With hundreds of millions of users worldwide, Viber data may include inactive, duplicate, or invalid accounts. This guide explains how to filter Viber users efficiently, helping businesses acquire real users and boost conversion rates.
Viber User Activity Analysis
Viber has hundreds of millions of registered users worldwide, especially active in Europe and Southeast Asia. For businesses, accurately reaching active users is key to improving marketing conversion rates.
Unfiltered user data may contain long-term inactive, duplicate, or invalid accounts, which directly impact advertising and marketing performance. Establishing a scientific user filtering system is therefore essential.
Common Issues in Viber User Data
The complexity of Viber user data mainly lies in several aspects: some accounts are long inactive, duplicates are common, and different channels have varying data formats and standards. These factors increase data processing and precision marketing challenges.
Without effective filtering, businesses may waste significant marketing resources on low-value users, reducing overall operational efficiency.
Data Collection and Integration Strategies
High-quality data begins with structured collection. Businesses can obtain Viber user data through ad campaigns, partner channels, or user registration.
During collection, record the source and completeness of data to ensure accuracy in subsequent filtering and analysis.
Multi-Channel Data Integration
Integrating data from multiple channels helps build a complete user profile. Combining active users, ad-acquired users, and organically grown users provides a comprehensive dataset.
Integration improves data usability and supports more efficient precision filtering.
Deduplication and Standardization
During integration, deduplication and standardization are necessary to ensure data quality and support automated analysis and efficient operations.
Standardized data better supports analytics systems and marketing automation tools, enhancing overall efficiency.
Active User Identification and Filtering
Active users are critical to conversion. By analyzing login frequency, message interaction, and behavior patterns, businesses can determine user activity levels.
Filtering active users helps improve ad click-through rates and marketing conversions.
Activity Scoring Model
Businesses can establish an activity score model based on login frequency, interaction rates, and engagement levels.
Combined activity scores quickly identify high-value users for precision marketing.
Eliminating Low-Value Users
Long-term inactive or abnormal accounts should be removed to avoid wasting marketing resources and ensure data reliability.
Removing low-value users improves data quality and lays a solid foundation for precision marketing.
User Profiling and Segmentation
After filtering active users, businesses should build user profiles based on interests, behaviors, and interaction patterns for in-depth analysis.
User profiling supports segmentation and differentiated marketing strategies, increasing engagement and conversion rates.
Segmentation Strategy
Segment users into high, medium, and low activity groups to apply differentiated strategies for each group.
Segmentation optimizes resource allocation and maximizes marketing conversion.
Marketing Path Design and Private Domain Management
After identifying high-value users, design clear conversion paths using content marketing, promotions, and one-on-one engagement to gradually improve conversions.
Private domain management retains users, builds trust, and encourages repeat engagement and purchases.
Continuously optimizing marketing processes ensures long-term growth and ROI improvement.
Case Study: Viber Filtering Boosts Conversions
An online education company initially had a 1.8% conversion rate using unfiltered Viber data. After applying active user filtering and data cleaning, conversion rose to 5%, while marketing costs decreased by ~30%, demonstrating the importance of precise data filtering.
Conclusion and Platform Recommendation
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