AdHive.tv
AdHive.tv
Jul 20 · 3 min read

HiveAnalytic.com — new product from Adhive team for social media audiences analysis

Adhive team released first version of Hiveanalytic.com — new service for deep analysis of audience parameters and intersections in social media. It designed for influencer marketing platforms, brands and agencies who running influencers marketing campaigns.

Problem and solution

Everyone who pays for reach influencers campaigns has to know several critical parameters about followers base: do they real, where they are located, how old are they, what are their interests, which brands do they prefer, and many others. Hive Analytic can solve it with one report contained audience description and fraud detection analysis. Hive Analytic report provides detailed data for one influencer account, including fields of interests of audience, brand affinity, quality of account. All paid reports are available in personal account any time with no need to download it.

Algorithms

Adhive team has deep competences in AI and thanks to that Hive Analytic has proven leadership in accuracy of fraud detection. Advanced AI algorithms help to determine plenty of parameters which are critical for influencers campaigns, such as: gender/age, location, real interests, do comments and likes are made by real people or bots, does audience is really matched with segment of influencer. We have compared our results with competitors in July 2019 and can guarantee the highest accuracy in fake followers detection.

How to use

We launched separate personal account for social media analysis and users of Adhive platform need to register there. In next releases of platform it will be also integrated to Adhive platform personal account for advertisers.

Infrastructure

Our own infrastructure for data collection and storage provides high productivity of service which can generate hundreds of reports simultaneously. With such productivity Hive Analytic can be used as stable data provider for any influencers marketing platform. First platform which use service as data provider became Adhive Platform itself, which going to use Hive Analytic as integrated tool for own influencer marketing campaigns, so clients of Adhive Platform can make data driven decisions choosing the influencers.

Payment plans

Hive Analytic is standalone online service available for any customer — reports could be paid by credit card, with Wire transfer or ADH tokens. Balance of the account is indicated in currency and tokens, so users can easily understand how much money or tokens they need to have there for analysis. After a registration customers get free tokens to try service, but agencies and platforms will already have in their account prepared reports of random influencers to check parameters and data formats. There is no subscription in the service yet, customers can buy internal tokens by batches and spend them any time without limitation.

Coming releases

Based on the service roadmap next releases will contain neural networks improvement for even more accurate detection of fake followers, Tiktok as next social media and mobile application for influencers with gamification where they can check accounts, share results and get ranking among their location/segment/etc.

Official links:

AdHive Platform

Twitter

Telegram

Facebook

Adhive.tv

A community powered global network for native video advertisement.The AdHive platform automates all steps of interactions between bloggers and advertisers.AI modules for video and speech recognition connect to vlog channel and control the execution of the ad task by the blogger.

AdHive.tv

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AdHive.tv

The first AI-controlled influencer marketing platform on Blockchain. Launching massive advertising campaigns has never been so simple.

Adhive.tv

Adhive.tv

A community powered global network for native video advertisement.The AdHive platform automates all steps of interactions between bloggers and advertisers.AI modules for video and speech recognition connect to vlog channel and control the execution of the ad task by the blogger.

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