Indispensable for Entering the Vietnamese Market: Practical Applications and Case Analysis of Zalo Number Filtering in Cross-Border Commerce

In the wave of Vietnam's digital economy, Zalo, with its over 70 million users and localized advantages, has become a private domain operations platform that cannot be ignored for businesses entering this market. However, many cross-border companies often face core pain points in their Zalo operations: how to accurately target potential customers from a massive user base? How to avoid resource waste caused by invalid numbers? At this point, Zalo number filtering becomes the key to breaking through these challenges. Through scientific Zalo number filtering methods, enterprises can efficiently identify potential customers and optimize marketing strategies. By leveraging professional tools like ITG Omni-Filter, this process can be systematized and automated. This article will delve into the practical application of Zalo number filtering in cross-border business and analyze its value through real case studies, helping companies gain a competitive edge in the fiercely contested Vietnamese market.

I. Why is Zalo Number Filtering the First Step in Entering the Vietnamese Market?

Vietnam's mobile internet penetration rate exceeds 70%, but user behavior is fragmented with a preference for localized communication. As a national-level application, Zalo covers multiple scenarios from personal social networking to business services. However, blindly adding users or purchasing number lists can lead to the following problems:

1. High Cost, Low Conversion: Invalid numbers can account for 30%-50%, wasting manpower and marketing budget.

2. Account Ban Risk: Frequently adding invalid users can easily trigger platform risk control, leading to the banning of business accounts.

3. Inefficient Resource Allocation: Lack of precise classification traps operational teams in inefficient communication.

Through Zalo number filtering, companies can pre-filter invalid data and focus on high-value groups. For example, a maternal and infant brand used the ITG Omni-Filter tool to conduct an initial cleansing of 100,000 numbers, removing duplicates, virtual numbers, and non-target regional users, ultimately reducing the valid number list to 65,000. This resulted in a 40% reduction in marketing costs and a 25% increase in conversion rates.

II. Core Dimensions of Zalo Number Filtering & Practical Application of ITG Omni-Filter

Zalo number filtering needs to be based on multi-dimensional data to ensure number quality aligns with business objectives. Here are the core filtering dimensions and how tools can achieve them:

1. Basic Validity Verification

• Number Status Check: Identify disconnected, invalid, or numbers not registered with Zalo through the ITG Omni-Filter carrier interface.

• Activity Analysis: Filter users who have recently logged into Zalo or posted updates, avoiding "inactive accounts."

• Geographical Matching: Filter numbers based on location (e.g., Ho Chi Minh City, Hanoi) to ensure target consistency.

2. User Attribute Filtering

• Age & Gender: Tag user attributes based on public data (like social profiles) to match product positioning. For instance, a cosmetics brand can filter female users aged 20-35.

• Interest Tags: Capture potential audience segments based on keywords in Zalo communities (e.g., "maternal and child," "cross-border e-commerce").

• Spending Capacity: Classify user value tiers based on Zalo Pay usage history or associated e-commerce behaviors.

3. Compliance and Risk Control

• Blacklist Filtering: Exclude numbers that have been reported or are suspected of fraud to reduce operational risks.

• Data Source Audit: Ensure number sources comply with Vietnam's Personal Data Protection Decree to avoid legal disputes.

Case Study:
A cross-border e-commerce company used the ITG Omni-Filter tool to perform layered filtering on 50,000 numbers:

• First Layer: Basic verification removed 12,000 invalid numbers.

• Second Layer: Filtering by region and interest tags (e.g., "overseas shopping," "Korean/Japanese cosmetics") identified 23,000 target users.

• Third Layer: Combined with spending capacity tags, finally locked in 8,000 high-potential users.
  Result: The marketing conversion rate in the first month was 3 times higher compared to the non-filtered group, and the average order value increased by 20%.
  
  

III. Application Scenarios of Zalo Number Filtering in the Cross-Business Workflow

1. Market Research & User Profile Building

By analyzing the geographical distribution, age structure, and interest preferences of users through Zalo number filtering, companies can quickly sketch a profile of the target market. For example, a home furnishings brand discovered that 30% of filtered users were concentrated among Hanoi's working class, prompting them to adjust their product line to focus on practical, cost-effective furniture.

2. Precision Marketing & Advertising

Import the filtered number lists into the Zalo advertising system for customized reach:

• Promotional Activities: Push discount codes to users with high spending potential.

• New Product Testing: Invite users with matching interests to participate in experience programs and collect feedback.
  A fitness equipment company used ITG Omni-Filter to target active users in fitness communities; the participation rate for their new product crowdfunding campaign was twice that of traditional channels.

3. Customer Service & Relationship Management

• Priority Service Channels: Assign dedicated customer service to high-value users.

• Repurchase Incentives: Filter inactive users based on purchase history and send reactivation offers.
  Case: A skincare brand filtered users with repurchase intent and launched exclusive member sets, increasing the repurchase rate by 35%.
  
  

IV. Compliance Challenges and Countermeasures

As Vietnam's data privacy regulations become increasingly strict, companies must focus on the following compliance points in Zalo number filtering:

1. Clear Data Sources: Use only numbers obtained through user authorization or public channels, avoiding purchasing grey-market lists.

2. Principle of Minimal Necessity: During filtering, collect only fields essential for the business (e.g., region, interests), and prohibit sensitive information.

3. Localized Compliance Tools: Adopt modules like the Vietnam compliance feature in ITG Omni-Filter to automatically filter out illegal data.
   
   

V. Future Outlook: From Filtering to Intelligent Operations

With the deepening application of AI technology in data mining, Zalo number filtering will evolve beyond initial filtering to integrate with user lifecycle management:

1. Dynamic Update Mechanism: Use ITG Omni-Filter to monitor changes in user behavior in real-time (e.g., shifting interests, declining activity) and dynamically adjust tags.

2. Predictive Modeling: Predict user purchase probability based on historical data to guide resource allocation.

3. Omni-channel Integration: Integrate Zalo data with platforms like Facebook and TikTok to build a unified customer view.
   
   

Conclusion

In the exploration of the Vietnamese market, Zalo number filtering has transitioned from an "option" to a "necessity." It is not just a tool for improving marketing efficiency but also a core component of a company's localization strategy. By utilizing professional tools like ITG Omni-Filter, enterprises can systematically address issues of number quality, user targeting, and compliance risks, building a foundation of trust while winning market share. In the future, deeply cultivating data value and optimizing filtering precision will be key for cross-border enterprises to break through in the competitive landscape.