Is your Viber account having too many unpopular numbers? Use a filtering system to efficiently remove unpopular numbers.

Why does Viber have such a high percentage of unpopular numbers?

• The account list came from various sources, including advertising leads and offline lists, which contained a large number of Viber accounts that had not been used for a long time. These accounts were imported directly without prior screening.
• Ignoring registration status checks, numbers not registered with Viber are included in the list, directly increasing the proportion of unregistered numbers.
• The system fails to identify "cold account" signals, and accounts that have been registered but not logged in for a long time and have blank profile pictures are not removed in a timely manner, which leads to an increase in their proportion over time.
• The list was not updated regularly, some active accounts gradually became inactive numbers but were not cleaned up, and the impact of inactive numbers in the risk control range of SMS verification platforms was ignored.
  
  

What negative impacts will Viber's high proportion of unpopular numbers have?

• Wasting time and manpower, following up on unresponsive numbers, dragging down overall work efficiency, and doing useless work.
• Diluting the quality of the customer pool increases the difficulty of screening and follow-up, buries out accurate customers, and affects customer acquisition and conversion.
• Sending messages to inactive or abnormal accounts increases the risk of your main account being blocked, as it may trigger the platform's risk control measures.
• Increasing operating costs and misleading decision-making, cold numbers occupy resources without generating revenue, and can also lead to data distortion and strategy deviations.
  
  

What are some common misconceptions about identifying unregistered Viber numbers?

• Equating "no response" with "cold account" leads to misjudging busy, active accounts and missing out on potential customers.
• Only login status is considered, ignoring account interaction. Some accounts that are logged in but have no interaction are still considered inactive accounts.
• Manually identifying each account is inefficient, prone to misjudgment, and cannot meet the needs of filtering a large number of Viber accounts.
• The screening process was not reviewed, the dynamic changes of cold numbers were ignored, the screening process was halted after one round, and newly added cold numbers were not cleared in a timely manner.
  
  

How can I use ITG to filter across the entire domain and accurately remove unpopular Viber numbers?

• ITG's core 5-step number screening process:
  ① Batch upload CSV and TXT format phone number lists (sources may include advertising leads and historical customer pools);
  ② Check registration status and remove unregistered numbers;
  ③ Identify profile pictures and cold number signals, and label abnormal accounts as "low-activity/cold numbers";
  ④ Identify risk control number segments and exclude SMS verification code platforms and virtual operator number segments;
  ⑤ Output tagged data and process it in layers according to "recommended use/use with caution/exclude," directly removing cold numbers.
• Batch number screening auxiliary steps: First, preprocess the list to remove accounts with incorrect format or blank information to reduce workload; after screening, manually check and verify to reduce the probability of misjudgment.
• Subsequent maintenance: Re-screen accounts every 1-2 weeks to remove newly added cold accounts; optimize account sources to reduce the proportion of cold accounts from the source; strengthen the follow-up of active accounts to prevent them from becoming cold accounts.
  
  

Conclusion