InferSystems Revolutionizes Real Time Bidding (RTB) OptimizationInfersystems is Proud to Announce the Release of the Infer RTB Optimizer, a Proprietary Predictive Analytics Engine, Providing Data Driven Ad Serving Platforms with the Ability to Automatically Optimize Performance (CPA/CPC) Campaigns to Maximize Profit


Toronto, ON (PRWEB) November 09, 2011

Infersystems Corporation, a leading provider of RTB Optimization Technology is excited to announce the release of their latest (patent pending) product, the Infer RTB Optimizer.

 

The Infer RTB Optimizer is a proprietary embedded software application that enables media buying/selling platforms to build accurate data models from Internet response data (large categorical databases) in less than 10% of the time of any of todays modeling tools and/or methods. The RTB Optimizer is not a platform nor is it an algorithm. It is a predictive analysis engine that can quickly generate a set of media buying rules from any internet response data that will perform faster and more accurately than any algorithm(s) or data model(s) generated by todays leading machine learning methods.

 

The Infer RTB Optimizer, based on applied non-parametric statistics, is able to digest Big Internet Data containing hundreds of variables and automatically generate thousands of multivariate media buying rules. Alternate machine learning approaches try to fit data to a curve represented by one single equation or algorithm, whereas the RTB Optimizer combines multiple optimization models (buying rules) based on different variables to capture all pockets of performance.

 

The winning bidders in RTB will be those that can most accurately predict the response rate for an incoming impression. However, the likelihood of anyone clicking (let alone buying) on an impression is almost 0 Therefore, any optimization solution must be very effective in its treatment of rare events. Infersystems underlying science is uniquely suited to estimating response rates for super rare events. The recommended bid prices generated by the RTB Optimizer correlate directly with actual response rates the next day – The Optimizer bids more for impressions that do convert more profitably.

 

Infersystems takes advantage of the ability RTB offers to truly optimize your marketing expenditure by bidding on each advertising impression according to its true value; a value that is different for every product advertised to every consumer.

 

We are very excited to release this version of the RTB Optimizer. True, automatic, data driven optimization will enable DSPs and SSPs to leverage their RTB infrastructure and data investment to build a very profitable performance business. Whether you buy or sell media, the Infer RTB Optimizer will maximize the profit from your performance marketing initiatives. If your platform is buying media, the RTB Optimizer will drop your eCPC/eCPA thereby improving the ROI on your media spend dramatically. If your platform is selling display media, Infersystems automatic data driven campaign optimization will enable you to increase eCPM by effectively arbitraging performance campaigns across unfilled inventory. said Ben Mair, President & Co-Founder, Infersystems.

 

Infersystems Corporation, a Toronto based company founded in 2009, has developed patent pending technology, based on non-parametric statistics, that enables digital media platforms to offer automatic data driven Real-Time Bidding (RTB) Optimization. Platform providers can license the Infer Optimizer to leverage their investment in infrastructure and data to increase eCPM for their publishers and/or reduce the eCPA for their advertisers.

 

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About The Author

Ibrar Ayyub

I am an experienced technical writer holding a Master's degree in computer science from BZU Multan, Pakistan University. With a background spanning various industries, particularly in home automation and engineering, I have honed my skills in crafting clear and concise content. Proficient in leveraging infographics and diagrams, I strive to simplify complex concepts for readers. My strength lies in thorough research and presenting information in a structured and logical format.

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