ADOHM is all set to revise the digital media purchasing arena. Autonomous media buying is when AI performs advanced media purchasing for you. When you apply ADOHM to the media buying procedure, data gathered from past exchanges, exercises etc are accumulated and real time predictions to allocate budgets are generated. It utilizes machine learning algorithms to predict productive campaigns. Furthermore, It analyses the strategies from past encounters and predicts which channels would be more effective. ADOHM performs placing of programmatic ads, social media advertising etc and delivers results much faster. Instead of the traditional media purchasing framework which is totally human reliant, AI influenced media purchasing requires practically zero human cooperation or supervision.
Marketers who have adapted ADOHM into their marketing strategy can rest with ease, as the platform offers complete data transparency. By integrating ADOHM into their marketing strategies, the data collected can be accounted for by the platform, subsequently maintaining transparency - as ADOHM aims at relieving marketers from the downfalls of existing practices. ADOHM filters through consumer data consistently generating insights. It uses existing and incoming data to determine which content would be suitable for consumer segments and carries out the entire media purchasing process by bidding proactively. The revolutionary tool works 24/7, adjusting to minor changes and enhancing algorithms to suit your requirements.
Statistics state that almost $7.2 Billion was lost due to ad fraud in the previous financial year. Furthermore, marketers might not even contradict the matter until warning signs such as poor on-site analytics and abnormally high CTRs show up. ADOHM aims at eradicating the ad fraud epidemic from the industry. ADOHM’s superior algorithms avail the capability to sift through fake bot traffic and dummy websites discarding them instantly. As ADOHM learns from every encounter with incoming data, it ensures the safety of campaigns significantly.