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Mashup of telecom data and external data

Telecom data vs External data

Mashup Of Telecom Data And External Data
  • Digital advertising real-time bidding data
  • Tracking Code
  • Customer Relationship Management/CRM

1. Digital advertising real-time bidding data

Mashup Of Telecom Data And External Data

When Realtime Bidding (RTB) data is combined with telecom data, it becomes one of the most powerful tools to be utilized by advertisers.

RTB data carries an advertisement object identification code that when strung together with the corresponding mobile phone number, we can know which phone number a certain RTB advertising request is related to.

In order to assist AI advertising in providing more relevant advertisements to users, RTB data usually carries the current contextual data of the user, such as the URL being browsed. By capturing and analyzing URL content and supplementing telecommunications data, we can know which domain the mobile phone user has visited.

Because we can match the advertising object identification code in the RTB data with the phone number, we can retrieve the interests and preferences of the advertising object inferred from the telecommunications data as a reference for RTB advertising decision-making.

2. Tracking Code

What is a tracking code? It is the code that website owners/App developers embed in their own services to track and record user behavior. The most well-known example is Google Analytics (GA).

The tracking code mentioned in this article is very similar to GA in terms of concept and function,

Mashup Of Telecom Data And External Data

but an additional mechanism will be added to match the identification code assigned to the user in the tracking code with the telecommunications data. In this way, the usage behavior records of a specific user on the website or app can be mixed and matched with telecommunications data to build a deeper understanding of the user, such as what types of products they often browse or even buy. Website owners/app developers can know what kind of similar group attributes, interests, and hobbies this group of customers may have, and even which websites or apps they often use through the mashup data and analysis results.

3. Customer Relationship Management/CRM

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Consumers’ mobile phone numbers are usually included in the CRM information of consumer product brands or channels. According to the conditions of the customer group they want to analyze, for example, consumers who have spent more than M amount in the past N months,

brands or channels can retrieve qualified consumer information and their mobile phone numbers from their CRM system. After being processed by the hash calculation tool we provide, we can mix and match the processed mobile phone numbers with the telecom data of the mobile telecom operators we cooperate with. Enrich telecom operators’ understanding of this group of mobile phone users, and at the same time allow brands or channels to understand which other brands/channels of this group of consumers cannot know from their own channels through the labels analyzed by the telecom data on this group of consumers interests and hobbies.