Multi channel message push

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High traffic cost

Under the background of the disappearance of traffic dividend, the traffic cost is getting higher and higher, and enterprises want to obtain higher ROI

Ambiguous user profile

Inaccurate customer circle selection of advertising target group leads to unstable advertising effect, high cost and low conversion into operational normality, and advertising effect cannot be monitored in real time

It is difficult to accurately launch advertisements

Inaccurate customer circle selection of advertising target group leads to unstable advertising effect, high cost and low conversion into operational normality, and advertising effect cannot be monitored in real time

Lack of data for crowd modeling

The modeling work cannot be carried out due to the lack of crowd tag data or insufficient comprehensive and three-dimensional portrait data

What functions can the Aurora tag service achieve?

    Through the multi-dimensional, accurate and reliable data of Evoque, help enterprises build and improve user profiles, develop personalized operation strategies, build recommendation systems, search engines, and advertising systems, improve service accuracy, and assist business decision-making and growth
    Insight into users
    The rich user profile data and the ability of backtracking/real-time scene recognition can help enterprises understand users in an all-round and three-dimensional way, provide in-depth insight into their own users' online and offline behaviors, and build a comprehensive, accurate and multi-dimensional user profile system
    Refined operation
    Through customer portrait screening, help enterprises accurately target customers. In combination with the light push service of Aurora Alliance, we can customize the advertising content, achieve accurate advertising by thousands of people and faces, improve the efficiency of advertising, and achieve accurate customer expansion. Real time monitoring data and viewing advertising effect
    Precision marketing
    Develop models and strategies based on specific products or populations, provide customized solutions and personalized risk control services, adapt to different business scenarios, and further explore the value of data
    Joint modeling

    Why choose Aurora iAudience?

    Extensive coverage

    46.7 billion SDKs have been installed in more than 1.7 million domestic APPs. 9 years of data accumulation, covering more than 90% of domestic mobile users

    Accurate data

    Stable self owned data and multi-source external data are cross verified and supplemented to ensure accurate and stable trend of data indicators

    Fast data update

    Automatic data analysis platform to ensure daily data update and rapid interface response

    Rich tags

    8 tag categories, 2000+tags in total. It includes basic attributes, social attributes, equipment attributes, consumption value, geographical location, online and offline behavior, preference types, etc., and comprehensively depicts user interest characteristics

    Various ways of cooperation

    In addition to the standardized data interface, Evoque also provides customized factor development, on-site modeling and other services to meet the personalized needs of customers

    Application scenarios

    Aurora iAudience relies on its massive mobile terminal data to analyze users' online and offline behavior, build a multidimensional, accurate and timely holographic system, and provide services to the whole industry in the form of open interfaces.

    Holographic image system Online behavior Offline behavior

    • Demographic attribute

      Describe the basic situation of user objectivity, such as gender, age, marriage, children, etc

    • Equipment analysis

      Basic parameters of the user's network terminal, including but not limited to type, brand, price, operator, size and other attributes

    • General behavior

      It covers most of the basic information and preferences of users, such as whether there is a car, income level, consumption level and preferences, and dozens of other dimensions

    • Subdivision behavior

      Describe users' online behavior from hundreds of dimensions, covering users' finance, tourism, games, life, social interaction, etc

    • Offline visit insight

      Gain insight into the user's visit preference (visit time, visit frequency, etc.) for relevant Poi in automobile, education and training, real estate, tourism and other industries

    • Offline brand preference

      Insight into users' offline brand preferences, such as catering brands, 4S store brand preferences, etc

    • Travel preference

      Insight into users' travel preferences, such as working living distance, travel habits, etc

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