Maximize your ROI with Programmatic Media Buying Platforms

Our proprietary real-time bidding (RTB) technology is the smartest in the industry. We evaluate a range of variables to bid on the highest-quality inventory at the most competitive time and price. Our algorithms are constantly optimizing to market conditions to ensure your campaigns are always getting the most for your spend.

Precision Real-Time Bidding

Our platform updates bid price according to market demand and optimizes for clicks and conversion rates based on historical data. We regularly update our data set and add new data points to our custom-built bidder and machine learning models to optimize bids, discover inventory and deliver the industry’s lowest acquisition costs so your ad spend gets more effective and efficient with each new data insight we collect.

Maximum ROI

Axismobi is integrated with all major ad networks and real-time bidding exchanges. Using precision targeting, we bid on individual ad impressions to ensure your spend only goes toward the mobile users with the highest likelihood of engaging. Our machine learning technology uses unique algorithms that update bid price according to market demand to ensure the highest possibility of a winning bid.

Technology Powered by Human Insight

Axismobis dedicated team of media buyers, campaign managers and data scientists collaborate closely to refine the development of our machine learning algorithms. Their shared findings on campaign performance, client feedback, inventory discovery, competitive landscape and predictive modeling are used to continually enhance our machine learning solutions. Our partnerships with unique sources gives us access to premium mobile performance inventory.

Data Intelligence

Our platform incorporates trillions of first party data points into our algorithmic models to continually enhance our bidding platform. We collect over 50 terabytes of first party data per day to enhance our insights. We employ multiple machine learning and deep learning models, including regression, random forests and neural networks.

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