People qualify themselves on digital media by their own actions. Targeted users increase value for advertisers and extend premium inventory for publisher. Highly targeted messages is possible by integrating behaviour with existing customer data collected across several new digital channels, both external and internal sources.
[ad.agio] works with Neo-Targeting, the user profiling engine by Neodata for the automatic recommendation of ads serving according to user’s profile.

By evaluating the user’s interaction with editorial content (text-mining analysis by Neo-TM*), click on ads, search term entered, website and pages visited, time and frequency of visit, referring domain, IP-address, new/return visit, previous campaign response, and so on, Neo-Targeting builds up a profile for each user. Various algorithms are then executed depending on the availability of the data mentioned above. Output from the various algorithms is then combined to maximize optimization.

Neo-Targeting supports data import/export (Eg. socio-demo; CRM profiles; opt-in preferences and interest etc..) from/to client-side DB both in real-time or batch mode. The client provides the unique user-id in order to univocally identify user’s data. Neo-Targeting imports explicit user information from the client DB with no restrictions on the number of data that can be transferred. Via a registration tag Neo-targeting can register explicit user preferences and interests directly on its servers.

A user may have several interests with a different share: eg. User A interested in Sport 40% and Finance 70%; user B interested in Luxury Goods 40%, Finance Loans 60% and Formula 1 80%. [ad.agio] integrates a default library of 17 marketable profiles that can be extended or modified according to the client’s needs.
In order to deliver relevant ads to each single user, Neo-Targeting performs a combination of batch profiling process (clustering) and some real-time knowledge based reasoning that takes into consideration user profile.