Avoid common ASO mistakes of new apps: 5 hidden traps that slow down the start

Trap 1: Blindly chasing search volume, ignoring users' real intentions

1. Build an initial pool of competitor keywords

• Keyword dimension: Using professional tools (such as UPUP analysis platform), the system captures the title and subtitle information of target competitors' applications, and extracts their high-frequency core keywords.
• Keyword pool generation: Summarize all competitor keywords, merge and deduplicate them to form a preliminary "competitor keyword pool".

2. Incorporate user perspective to expand keywords

• User demand scenario restoration: In-depth analysis of the core demand scenarios of target users, deducing the search keywords that users may use when seeking this application function to solve their problems.
• Analyze the related keywords and their popularity trends with the help of keyword expansion function of platforms such as UPUP.
• Keyword pool expansion: Incorporate the effective search terms mined from the user's perspective into the keyword pool.

3. Keyword Screening, Combination and Optimization

• Remove irrelevant keywords: Remove overly broad (e.g., "game"), non-core function, or ambiguous intent keywords.
• Focus on mid and long tail strategy words: Prioritize screening and building mid and long tail keywords with relatively low competitiveness, clear user intent, and high conversion potential.

4. Precise Layout Metadata

Trap 2: Treat screenshots as billboards, not conversion engines

• Screenshot Golden Structure + Visual Techniques:
  • Pain point layer: Use red exclamation marks and enlarged problem images to intensify anxiety.
  • Solution layer: Use dynamic arrows (such as from "Album" pointing to the "One-click classification" button), step numbers (① Select ② Crop ③ Share), split-screen comparison (left picture messy album vs right picture completed classification) to show the operation path.
  • Result Layer: Present value using data visualization (e.g., “80% time saved on organization”) or user expressions.
• Design points for the first picture:
  • Must include "core selling point + extreme result", such as the first picture of photo editing app uses "1 key to eliminate passersby" instead of "professional photo editing tools".
  • High contrast (e.g. dark background with bright text) to ensure that the core information is visible in thumbnail state.
  • Avoid logo taking up too much space, users care more about "what they can get" rather than "who provides it".
• A/B Test Key Dimensions:
  • First image variant: test the conversion difference between "pain point first" (such as "phone memory full?") and "result first" (such as "free up 10GB of space").
  • Number of screenshots: Tool class App test 3 pieces (focus on core functions) vs 4 pieces (increase one scene extension) sliding completion rate.
  • Text style: Test the attractiveness of colloquialism ("There are too many photos to save?") vs. data (1000 photos fill up the memory).

Trap 3: Treating Ratings as KPIs, not a User Insight库

• Automated Review Analysis Tool:
  • Low-cost solution: Use UPUP's "Comment Theme & Keyword" function to view high-frequency keywords (such as "lag" and "crash").
  • Advanced solution: Use NLP tools such as MonkeyLearn to upload review data and identify deep needs (such as when users say "complex interface", the actual need is "simplified operation").
• The Dual Value of Negative Ratings:
  • For potential users: Timely reply to negative reviews and explain the solution (such as explaining transfer rules) can enhance the trust of potential users, indirectly improving conversion.
  • For brand image: soft tone, closer relationship, and showing the attitude of valuing users.
• Compliance invitation strategy:
  • Trigger reviews after the user completes a core action.
  • Provide neutral options ("Not now" "Remind me later"), to avoid forced pop-ups affecting the experience.
  • Tell them clearly that "Your feedback will help us improve" instead of "Please give 5 star ratings".

Trap 4: Localizing as translation, not cultural adaptation

• Keyword Cultural Adaptation:
• Religious factors: The Middle East avoids "pig" and "alcohol", and uses "Ramadan" and "prayer" instead.
• Festival customs: Europe and the United States focus on "Black Friday" and "Christmas", while Southeast Asia focuses on "Eid al-Fitr" and "Songkran".
• Slang use: Brazil uses "pamonha" (corn cake) to refer to "simple things", rather than a literal translation
• Visual Adjustments:
• Color: China prefers red (festive), Western weddings avoid red (symbolizing blood)
• Person: Indian market uses dark-skinned models more often to avoid "whitening" related visual elements
• Symbol: Middle East avoid using pig patterns, can use local elements such as camel, date etc

Trap 5: Isolated operation of ASO, ignoring traffic synergy

• Data Interoperability Practice plan:
  • Use AppsFlyer (the free version supports basic functions) to generate exclusive tracking links for different channels (such as official website button links and Facebook promotion links). The backend can directly view the "download conversion number" brought by each channel.
  • Cross-team synchronization mechanism: A meeting is held every week. The ASO team and the paid promotion team exchange information about keywords with good performance, which can be added to metadata or included in advertising after evaluation.

• Brand word defense strategy:
  • Use the full name for all external content to avoid users jumping to competitors when searching for abbreviations.
  • Monitor the fluctuation of brand word rankings. If a "copycat App" occupies the top 3 positions, report infringement and increase brand word placement to squeeze it out.

Call to action: ASO precise diagnosis, direct hit optimization pain point