially Suitable for Location-Based Offline Business Promotion

Three Key Traffic Recommendation Logics on Xiaohongshu Notes

1. Personalized Recommendation Logic

This logic involves initial traffic boost upon publishing and approval. The initial pool's assessment score determines note advancement to larger pools, resulting in greater exposure.

2. Social Viral Recommendation Logic

- Likes and Saves: Likes from bloggers lead to exposure, especially if the blogger has a substantial following in the same field.

- Crossing 10,000 Saves: Recognition and recommendation increase for notes with over 10,000 saves.

- Share Count: High share counts lead to more recommendations.

3. Search Keyword Recommendation Logic

This logic encompasses four strategies:

(1) Industry Domain Keywords: Competitive, not recommended for beginners.

(2) Subdomain Keywords: Focusing on specific niches within industries.

(3) Product Marketing Keywords: Using competitor-related keywords.

(4) Marketing Demand Keywords: Reflecting user search habits.